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AACFlow vs. Flowise

AACFlow ist der KI-Workspace, in dem Teams KI-Agenten visuell, im Dialog oder mit Code erstellen, bereitstellen und verwalten. So schneidet AACFlow im Vergleich zu Flowise bei Plattformarchitektur, KI-Fähigkeiten, Integrationen, Preisen, Sicherheit und Support ab. Jeder Fakt unten ist belegt und datiert, zuletzt geprüft am .

AACFlow ist ein KI-Workspace zum Erstellen, Bereitstellen und Verwalten von KI-Agenten. Diese Seite vergleicht AACFlow mit Flowise bei Plattformarchitektur, KI-Fähigkeiten, Integrationen, Preisen, Sicherheit und Compliance, Observability und Support – mit belegten, datierten Fakten für Entscheider, die beide Plattformen bewerten.

Was ist AACFlow?

AACFlow is the AI workspace where teams build, deploy, and manage AI agents, connecting 1,000+ integrations and every major LLM to automate real work visually, conversationally, or with code.

Was ist Flowise?

Flowise is an open-source, low-code visual builder for LLM chains, RAG pipelines, and multi-agent AI workflows, available self-hosted or as a managed cloud service, and owned by Workday since August 2025.

AACFlow vs. Flowise: Funktionsvergleich

Die folgenden Abschnitte vergleichen AACFlow und Flowise bei Plattform und Bereitstellung, Preisen, Sicherheit und Compliance, KI-Fähigkeiten, Integrationen, Observability und Support.

Plattform und Bereitstellung

CompareAACFlow vs Flowise
AACFlow
Flowise
Builder-Typ
Flowise
Visual canvas plus custom-code nodes (Quelle: Flowise Docs: Custom JS Function, öffnet in neuem Tab)Flowise is primarily a drag-and-drop visual canvas for wiring chatflow and agentflow nodes together, supplemented by Custom JS Function nodes for arbitrary code and a Custom Tool node for JS-based tools. There is no natural-language "describe it and I'll build it" flow generator.. No natural-language workflow generation feature.
Lernkurve
AACFlow
Low, plus natural-language Chat for non-technical users (Quelle: AACFlow Docs: Introduction (visual, natural-language, and API/SDK building), öffnet in neuem Tab)Low for visual building; natural-language Chat surface (with a workflow-scoped Copilot) for non-technical builders. Chat lets users describe a workflow in plain language and have AACFlow scaffold or edit it; the visual canvas requires no code to connect blocks.
Flowise
Easy to start, technical depth needed for production (Quelle: Flowise Docs: Custom JS Function, öffnet in neuem Tab)Approachable for non-technical users via templates and drag-and-drop nodes, but real production use (custom tools, external libraries, env vars) requires developer comfort with JavaScript and LangChain concepts.
Bereitstellungsoptionen
AACFlow
Managed cloud, no single-tenant VPC option (Quelle: AACFlow Pricing Page, öffnet in neuem Tab)Cloud-hosted (managed, multi-tenant SaaS) operated by AACFlow. No documented managed single-tenant/VPC hosting tier. AACFlow is sold as a managed cloud service; there is no dedicated-instance/VPC offering.
Flowise
Self-hosted, cloud, and enterprise on-prem/air-gapped (Quelle: Lindy: Flowise Pricing, Features, and Alternatives for 2026, öffnet in neuem Tab)Flowise offers self-hosted open-source deployment (Docker/npm), a managed multi-tenant Cloud plan, and an Enterprise tier supporting on-premise or air-gapped deployment for regulated industries.
Vorlagen
AACFlow
(Quelle: AACFlow codebase: templates gallery and APIs removed, öffnet in neuem Tab)No: the pre-built workflow template gallery (landing and in-workspace) was removed platform-wide. AACFlow now surfaces per-integration starter prompts instead of a template library.
Flowise
(Quelle: DeepWiki: Marketplace & Template Flows, öffnet in neuem Tab)Yes: Flowise ships a Marketplace of pre-built, production-ready chatflow and agentflow templates (document Q&A/RAG, SQL agents, multi-agent orchestration), filterable by type, framework, and use case, plus support for organizations to save their own custom templates.
Übernahme zwischen Umgebungen
AACFlow
(Quelle: AACFlow Docs: Workspace Forks, öffnet in neuem Tab)Yes: fork a whole workspace into a dev/qa/prod-style child, diff it, and promote or roll back changes in either direction. Credential and env-var remapping is required before every promote, so secrets are never silently copied across environments. Gated to the Enterprise plan.
Flowise
Unknown / not documentedUnknown: no documentation describes forking or cloning a whole project or workspace and promoting it between dev, QA, and production environments. Flowise's version control works at the level of individual chatflow/assistant history snapshots, not whole-environment promotion.
Versionskontrolle
AACFlow
Deployment rollback plus Copilot edit diff/revert (Quelle: AACFlow codebase: WorkflowDiffEngine, öffnet in neuem Tab)Deployed-version history with rollback for every workflow; server-persisted checkpoint/revert and visual diff (accept/reject) specifically for Copilot AI edits. Manual drag-and-drop undo/redo is client-side/localStorage only (capped at 100 ops, 5 stacks), not server-synced across devices. Deployment history does not include an arbitrary version-to-version diff tool, and knowledge base documents have no version history.
Flowise
(Quelle: GitHub PR #5024: Implement version control system for ChatFlows and Assistants, öffnet in neuem Tab)Yes: Flowise automatically saves a version snapshot every time you save a ChatFlow or Assistant, with a history view to restore prior versions. This is snapshot-and-restore depth, not full diff or branching.
Echtzeit-Zusammenarbeit
AACFlow
(Quelle: AACFlow codebase: realtime presence handler (cursor/selection broadcast), öffnet in neuem Tab)Yes: live multiplayer editing of the same workflow canvas, with real-time cursors, selection broadcasting, and synced concurrent edits over a dedicated realtime backend
Flowise
(Quelle: Flowise Docs: Workspaces, öffnet in neuem Tab)No: Flowise's canvas supports only one user per session, with no live, multi-cursor editing of the same flow. Cloud/Enterprise multi-user features (workspaces, RBAC) govern access, not concurrent editing.. No public Flowise GitHub issue specifically tracks multi-cursor/real-time canvas collaboration as a feature request; GitHub issue #2661, sometimes cited for this, is actually a closed request about user authentication, RBAC, and audit trails, not concurrent editing.
Nativer Dateispeicher
AACFlow
(Quelle: AACFlow codebase: file share modal (password/email/SSO modes), öffnet in neuem Tab)Yes: a native Files area with folder hierarchy, link-based sharing (public, password, email OTP, or SSO auth), and a workspace-level Recently Deleted view covering workflows, tables, knowledge bases, files, and folders. Admins can restrict which share-auth modes (public/password/email/SSO) a permission group is allowed to use.
Flowise
Unknown, only per-node file uploads documentedUnknown: no documented general-purpose file storage system with folder hierarchy, link-sharing with access controls, or recovery of deleted items. Flowise's file handling is scoped to per-node uploads and Document Store ingestion, not a standalone file manager.
Native Datentabellen
AACFlow
(Quelle: AACFlow Docs: Tables, öffnet in neuem Tab)Yes: a native spreadsheet-like Tables feature (typed columns, not an external DB connector) with full keyboard support (arrow keys, Tab, copy-paste bulk load, Cmd/Ctrl+Z undo) and atomic per-row writes from multiple workflows at once. No public fixed row-limit figure is documented (guidance says paginate reads past ~100k rows); a workflow can also be wired to run per row via a "workflow column."
Flowise
Unknown, not documented as a native featureUnknown: no native spreadsheet-like data table feature with row/column limits and keyboard navigation is documented. Flowise's structured-data support comes through external database and vector-store connector nodes instead.
Rich-Text-Dokumenteditor
AACFlow
(Quelle: AACFlow codebase: rich markdown editor, öffnet in neuem Tab)Yes: markdown files opened in the Files viewer render in an inline WYSIWYG-style rich markdown editor, with inline @-mention links to other AACFlow resources
Flowise
Unknown, not documentedUnknown: no documented inline rich-text/WYSIWYG markdown editor for documents stored in Flowise.
Sub-Workflows (Komposition)
AACFlow
(Quelle: AACFlow Docs: Workflow block, öffnet in neuem Tab)Yes: a Workflow block calls another saved workflow as a step, waits for it to finish, runs its latest deployed version, and maps parent variables into the child's input form. Self-references are blocked to prevent infinite recursion.
Flowise
(Quelle: Flowise Docs: Agentflow V2 (Execute Flow node), öffnet in neuem Tab)Yes: Flowise's Execute Flow node calls another saved Chatflow or Agentflow as a step, passes it input, waits for the child flow to finish, and receives its output back to continue the parent flow.
Eigene Blöcke (organisationsweite Wiederverwendung)
AACFlow
(Quelle: AACFlow codebase: custom-blocks publish API (admin gate), öffnet in neuem Tab)Yes: a user with admin access on a workflow's workspace can publish its deployed version as a named, iconed custom block that appears in the block toolbar for the whole organization. Inputs are read live from the source workflow's Start block; the publisher picks which outputs to expose. The block always runs the source workflow's latest deployed version, and its internal steps and intermediate values are never exposed to consumers. Enterprise-gated. Distinct from the Workflow (sub-workflow) block, which composes a workflow the same author controls, and from custom code/tool blocks, which run inline code rather than a full deployed workflow.
Flowise
(Quelle: Flowise Docs: Agentflow V2 (Execute Flow node), öffnet in neuem Tab)No: Flowise has no feature for publishing a deployed chatflow/agentflow as a named, encapsulated block that appears in the node palette for other users across an organization. Its closest feature, the Execute Flow node, only lets a flow call another saved flow by name or ID from within the same Flowise instance, passing input and receiving output; the docs describe this as invoking an existing flow, not publishing a version-synced, credential-hidden component into a shared toolbar. Flowise's Custom Tool node is likewise scoped to inline JavaScript written within a single flow, not a published workflow-as-block. There is no documented mechanism that hides a source flow's internal steps/credentials from consumers, restricts a published block via access control/permission groups, or automatically points every consumer at the source flow's latest deployed version.. This is distinct from Flowise's Execute Flow sub-workflow calling (see subWorkflows above), which is same-instance flow-to-flow composition, not org-wide reuse of a hidden, centrally-updated block by other users.

Preise

CompareAACFlow vs Flowise
AACFlow
Flowise
Preismodell
AACFlow
Credit-based billing, BYOK exempt from caps (Quelle: AACFlow Pricing, öffnet in neuem Tab)Credit-based usage billing (Stripe), with bring-your-own-key exemption from metered caps
Flowise
Prediction-volume based tiers (cloud), free self-hosting (Quelle: Lindy: Flowise Pricing, Features, and Alternatives for 2026, öffnet in neuem Tab)Flowise Cloud prices by monthly prediction (execution) volume plus storage tier, with separate paid plans; self-hosting is free aside from your own infrastructure and LLM costs.
Günstigster kostenpflichtiger Tarif
Flowise
$35/month Starter: unlimited flows, 10k predictions, 1GB storage (Quelle: Lindy: Flowise Pricing, Features, and Alternatives for 2026, öffnet in neuem Tab)The cheapest paid Cloud plan (Starter) is reported at $35/month, including unlimited flows, 10,000 predictions/month, and 1GB storage.. Sourced from third-party aggregator coverage; Flowise's own pricing page sits behind a login wall.
Kostenloser Tarif
AACFlow
(Quelle: AACFlow Pricing, öffnet in neuem Tab)No free tier: usage is paid for with prepaid wallet credits or a paid plan
Flowise
(Quelle: Lindy: Flowise Pricing, Features, and Alternatives for 2026, öffnet in neuem Tab)Yes: a free Cloud plan exists with 2 flows/assistants, 100 predictions per month, and 5MB storage, with community support and Flowise embed branding.
Eigener Schlüssel (BYOK)
AACFlow
(Quelle: AACFlow Docs: Bring Your Own Key (BYOK), öffnet in neuem Tab)Yes: bring-your-own-key support exempts usage from metered credit caps, and multiple keys stored for the same provider are automatically round-robin rotated, with automatic fallback past any key that fails to decrypt
Flowise
(Quelle: Flowise Docs: Environment Variables, öffnet in neuem Tab)Yes: users configure their own LLM provider API keys as encrypted credentials within Flowise (self-hosted or cloud), so LLM usage is billed directly by the provider rather than metered by Flowise beyond its own prediction-count limits.. Flowise Cloud plans still cap by predictions/month regardless of BYOK.

Sicherheit und Compliance

CompareAACFlow vs Flowise
AACFlow
Flowise
SOC 2
AACFlow
(Quelle: AACFlow Landing Page, öffnet in neuem Tab)No third-party SOC 2 report is claimed
Flowise
No official confirmation foundUnknown: a third-party security-scan aggregator (Nudge Security) lists Flowise as SOC 2 compliant among several other certifications, but Flowise has published no SOC 2 report, badge, or trust page of its own.. The same third-party source also claims FedRAMP and PCI compliance for a small startup, an atypical combination not corroborated on flowiseai.com.
Datenspeicherort
AACFlow
Cloud region toggle is global, not per-customer (Quelle: AACFlow codebase: async job region resolution, öffnet in neuem Tab)On AACFlow Cloud, async job execution has an internal US/EU region toggle, but it is deployment-wide, not a customer-selectable per-workspace residency option
Flowise
(Quelle: Lindy: Flowise Pricing, Features, and Alternatives for 2026, öffnet in neuem Tab)Yes, indirectly: self-hosting (including on-prem/air-gapped Enterprise deployment) lets an organization fully control data location. There is no dedicated regional-cloud-hosting option for the managed Cloud product.
Rollenbasierte Zugriffskontrolle
AACFlow
(Quelle: AACFlow Docs: Roles and Permissions, öffnet in neuem Tab)Yes: admin/write/read workspace permissions, org-level admin/member roles, plus Enterprise-tier permission groups that allow/deny-list specific models, tools, and integrations per group on top of those base roles. See modelAndToolGovernance and credentialGovernance for the finer-grained permission-groups layer.
Flowise
(Quelle: Flowise Docs: Workspaces, öffnet in neuem Tab)Yes: Enterprise and Cloud Workspaces support custom roles with granular per-resource permissions (full access vs. view-only). User and Workspace Management resources (Roles, Users, Workspaces, Login Activity) are restricted to Account Admins only.
Audit-Protokollierung
AACFlow
(Quelle: AACFlow codebase: auditLog table, öffnet in neuem Tab)Yes: dedicated audit_log table plus workflow execution logs, exposed via a public /v1/audit-logs API (Enterprise plan), plus continuous SIEM/warehouse export to Datadog, S3, GCS, Azure Blob, BigQuery, or Snowflake via a data-drains dispatcher
Flowise
(Quelle: Flowise Docs: Workspaces, öffnet in neuem Tab)Yes: Workspaces (Cloud and Enterprise plans) let Account Admins see every login and logout across all users. The docs do not show a separate detailed action-by-action audit trail beyond this login activity log.
Zusätzliche Compliance
AACFlow
None claimed (Quelle: AACFlow Enterprise Page, öffnet in neuem Tab)None claimed. No additional third-party certification is claimed.
Flowise
Unknown, no official certifications publishedUnknown: beyond the unconfirmed third-party SOC 2 claim, Flowise has published no HIPAA, ISO 27001, PCI, or FedRAMP certification.
Modell- und Tool-Governance
AACFlow
(Quelle: AACFlow codebase: PermissionGroupConfig (allowedModelProviders, deniedModels, deniedTools), öffnet in neuem Tab)Yes: enterprise "permission groups" let an admin allow-list/deny-list specific LLM providers and models, and separately deny specific tools/integrations (or disable all MCP or custom tools) per group, layered on top of workspace admin/write/read roles. This does not control whether an LLM provider retains prompts. AACFlow offers no "zero data retention" mode or governed AI gateway. A separate, Enterprise-gated feature lets orgs set a log-retention window and redact PII, but that only controls how long AACFlow itself keeps execution logs.
Flowise
Unknown, RBAC is resource-level not model/tool-specificUnknown: no documented admin controls restrict which specific LLM providers/models or which tools/integrations a given role may use. Flowise's RBAC governs resource-level (create/edit/delete) permissions, not model/tool allowlists.
Governance für Anmeldedaten
AACFlow
(Quelle: AACFlow Docs: Roles and Permissions, öffnet in neuem Tab)Yes: shared credentials (connected accounts, service accounts, workspace secrets) are their own nested permission level (Member/Admin) below organization and workspace roles, and enterprise permission groups can further allow-list specific integrations and restrict which file-share auth modes (public/password/email/SSO) a group may use. A user's personal environment variables/secrets are never shared or inherited by anyone, including org owners/admins.
Flowise
Credentials shareable across workspaces; per-role credential limits unclear (Quelle: Flowise Docs: Workspaces, öffnet in neuem Tab)Partial: credentials can be shared across workspaces in Flowise's workspace model, but there is no documented way to restrict which specific stored credential a given role/permission group may use.
Single Sign-on (SSO)
AACFlow
(Quelle: AACFlow Docs: Single Sign-On (SSO), öffnet in neuem Tab)Yes: SAML 2.0 and OIDC single sign-on, with users routed to SSO by their email domain, plus SCIM 2.0 directory provisioning for Okta, Microsoft Entra ID, OneLogin, and JumpCloud that creates, updates, deactivates, and removes members and maps pushed groups to permission groups, workspace access, and the organization admin role
Flowise
(Quelle: Flowise Docs: SSO, öffnet in neuem Tab)Yes, with a caveat: Enterprise-plan SSO supports OIDC via Microsoft Azure/Entra ID, Google, and Auth0, but has no automatic org auto-provisioning. Invited users must be added first before SSO login works.. No SAML support documented.
Individuelle Sitzungsrichtlinie
AACFlow
(Quelle: AACFlow Docs: Session Policies, öffnet in neuem Tab)Yes: Enterprise organization owners and admins can set a max session lifetime (1 to 8,760 hours from sign-in, regardless of activity) and an idle timeout (48 to 8,760 hours without activity), applied to every member on every device. Both limits are optional; leaving them empty keeps the default of 30-day sessions that extend automatically while a member stays active. A separate "Sign out all members" action immediately revokes every member session in the organization except the admin's own, for use after a security incident or an offboarding wave. The 48-hour idle floor exists because session activity is recorded at most once per day, so a shorter window could sign out members who are actively working.
Flowise
Self-hosted JWT expiry env vars; no idle timeout, no documented Cloud control (Quelle: Flowise Docs: Application authorization (JWT expiry and session variables), öffnet in neuem Tab)Partial: self-hosted server environment variables rather than an admin-console setting. JWT_TOKEN_EXPIRY_IN_MINUTES sets the access-token lifetime and JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES sets the refresh-token lifetime, which together bound how long a sign-in survives, and EXPIRE_AUTH_TOKENS_ON_RESTART invalidates all tokens on server restart. No idle/inactivity timeout is documented, and Flowise does not document any equivalent control for admins of the managed Flowise Cloud product.. The shipped .env.example sets JWT_TOKEN_EXPIRY_IN_MINUTES=360 and JWT_REFRESH_TOKEN_EXPIRY_IN_MINUTES=43200 (30 days); the Application authorization docs page instead cites defaults of 60 minutes and 129,600 minutes (90 days), so the documented default differs from the shipped one. Because these are process environment variables, changing them is a deploy-level action for the whole instance, not a per-organization policy an account admin can set from the Workspaces UI.
Geprüfte native Integrationen
AACFlow
(Quelle: AACFlow codebase: first-party block directory, öffnet in neuem Tab)Yes: every one of AACFlow's 266 blocks is first-party authored and code-reviewed through the standard pull-request process in the main AACFlow repository; there is no public marketplace where an arbitrary third party can publish and have other users install executable tool code without going through AACFlow's own review. Custom code steps run inside AACFlow's own isolated-vm sandbox rather than as an installable third-party skill package, so the supply-chain trust boundary is AACFlow's codebase review, not an open registry.
Flowise
(Quelle: Flowise Docs: Building Node, öffnet in neuem Tab)Yes: Flowise's nodes (LLMs, tools, vector stores, document loaders) live in the packages/components/nodes folder of the core FlowiseAI/Flowise monorepo. New nodes are contributed via GitHub pull request and reviewed/merged by the Flowise team before shipping in an official release, rather than published independently by third parties into an open, unreviewed marketplace. The separate Marketplace feature distributes JSON chatflow/agentflow templates, not installable executable code.. That PR-review process has not stopped a critical incident in vetted, first-party code: CVE-2025-59528 (CVSS 10.0) was an unauthenticated remote code execution flaw in the official CustomMCP node, where user-supplied mcpServerConfig input was passed into a JavaScript Function() constructor. Patched in 3.0.6, but VulnCheck observed in-the-wild exploitation starting April 2026 against thousands of still-exposed instances. By contrast, AACFlow documents its own thirdPartyVetting fact as every one of its 302 blocks being first-party authored and code-reviewed with no public marketplace for third-party executable code either, so the two products share the same no-open-marketplace posture; the difference is that Flowise's own review pipeline has already shipped one CVSS-10 RCE into a first-party node, which is the concrete cost of that model rather than of an unreviewed community ecosystem.
Schwärzung personenbezogener Daten (PII)
AACFlow
(Quelle: AACFlow Docs: Guardrails Block, öffnet in neuem Tab)Yes: a Guardrails workflow block detects and blocks or masks PII (30+ entity types across the US, UK, and several other countries) via Microsoft Presidio, in addition to the org-level data-retention PII policy applied to stored data
Flowise
Unknown, not documentedUnknown: no documented PII detection/redaction feature for workflow content or logs.
Individuelle Datenaufbewahrung
AACFlow
(Quelle: AACFlow Docs: Data Retention, öffnet in neuem Tab)Yes: Enterprise orgs can independently configure log retention, soft-deletion cleanup, and Chat/Copilot task cleanup (chats, runs, checkpoints, Inbox tasks) at 1 day to 5 years or Forever, applied org-wide with no per-workspace override
Flowise
Unknown, not documentedUnknown: no documented org-configurable retention windows for execution logs or soft-deleted resources.
White-Labeling
AACFlow
(Quelle: AACFlow Docs: Whitelabeling, öffnet in neuem Tab)Yes: Enterprise orgs can replace the logo, wordmark, brand name, and primary/accent theme colors across the workspace UI with their own
Flowise
Partial: widget theming yes, full logo/brand removal unclear (Quelle: GitHub Discussion #626: remove the Powered by flowise watermark, öffnet in neuem Tab)Partial: the free plan includes Flowise's own embed branding, and paid plans support customizing the embedded chat widget's theme (colors, welcome message, tooltips). Community reports indicate fully removing the "Powered by Flowise" watermark requires workarounds, not a clean built-in option.

KI-Fähigkeiten

CompareAACFlow vs Flowise
AACFlow
Flowise
Multi-LLM-Unterstützung
AACFlow
21 providers plus dynamic-resolution aggregators (OpenRouter, LiteLLM, etc.) (Quelle: AACFlow codebase: PROVIDER_DEFINITIONS, öffnet in neuem Tab)21 provider integrations (OpenAI, Anthropic, Google/Gemini, Azure OpenAI, Azure Anthropic, Groq, Cerebras, Mistral, xAI, Bedrock, Vertex, Ollama, OpenRouter, and more), with OpenRouter, LiteLLM, vLLM, and Ollama resolving models dynamically at runtime rather than from a fixed list, so effective model reach extends well beyond the 21 named providers. apps/sim/providers/models.ts defines 21 provider entries.
Flowise
(Quelle: Flowise Docs: LLMs, öffnet in neuem Tab)Yes: Flowise integrates a broad set of LLM providers including OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, Cohere, HuggingFace Inference, Ollama, and Replicate, plus (via its separate Chat Models integrations, e.g. ChatAnthropic) Anthropic Claude models, covering both hosted and self-hosted open-source models.
Agent-Reasoning-Blöcke
AACFlow
(Quelle: AACFlow codebase: block registry, öffnet in neuem Tab)Yes: dedicated agent, function-calling, RAG, code-execution, and evaluation blocks, not just data routing
Flowise
(Quelle: Flowise Docs: Agentflow V2, öffnet in neuem Tab)Yes: Flowise's Agentflow V2 provides dedicated Agent nodes plus orchestration primitives (Condition, Iteration, Human Input) for multi-step agent reasoning and tool-use loops, distinct from plain data-routing nodes.
Erstellung in natürlicher Sprache
AACFlow
(Quelle: AACFlow Docs: Copilot, öffnet in neuem Tab)Yes: Chat + in-editor AI Copilot can build and modify workflows from natural-language requests
Flowise
(Quelle: Flowise Docs: Custom JS Function, öffnet in neuem Tab)No: no documented feature lets a user describe an automation in plain language and have Flowise generate or edit the flow automatically. Flowise is primarily a drag-and-drop visual canvas, supplemented by Custom JS Function nodes for arbitrary code, with no natural-language "describe it and I'll build it" flow generator.
Wissensdatenbank / RAG
AACFlow
(Quelle: AACFlow codebase: KB schema (pgvector + tsvector), öffnet in neuem Tab)Yes: hybrid vector (pgvector) plus full-text (tsvector) search knowledge base, 11 supported file formats (csv, doc, docx, html, json, md, pdf, pptx, txt, xlsx, yaml), configurable chunking, plus 51 connectors that continuously sync external sources (Google Drive, Confluence, Slack, Gmail, GitHub, HubSpot, Linear, Jira, and more) into the knowledge base rather than a one-shot upload
Flowise
(Quelle: Flowise Docs: Document Stores, öffnet in neuem Tab)Yes: Flowise's Document Store provides a full RAG pipeline covering document loading (PDF, web pages, Word, etc.), configurable chunking/text-splitting, multiple embedding providers, and upsert into vector stores like Pinecone, Weaviate, Milvus, and FAISS.. n8n's 2026 report rated Flowise's chunking/splitter options the broadest natively available among evaluated tools.
MCP-Unterstützung
AACFlow
(Quelle: AACFlow Docs: Using MCP Tools, öffnet in neuem Tab)Yes: both MCP client (call external MCP servers) and MCP server (expose AACFlow workflows as MCP tools)
Flowise
(Quelle: Flowise Docs: Tools & MCP, öffnet in neuem Tab)Yes: Flowise acts as an MCP client, consuming external MCP servers as tools via Stdio (NPX/Docker) or Streamable HTTP transports, with prebuilt MCP integrations (GitHub, Atlassian Jira, Brave Search) and a Custom MCP node for any server.
Evaluierung und Guardrails
AACFlow
LLM-judge Evaluator plus Guardrails validation block (Quelle: AACFlow Docs: Evaluator Block, öffnet in neuem Tab)Evaluator block (LLM-judge scoring against user-defined named metrics) and Guardrails block (JSON validity, regex, RAG/hallucination scoring, PII detection/masking). These are per-call scoring/validation primitives, not a batch golden-dataset eval-suite runner or A/B prompt-testing harness.
Flowise
(Quelle: Flowise Docs: Evaluations, öffnet in neuem Tab)Yes: Flowise has a built-in Evaluations feature that runs datasets through chatflows/agentflows and scores outputs with string-match, numeric, or LLM-as-judge evaluators, reporting pass/fail rate, average tokens consumed, and latency. There is no separate, dedicated "guardrail validation" block beyond this.
Human-in-the-Loop
AACFlow
(Quelle: AACFlow Docs: Human in the Loop Block, öffnet in neuem Tab)Yes: dedicated approval block that pauses a run and waits for a human-submitted "Resume Form," with durable pause/resume via persisted execution snapshots and notification hooks (e.g. Slack, email) carrying the resume link
Flowise
(Quelle: Flowise Docs: Human In The Loop, öffnet in neuem Tab)Yes: Agentflow V2 includes a dedicated Human Input node that pauses execution and resumes only after a human approves or rejects the pending action, with separate output paths for each outcome.
Generative Medien
AACFlow
(Quelle: AACFlow codebase: Image Generator V2, öffnet in neuem Tab)Yes: dedicated image (3 provider families incl. OpenAI, Gemini, Fal.ai proxy), video (5 provider families incl. Runway, Veo, Luma, Hailuo, Fal.ai proxy), text-to-speech (7 providers), and speech-to-text (5 providers) blocks
Flowise
Partial: STT built in, image/TTS via custom tools only (Quelle: GitHub Issue #2385: Text To Speech, öffnet in neuem Tab)Partial: Flowise supports speech-to-text nodes and multi-modal image inputs. Image and audio generation can be wired in via custom tools calling providers like Replicate (Stable Diffusion) or ElevenLabs, but the standard node library has no dedicated, built-in image, video, or text-to-speech generation node.. Community GitHub issues show text-to-speech and native image generation as requested but not shipped as first-class nodes.
Dynamische Tool-Nutzung
AACFlow
(Quelle: AACFlow codebase: agent tool resolution (pre-wired only), öffnet in neuem Tab)No: an Agent block calls tools the workflow author explicitly added to it at build time, rather than browsing and picking from a broader pool (e.g. an entire MCP server catalog) at inference time. Runtime MCP "discovery" exists to resolve/refresh the schema of an already-configured tool. The model does not browse or choose from the server's full tool list.
Flowise
(Quelle: Flowise Docs: Tools & MCP, öffnet in neuem Tab)Yes: Flowise's Agent nodes and Custom MCP integration let an agent dynamically discover and select from a connected pool of tools/actions at inference time, rather than calling only a single pre-wired tool per step.
Automatischer Modell-Fallback
AACFlow
(Quelle: AACFlow codebase: executeProviderRequest (no retry/fallback), öffnet in neuem Tab)No: a failed or rate-limited LLM call is retried using AACFlow's own hosted API keys for the same model, rather than automatically switching to a different model or provider. A "fallback" comment in the provider layer refers to rotating among AACFlow's own hosted API keys for the same model, not switching models.
Flowise
Unknown, not documentedUnknown: no documented automatic retry against a different model or provider on a failed/rate-limited LLM call.
Agent-Skills
AACFlow
(Quelle: AACFlow Docs: Agent skills, öffnet in neuem Tab)Yes: named, reusable "Agent Skills" (built on the open Agent Skills / SKILL.md format) that agents load on demand via progressive disclosure, editable in-app or imported from a SKILL.md file or GitHub URL. Only the skill name and description sit in the agent's system prompt (~50-100 tokens each); the full instructions load into context only when the agent calls load_skill.
Flowise
Unknown, not documented as a distinct featureUnknown: no documented reusable, named prompt/knowledge-snippet feature invoked by reference across multiple agents, distinct from a one-off system prompt or Variables feature.. Flowise has a general Variables feature (static/runtime key-value), but it is not documented as an agent-skill abstraction.
Native Chat-Bereitstellung
AACFlow
(Quelle: AACFlow Docs: Chat Deployment, öffnet in neuem Tab)Yes: a workflow can be deployed as a public, shareable Chat interface with selectable auth (public, password, email OTP, or SSO), in addition to API and MCP deployment targets
Flowise
(Quelle: Flowise Docs: Embed, öffnet in neuem Tab)Yes: a built flow can be deployed as a shareable public chat URL or an embeddable chat widget (popup bubble or full-page, via JS script or React components), plus a REST API endpoint.
Parallele Ausführung
AACFlow
(Quelle: AACFlow Docs: Parallel block, öffnet in neuem Tab)Yes: a native Parallel block fans a run out into concurrent branches (fixed count or one per list item) and joins their results back into the workflow automatically. Contained blocks run concurrently instead of sequentially, either a fixed number of times or once per item in a list/collection, and each branch's output aggregates for downstream blocks.
Flowise
(Quelle: Flowise GitHub: "Not working parallel Node in AgentFlow 2" (#4673), öffnet in neuem Tab)No: AgentFlow V2 lets users draw a branching canvas layout, but the execution engine processes the queue one node at a time and does not run parallel branches concurrently, per user reports and Flowise's own issue tracker. This causes chat-history and input-inheritance bugs when a canvas is arranged in a parallel shape.
Agent2Agent-Protokoll (A2A)
AACFlow
(Quelle: AACFlow Docs: A2A integration, öffnet in neuem Tab)Yes: a dedicated A2A block sends messages to, tracks and cancels tasks on, and discovers the capabilities of any Agent2Agent (A2A)-compliant external agent via its Agent Card
Flowise
(Quelle: Flowise GitHub: "Support the Google A2A (Agent2Agent) Protocol" (#4283, open), öffnet in neuem Tab)No: Google A2A (Agent2Agent) protocol support is an open, unimplemented GitHub feature request (opened April 2025). Flowise supports MCP for tool-calling but has no Agent Card or agent-to-agent discovery feature.
Schleifen-/Iterationsblock
AACFlow
(Quelle: AACFlow Docs: Loop block, öffnet in neuem Tab)Yes: a Loop container block runs the blocks inside it repeatedly (For a fixed count, ForEach over a collection, While a condition holds, or Do-While), running iterations one after another; concurrent fan-out is a separate Parallel block
Flowise
(Quelle: Flowise Docs: Agentflow V2 (Iteration and Loop nodes), öffnet in neuem Tab)Yes: Flowise's Agentflow V2 has a dedicated Iteration node that takes an array and executes a nested sub-flow of steps once per item, running sequentially. Its separate Loop node instead jumps backward to re-run an earlier node, a retry cycle rather than a collection iterator.

Integrationen

CompareAACFlow vs Flowise
AACFlow
Flowise
Integrationen
AACFlow
1,000+ integrations (266 blocks, ~3,900 tool actions) (Quelle: AACFlow codebase: BLOCK_REGISTRY, öffnet in neuem Tab)1,000+ integrations counting individual API actions, built from 266 first-party blocks and roughly 3,900 underlying tool actions. AACFlow's landing page cites the "1,000+ integrations" figure; the block/tool-action counts are the same integration surface measured at a different level of granularity.
Flowise
Broad multi-category node library, exact count unverified (Quelle: Flowise Docs: Integrations, öffnet in neuem Tab)Flowise documents integration categories across LLMs, vector stores, document loaders, embeddings, tools, and MCP servers (referred to internally as "nodes"), but publishes no exact total node/integration count.
Trigger-Typen
AACFlow
Webhook, cron, chat, REST API, 61 app triggers, plus a diff-aware Tables trigger (Quelle: AACFlow Docs: Triggers overview, öffnet in neuem Tab)Webhook, schedule/cron, chat, REST API, and event-based triggers for 61 apps (Slack, Gmail, GitHub, Stripe, etc.), plus a native row-level trigger on AACFlow Tables that fires on insert/update with an optional column watch-list and emits a before/after diff
Flowise
Chat, API/webhook-style prediction calls; no schedule trigger found (Quelle: Flowise API: Complete Developer Guide, öffnet in neuem Tab)Flowise flows are triggered via the chat widget or public URL, direct REST API prediction calls (/api/v1/prediction/{chatflowId}), and Custom MCP/tool invocations. There is no dedicated cron/schedule trigger or broad library of app-specific event triggers.
Eigene Code-Schritte
AACFlow
(Quelle: AACFlow Docs: Function block, öffnet in neuem Tab)Yes: code-execution block for custom logic
Flowise
(Quelle: Flowise Docs: Custom Tool (JS function support, built-in/external modules), öffnet in neuem Tab)Yes: Flowise has a Custom JS Function node for arbitrary JavaScript (async functions, plus built-in and external Node modules) and a Custom Tool node for JS-based agent tools. There is no dedicated Python code-step node.
Konfigurierbare Code-Sandboxes
AACFlow
(Quelle: AACFlow Docs: Function block - Sandboxes, öffnet in neuem Tab)Yes: named sandboxes a workspace maintains and a Function block selects, each declaring a language, its pip or npm dependencies, optional Debian/APT system packages, and optional managed CLI tools from a catalog grouped by cloud, Kubernetes, infrastructure, deployment, data and storage, and security tools; on aacflow.io they require an active Max or Enterprise plan. Only workspace admins can create or edit sandboxes, in Settings → Sandboxes. On aacflow.io each specification is prebuilt into a reusable image so runs pay no install cost. Two sandboxes with the same language, dependency list, system packages, and managed CLI tools share one build. Every managed CLI entry uses a pinned, integrity-checked vendor artifact. With no sandbox selected, remote code runs on the dedicated Function base; import-free JavaScript stays in the local isolated runtime and ignores the sandbox selection either way.
Flowise
Self-hosted only: env-var allowlists plus a rebuild; no Cloud control (Quelle: Flowise Docs: Environment Variables (TOOL_FUNCTION_BUILTIN_DEP, TOOL_FUNCTION_EXTERNAL_DEP, ALLOW_BUILTIN_DEP), öffnet in neuem Tab)Partial: self-hosted only and at the image level. The runtime available to Custom JS Function and Custom Tool code is controlled by server environment variables: TOOL_FUNCTION_BUILTIN_DEP (which NodeJS built-in modules code may require, set to crypto,fs in the shipped .env.example and documented as accepting * for all builtins), TOOL_FUNCTION_EXTERNAL_DEP (which npm packages are importable, set to moment,lodash,pg,mysql2,mongodb,ioredis,redis,typeorm,@zilliz/milvus2-sdk-node in the same file), and ALLOW_BUILTIN_DEP, which the docs describe as allowing the project dependencies already bundled with Flowise to be used, illustrated with cheerio and typeorm. Adding an npm package that is not already bundled requires adding it to packages/components, rebuilding Flowise, and restarting the server, so it is a redeploy of your own image rather than a per-step dependency declaration; there is no runtime npm install inside the code node, and no documented way to declare OS-level system packages or preinstalled CLI binaries. Flowise does not document any way for users of the managed Flowise Cloud product to set these server environment variables.. The Custom Tool docs describe the workflow explicitly: add the package under packages/components with pnpm add, run pnpm build, "then, add the imported libraries to TOOL_FUNCTION_EXTERNAL_DEP environment variable", then restart the application. TOOL_FUNCTION_BUILTIN_DEP is additive rather than a replacement: packages/components/src/utils.ts concatenates it onto a hardcoded defaultAllowBuiltInDep list (assert, buffer, crypto, events, path, querystring, timers, url, zlib), so the shipped crypto,fs value widens that base set rather than defining it; TOOL_FUNCTION_EXTERNAL_DEP is additive in the same way, layered onto a defaultAllowExternalDependencies list of axios and node-fetch. Python is not a supported code-step runtime at all, so the configurable surface is Node-only.
API-Veröffentlichung
AACFlow
(Quelle: AACFlow Docs: API Reference - Getting Started, öffnet in neuem Tab)Yes: a public REST API (mostly under /api/, with /api/v1 reserved for logs and audit-log endpoints) supporting API-triggered workflow execution and deployment rollback. The API reference does not document SSE streaming, a resumable event buffer, a dedicated API-trigger block, or a chat-deployment surface as part of the REST API itself.
Flowise
(Quelle: Flowise API: Complete Developer Guide, öffnet in neuem Tab)Yes: any chatflow can be called as a REST API via /api/v1/prediction/{chatflowId}, with client code generated for Python, JavaScript, and cURL, and sessionId support for maintaining conversation context.
SDKs und Erweiterbarkeit
AACFlow
Official Python and TypeScript SDKs, plus MCP, code block, and A2A protocol (Quelle: AACFlow Docs: Python SDK, öffnet in neuem Tab)Official client SDKs exist for Python (aacflow-sdk, pip install aacflow-sdk) and TypeScript/JavaScript (aacflow-sdk, npm install aacflow-sdk), both wrapping the REST API (x-api-key header) with methods like execute_workflow / executeWorkflow, retry-with-backoff, and usage-limit lookups. Extensibility is further extended by MCP (client + server), a sandboxed code-execution block (JS/Python), custom tools, and an Agent-to-Agent (A2A) protocol block for external agent interop
Flowise
Embed SDKs and custom-node dev docs; no plugin marketplace found (Quelle: npm: flowise-embed, öffnet in neuem Tab)Partial: Flowise provides official embed SDKs (a flowise-embed JS package and React BubbleChat/FullPageChat components) and a documented process for building custom nodes to contribute. There is no first-party marketplace for community-built node plugins beyond the flow-template Marketplace.
Als MCP-Server veröffentlichen
AACFlow
(Quelle: AACFlow Docs: MCP Deployment, öffnet in neuem Tab)Yes: any deployed workflow can be published as a tool on an MCP server (private, API-key protected, or public/no-auth), with ready-to-paste client config generated for Codex, Cursor, Claude Code, Claude Desktop, and VS Code
Flowise
(Quelle: Flowise Docs: Tools & MCP, öffnet in neuem Tab)No: Flowise's documentation covers only consuming external MCP servers as an MCP client. It has no capability for publishing a deployed Flowise flow itself as a callable MCP server for other AI tools.. Third-party community wrapper packages (e.g. mcp-flowise) expose Flowise chatflows via MCP externally, but this is not native.

Observability und Ausfallsicherheit

CompareAACFlow vs Flowise
AACFlow
Flowise
Tracing und Observability
AACFlow
(Quelle: AACFlow codebase: TraceSpan tree builder, öffnet in neuem Tab)Yes: execution logs include a per-block/per-span trace view (duration, cost, token counts, and latency stats like TTFT/TPS) with expandable nested iteration groups, plus a "View Snapshot" frozen copy of the workflow structure and block states at run time for debugging. This trace view is built directly into AACFlow rather than a raw export browsable in an external tool like Jaeger, and does not expose aggregate latency-percentile charts (p50/p95/p99). The run snapshot serves as a log-detail/debugging artifact rather than a resumable mid-run checkpoint.
Flowise
(Quelle: Langfuse: Observability and Tracing for Flowise, öffnet in neuem Tab)Yes: Flowise provides built-in analytics/observability and integrates with third-party tracing tools (Langfuse, Opik) for per-execution, block-level trace views including duration, cost, and token usage, beyond simple aggregate stats.
Ausfallsicherheit und Wiederholungen
AACFlow
Tool-call retries (up to 10x); single-attempt job orchestration (Quelle: AACFlow codebase: ToolRetryConfig (exponential backoff), öffnet in neuem Tab)Individual tool/API calls have configurable exponential-backoff retry (up to 10 attempts). The background job-orchestration layer itself retries only once by design. Durability instead comes from consecutive-failure tracking on schedules and the human-in-the-loop snapshot pause/resume mechanism. AACFlow does not offer guaranteed-once-only block execution, a failed-run holding queue for manual recovery, or a "replay a past execution with its original inputs" feature. The per-execution debugging snapshot serves as a log-detail artifact rather than a resumable mid-run checkpoint.
Flowise
Unknown, not documentedUnknown: no documentation describes automatic retries, checkpointing, or replay of a past execution with its original inputs.
Fehlerbenachrichtigung
AACFlow
(Quelle: AACFlow Docs: AACFlow Workspace Events trigger, öffnet in neuem Tab)Yes: a sim_workspace_event trigger fires on run success/failure, deployments, and cost/latency spikes, wired to any notification block (Slack, email, webhook) for real-time alerting
Flowise
Unknown, not documentedUnknown: no documented proactive notification (email/Slack/webhook) when a run fails or crosses a cost/latency threshold, beyond viewing failures in logs/observability tools.
Data Drains
AACFlow
(Quelle: AACFlow Docs: Data Drains, öffnet in neuem Tab)Yes: Enterprise orgs can continuously export workflow logs, job logs, or audit logs on a schedule to a customer-owned S3 bucket, GCS bucket, Azure Blob container, BigQuery table, Snowflake table, Datadog logs intake, or an HTTPS webhook. Each drain exports exactly one data source; multiple drains are created to export multiple sources. Viewing drain config/run history is restricted to org owners/admins.
Flowise
Partial: trace export to Langfuse/Opik only, no generic data-drain found (Quelle: Langfuse: Observability and Tracing for Flowise, öffnet in neuem Tab)Partial: Flowise supports exporting execution traces to external observability platforms (Langfuse, Opik) on an ongoing basis, but has no documented way to export raw execution/audit/usage data to generic destinations like S3, BigQuery, or Datadog.
Asynchrone Ausführung
AACFlow
(Quelle: AACFlow codebase: async execution handler, öffnet in neuem Tab)Yes: a workflow can be triggered in fire-and-forget async mode, returning HTTP 202 with an execution ID immediately, then polled through the canonical execution resource across queued/running/terminal states. Async runs are tracked by execution ID through the same execution status endpoint used for durable logs rather than a separate queue-job resource.
Flowise
Partial: queue mode exists, prediction API is documented as synchronous (Quelle: Flowise Docs: Running Flowise using Queue, öffnet in neuem Tab)Partial: Flowise supports a queue-based execution mode ("Running Flowise using Queue") for scaling background job processing, but the standard /api/v1/prediction endpoint is documented as a synchronous call, with no clear poll-for-result async API pattern.
Ausführungslimits
AACFlow
5-50 min sync; async defaults to 90 min, Enterprise up to 7 days (Quelle: AACFlow Docs: Concurrent Executions, öffnet in neuem Tab)Plan-gated: synchronous runs time out at 5 minutes on accounts without a plan and 50 minutes on paid plans; async runs default to 90 minutes, while Enterprise policy can be configured up to 7 days; concurrency ranges from 10 to 1,000 executions per billing account depending on plan. A direct async API request can shorten the account policy for that request, but cannot extend it. Concurrency limits are published in the platform cost docs, where the Enterprise limit is 1,000 by default and customizable. A run that exceeds its time limit is terminated and marked failed with a timeout error.
Flowise
Unknown, only monthly prediction caps are publishedUnknown: Flowise publishes no numbers for maximum single-execution duration or concurrency limits, beyond monthly prediction-count caps tied to Cloud pricing tiers.
Behandlung von Teilausfällen
AACFlow
(Quelle: AACFlow codebase: error-output edge routing, öffnet in neuem Tab)Yes: any block can be wired to a dedicated error-output edge, so a failing step routes execution down an error-handling branch instead of always halting the entire run
Flowise
(Quelle: Flowise Docs: Agentflow V2, öffnet in neuem Tab)Yes: Agentflow V2's conditional branching and Human Input reject-path let a workflow route around a problematic step (e.g. loop back for refinement) rather than only halting entirely, though there is no dedicated "catch/error-handler" node distinct from conditional routing.
Unbeaufsichtigte Ausführung
AACFlow
(Quelle: AACFlow codebase: trigger.dev background job backend, öffnet in neuem Tab)Yes: scheduled, webhook, and chat-triggered runs execute as background jobs on trigger.dev workers, entirely on AACFlow's servers. No client device needs to be open, awake, or connected for a run to fire or complete; closing the browser tab or shutting down a laptop has no effect on a scheduled or triggered workflow.
Flowise
(Quelle: Flowise API: Complete Developer Guide, öffnet in neuem Tab)Yes, for the triggers Flowise has: a chat message, a REST API prediction call, or an MCP tool invocation all execute entirely on the Flowise server (self-hosted or Flowise Cloud), with no dependency on a client device staying open, awake, or connected. Flowise has no dedicated cron/schedule trigger of its own, so a genuinely unattended, time-based run has to come from an external scheduler (e.g. a cron job or another system calling the prediction API) rather than a built-in scheduling engine.. Once a run is invoked by any supported means, closing the browser tab or disconnecting the calling client has no effect on that run completing server-side; the caveat is only that Flowise itself cannot originate a scheduled run without an outside trigger.

Support

CompareAACFlow vs Flowise
AACFlow
Flowise
Support-Kanäle
AACFlow
Community support plus Enterprise 'Dedicated Support' (Quelle: AACFlow Pricing Page, öffnet in neuem Tab)Community plus an unquantified "Dedicated Support" flag on the Enterprise plan. Enterprise and pricing pages do not include CSM, onboarding/enablement, or professional-services details beyond a plan-comparison-table "Dedicated Support" flag.
Flowise
Community (free), priority (Pro), dedicated (Enterprise) (Quelle: Lindy: Flowise Pricing, Features, and Alternatives for 2026, öffnet in neuem Tab)Flowise offers community support (GitHub, Discord) on free/self-hosted tiers, priority support on the Pro Cloud plan, and personalized/dedicated support on Enterprise.
SLA
AACFlow
(Quelle: AACFlow Pricing Page, öffnet in neuem Tab)Yes: the Enterprise plan includes a "Dedicated Support" feature per the pricing plan-comparison table; no SLA terminology, response-time, or uptime figures are published on the enterprise or pricing pages
Flowise
Yes, ~99.99% SLA claimed on Enterprise plan (Quelle: Lindy: Flowise Pricing, Features, and Alternatives for 2026, öffnet in neuem Tab)A formal SLA (99.99% uptime) is offered on the Enterprise plan per third-party coverage; no SLA is documented for lower tiers.. No official Flowise SLA page confirms this figure.
Community
AACFlow
Flowise
~54,000 GitHub stars, active Discord community (Quelle: GitHub: FlowiseAI/Flowise, öffnet in neuem Tab)Flowise's GitHub repository has approximately 54,000 stars (Apache 2.0 licensed core), with an active Discord community whose exact member count is not published.
Academy / Schulungen
AACFlow
(Quelle: AACFlow Docs: Academy, öffnet in neuem Tab)Yes: AACFlow Academy is a dedicated structured-learning section of the docs site, separate from reference documentation and the API reference
Flowise
No official academy; only third-party courses exist (Quelle: Coursera: Designing a Customer Support Chatbot Using Flowise, öffnet in neuem Tab)Flowise runs no official academy or certification program. Third-party platforms (Coursera, Codecademy, Udemy) offer independent Flowise courses and certificates of completion, and Flowise maintains standard docs and YouTube tutorials.

Herausragende Funktionen von AACFlow

AI Copilot / Chat agent-building surface (Quelle: AACFlow Docs: Copilot, öffnet in neuem Tab)

Chat builds and manages work across the workspace; in-editor Copilot edits a single workflow.

A workspace-wide natural-language surface (Chat) that can build workflows, manage data, and take actions across integrations, plus an in-editor Copilot scoped to building and editing a single workflow directly.

Hybrid semantic + keyword knowledge base (Quelle: AACFlow codebase: KB schema + file-parsers, öffnet in neuem Tab)

Combines vector and full-text search with configurable chunking across 11 file formats.

Built-in RAG with pgvector embeddings and a generated tsvector column for combined vector + full-text search, plus a token-based chunker with configurable chunk size/overlap and 11 supported file formats (csv, doc, docx, html, json, md, pdf, pptx, txt, xlsx, yaml).

Native MCP client and server (Quelle: AACFlow Docs: MCP Deployment, öffnet in neuem Tab)

Call external MCP servers as tools, or expose AACFlow workflows as an MCP server.

A dedicated MCP block lets any workflow call external MCP servers as a tool, and a serve/workflow-servers API surface lets AACFlow expose its own workflows as MCP servers.

Fork a workspace into dev, qa, and prod environments (Quelle: AACFlow Docs: Workspace Forks, öffnet in neuem Tab)

Fork, diff, and promote environments with mandatory credential remapping.

Fork a whole workspace into a dev/qa/prod-style child environment, preview a diff, and promote changes bidirectionally. Credential and env-var remapping is required on every promote, so secrets never cross environments silently.

Human-in-the-loop approvals with durable resume (Quelle: AACFlow Docs: Human in the Loop Block, öffnet in neuem Tab)

Pause a run for human approval and resume later via a durable snapshot link.

A dedicated block pauses a run and waits for a human-submitted approval form, backed by persisted execution snapshots so the run can resume later via a link, even after a server restart.

Live multiplayer canvas editing (Quelle: AACFlow codebase: realtime presence handler, öffnet in neuem Tab)

Real-time cursors, selections, and synced edits on the same canvas.

Real-time cursors, selection broadcasting, and synced concurrent edits over a dedicated realtime backend, so a team can build the same workflow together at the same time.

Dokumentierte Einschränkungen von Flowise

Low enterprise-readiness score in third-party benchmarking (Quelle: n8n: 2026 AI Agent Development Tools report, öffnet in neuem Tab)

Scored only 37% on enterprise-readiness in a third-party 2026 vendor report.

The n8n 2026 AI Agent Development Tools report scored Flowise at 37% on "Enterpriseness," versus 63% on "Codability," citing gaps in security features, authentication mechanisms, and production-grade governance compared to top-performing platforms.

No native real-time multiplayer canvas editing (Quelle: GitHub Issue #2661: Multi User Support (closed, not planned), öffnet in neuem Tab)

No live multi-cursor concurrent editing of the same flow.

Flowise's core canvas supports only one user editing a flow at a time, with no built-in real-time co-editing of the same chatflow. A related multi-user/collaboration feature request (GitHub issue #2661) was closed as not planned.

Fazit

Choose AACFlow if you want an AI workspace that treats AI agents as first-class citizens: native multi-LLM support, real-time multiplayer editing, environment promotion (dev/qa/prod), human-in-the-loop approvals, and enterprise governance (SSO, credential-level permissions, audit logs) built in rather than bolted on.

Choose Flowise if you specifically need choice of vector-store backend, with the broadest native text-splitter menu: Flowise's Document Store lets a builder pick from a wide range of vector store backends to upsert into (Pinecone, Weaviate, Milvus, FAISS, and more), and offers the broadest range of native text-splitter types (character, token, recursive character, markdown, code, HTML-to-markdown) with configurable chunk size and overlap, a live preview before processing, and per-chunk editing.

Häufig gestellte Fragen

AACFlow is an AI workspace where teams build, deploy, and manage AI agents visually, conversationally, or with code. Flowise is an open-source, low-code visual builder for LLM chains, RAG pipelines, and multi-agent AI workflows, available self-hosted or as a managed cloud service, and owned by Workday since August 2025. Teams considering a switch typically weigh pricing model, and how AI-native the platform's agent-building experience is.

Jeder Agent Ihres Unternehmens. Alles an einem Ort.