AACFlow против Make
AACFlow — ИИ-рабочее пространство, где команды создают, развёртывают и сопровождают ИИ-агентов визуально, в диалоге или кодом. Вот как AACFlow соотносится с Make по архитектуре платформы, возможностям ИИ, интеграциям, ценам, безопасности и поддержке. Каждый факт ниже подтверждён источником и датой, последняя проверка: .
AACFlow — ИИ-рабочее пространство для создания, развёртывания и сопровождения ИИ-агентов. На этой странице AACFlow сравнивается с Make по архитектуре платформы, возможностям ИИ, интеграциям, ценам, безопасности и соответствию требованиям, наблюдаемости и поддержке; используются факты с источниками и датами для тех, кто выбирает между двумя платформами.
Что такое 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.
Что такое Make?
Make (make.com) is a closed-source, cloud-only visual workflow-automation platform where users connect app "modules" on a canvas into scenarios. It now also offers AI Agent blocks, an MCP server, and a JS/Python code step, billed on a per-module-execution credit model.
AACFlow и Make: сравнение по возможностям
В разделах ниже AACFlow и Make сравниваются по платформе и развёртыванию, ценам, безопасности и соответствию требованиям, возможностям ИИ, интеграциям, наблюдаемости и поддержке.
Платформа и развёртывание
Тарифы
Безопасность и соответствие требованиям
Возможности ИИ
Интеграции
Наблюдаемость и надёжность
Поддержка
Сильные стороны AACFlow
AI Copilot / Chat agent-building surface (источник: AACFlow Docs: Copilot, откроется в новой вкладке)
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 (источник: AACFlow codebase: KB schema + file-parsers, откроется в новой вкладке)
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 (источник: AACFlow Docs: MCP Deployment, откроется в новой вкладке)
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 (источник: AACFlow Docs: Workspace Forks, откроется в новой вкладке)
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 (источник: AACFlow Docs: Human in the Loop Block, откроется в новой вкладке)
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 (источник: AACFlow codebase: realtime presence handler, откроется в новой вкладке)
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.Задокументированные ограничения Make
No self-hosting of the core platform (источник: Make on-prem agents page, откроется в новой вкладке)
No self-hosted deployment; only a network-bridging on-prem agent.
Make is a fully managed multi-tenant SaaS; there is no option to run the Make engine itself on customer infrastructure. The only on-prem artifact is a lightweight 'agent' that bridges Make's cloud to a private network, not a self-hosted deployment of the platform.Proprietary, closed-source license (источник: Master Services Agreement for Make, Section 4.4 & 6.1 (Celonis), откроется в новой вкладке)
Closed-source codebase with no community fork or audit path.
Unlike open-source workflow tools, Make's codebase is not published; Celonis (Make's owner) retains exclusive ownership of the Services, and customers are contractually barred from copying, modifying, creating derivative works from, or reverse-engineering the platform, so there is no community fork/self-audit path and organizations depend entirely on Celonis's roadmap and infrastructure.Code step allows direct HTTP calls; custom package installs need Enterprise (источник: Make Code app docs, откроется в новой вкладке)
Code step permits HTTP calls; custom package installs are Enterprise-only.
The native Make Code (JS/Python) module can make direct HTTP requests, though Make recommends using the dedicated HTTP module instead to avoid exposing credentials. Enterprise-plan customers can import custom third-party npm/PyPI libraries as declared dependencies; lower tiers only get Make's pre-installed common libraries.Granular RBAC gated to the Teams plan and above (источник: Make Pricing page, откроется в новой вкладке)
RBAC needs the Teams plan ($38/mo) or above.
Full team/role-based permission management ('Teams and team roles', letting admins manage unlimited team permissions for scenario apps, templates, and connections) is only listed as a feature starting on the Teams plan ($38/mo) and Enterprise; lower tiers (Free, Core, Pro) get unlimited users but no role-based access controls, unlike AACFlow, which ships admin/write/read roles on every tier.Итог
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 Make if you specifically need 3,000+ integrations and an 8,000+ template gallery: Make lists 3,000+ integration apps and a public gallery of over 8,000 pre-built, importable scenario templates, free to browse on every plan including Free.
Что почитать ещё
Часто задаваемые вопросы
AACFlow is an AI workspace where teams build, deploy, and manage AI agents visually, conversationally, or with code. Make (make.com) is a closed-source, cloud-only visual workflow-automation platform where users connect app "modules" on a canvas into scenarios. It now also offers AI Agent blocks, an MCP server, and a JS/Python code step, billed on a per-module-execution credit model. Teams considering a switch typically weigh pricing model, and how AI-native the platform's agent-building experience is.

