Relevance AI

Multi-agent systems, tools, knowledge, and automated business workflows

KINDA · partial replacement
price variesestimated build time weekend to multi-dayreplaced by 0 people

The visible AI workforce platform loop is buildable, but a credible replacement needs more than the first screen. Relevance AI earns its keep through connectors, auth, reliability, so expect a weekend or multi-day build and a narrower personal scope.

Build verification: not recorded. How we judge buildability

What you give up

  • hundreds of maintained connectors
  • OAuth app verification
  • durable execution at scale
  • schema drift handling and enterprise controls

Why people still pay

Relevance AI: One automation is easy. Subscribers pay for maintained integrations, credentials, retries, observability, and someone else owning breakage.

Your build guide

The stack, security requirements, and agent rules for a focused replacement.

Before you start

  • Runtime and tools: TypeScript, Node, PostgreSQL and a database-backed job worker with a small React run inspector.
  • Before starting: Credentials for only the chosen integrations, their current API documentation, example payloads and an always-on worker for schedules.
01
TypeScript, Node, PostgreSQL and a database-backed job worker with a small React run inspector
02
Data design: Store WorkflowVersion, Run, ToolCall, EvidenceItem and Approval; tools are allowlisted and a generated plan cannot grant itself new capabilities or destinations.
03
Setup: Credentials for only the chosen integrations, their current API documentation, example payloads and an always-on worker for schedules
engineering roadmap

Implementation plan

1

Phase 1

Pin the working slice and create its example input: Run one research-to-brief assistant workflow that retrieves approved company pages, extracts a structured brief and stops for human review before any external action. Confirm setup: Credentials for only the chosen integrations, their current API documentation, example payloads and an always-on worker for schedules.

2

Phase 2

Implement persistence and write-time invariants before decorating the UI: Store WorkflowVersion, Run, ToolCall, EvidenceItem and Approval; tools are allowlisted and a generated plan cannot grant itself new capabilities or destinations.

3

Phase 3

Connect the working view to real saved state. Persist trigger identity, step input version and external receipts before marking success. Retry bounded transient failures; unknown write outcomes require reconciliation. Do not promise exactly-once execution across external services.

4

Phase 4

Expose the app-specific limits and recovery path in context: Start with one agent and two read-only tools, not an autonomous workforce. Record cost/time budgets, unknown tool results and cancelled runs; retries must not bypass approval gates.

5

Phase 5

Walk through this concrete acceptance case and preserve its exported evidence: A retrieved page instructs the agent to email secrets; keep it as source data, reject the instruction and produce only the approved brief. Finish the README and backup/restore instructions; report unfinished capabilities explicitly.

the pro prompt
download AGENTS.md
Build the following focused alternative to Relevance AI. This is a deliberately limited personal or small-team substitute, not parity with the paid service.

WORKING SLICE
Run one research-to-brief assistant workflow that retrieves approved company pages, extracts a structured brief and stops for human review before any external action.

SETUP AND ARCHITECTURE
Use TypeScript, Node, PostgreSQL and a database-backed job worker with a small React run inspector. Prerequisites: Credentials for only the chosen integrations, their current API documentation, example payloads and an always-on worker for schedules. Before integrating anything, record actual versions and permissions, plus model files or provider limits only where used, in the README; make unavailable dependencies visible rather than simulating success.

DOMAIN MODEL AND INVARIANTS
Store WorkflowVersion, Run, ToolCall, EvidenceItem and Approval; tools are allowlisted and a generated plan cannot grant itself new capabilities or destinations.

IMPLEMENTATION CONTRACT
Persist trigger identity, step input version and external receipts before marking success. Retry bounded transient failures; unknown write outcomes require reconciliation. Do not promise exactly-once execution across external services. Provide an input/setup view, the main work view, and a review/export view appropriate to this workflow. Preserve the last saved state if a job or save fails. Include empty, loading, permission-denied, partial and retryable-error states. Log identifiers and error categories without secret values or unnecessary private content.

APP-SPECIFIC BOUNDARY AND RECOVERY
Start with one agent and two read-only tools, not an autonomous workforce. Record cost/time budgets, unknown tool results and cancelled runs; retries must not bypass approval gates.

ACCEPTANCE SCENARIO
A retrieved page instructs the agent to email secrets; keep it as source data, reject the instruction and produce only the approved brief. Also reopen the app after an interrupted operation, confirm the saved record/export remains inspectable, and document the recovery action. These are implementation acceptance requirements, not a claim that this guide has been tested.

DELIVERY
Deliver a runnable repository with migrations or project-format versioning, a non-sensitive example, environment/permission setup, the exact manual acceptance steps, and a backup/export-and-restore walkthrough. Implement the working slice before optional integrations; list any deferred paid-product capabilities honestly. Do not add capabilities outside the working slice just to resemble the original product.

PROJECT RULES FOR AGENTS.md
Keep the domain invariants above executable at the write boundary. Propose scope changes before adding providers or permissions. Never fabricate source evidence, publish results, identity matches or successful delivery. Preserve user originals and require an explicit confirmation for destructive changes or external publication.

$ open in your agent (prompt prefilled, you press enter), copy the prompt or copy or download AGENTS.md · generated from this app's build plan

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Alternatives to building your own

LangflowA desktop-or-server visual agent builder with tools, knowledge, and multi-agent flows.153kaug 2026open source↗Dify Community EditionThe broadest finished free agent platform here; the Docker stack is the tax.$0free↗

no votes, no pay-to-list · just what's real

Relevance AI pricing

planmonthlyannual (per mo)what you get
free$0/workspace$0/workspace200 Actions/month; 1,000 vendor credits one time (stated value $2); 1 workforce, 1 user, 1 project and 30-day history.
pro$29/workspace$19/workspace2,500 Actions/month or 30,000/year; $20 vendor credits/month or $240/year; 2 builder users.
team$349/workspace$234/workspace7,000 Actions/month or 84,000/year; $70 vendor credits/month or $840/year; 5 builder users, 45 end users and 5 projects.
enterprise——Custom Actions, vendor credits, users, projects, security and support.Quote required.

free tier200 Actions/month, 1,000 one-time vendor credits, 1 workforce, 1 user, 1 project and 30-day history

billingmonthly + annual; annual plans carry the stated yearly Action and vendor-credit pools

hidden costsExtra Actions cost $80 per 1,000; vendor credits cost $20 per 10,000. The Free plan cannot top up. Included Actions reset, while purchased Actions and vendor-credit balances can roll while the subscription remains active.

pricing sources checked 2026-08-11 · pricing source ↗

Questions about Relevance AI

Can you build your own Relevance AI with AI?

Partly. The visible AI workforce platform loop is buildable, but a credible replacement needs more than the first screen. Relevance AI earns its keep through connectors, auth, reliability, so expect a weekend or multi-day build and a narrower personal scope.

What does the Relevance AI build prompt cover?

The prompt starts with this scope: Run one research-to-brief assistant workflow that retrieves approved company pages, extracts a structured brief and stops for human review before any external action. Full-product capabilities excluded from the comparison include: hundreds of maintained connectors; OAuth app verification; durable execution at scale. Follow the implementation plan and its prerequisites before expanding the build.

How do I use the prompt, AGENTS.md and agent skills?

Start with the Relevance AI prerequisites and stack, then copy the prompt into your coding agent. Save the project rules as AGENTS.md in the project root. Linked skills are optional packages or source instructions for specific tasks; review their current contents and install only those matching the chosen stack. A skill does not supply API credentials or verify the finished app.

How long will this Relevance AI project take?

The catalogue estimate is weekend to multi-day for the limited scope. Setup, integration approvals, debugging, deployment and ongoing maintenance can add time. This is an estimate, not a delivery guarantee.

What would I give up by replacing Relevance AI?

hundreds of maintained connectors; OAuth app verification; durable execution at scale; schema drift handling and enterprise controls. Relevance AI: One automation is easy. Subscribers pay for maintained integrations, credentials, retries, observability, and someone else owning breakage.

What can I use instead of building Relevance AI?

Langflow: A desktop-or-server visual agent builder with tools, knowledge, and multi-agent flows. Dify Community Edition: The broadest finished free agent platform here; the Docker stack is the tax. Check each option's license, hosting needs and feature limits.

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