Agentic Index

AutoGPT vs Relevance AI (2026)

AutoGPT last verified ·Relevance AI last verified

Both let you assemble a workforce of agents and they differ on openness against polish. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.

Relevance builds and deploys a workforce of agents with a no code tool builder, on plans from Pro at $19 a month billed annually. AutoGPT is open source with a visual block based builder, an agent marketplace and a continuous agent runtime, free to self host or hosted on subscription plus credits. Relevance is the smoother commercial product, and AutoGPT is free forever if you run it yourself.

On the Agentic Index self hosted platform ranking, AutoGPT and Relevance AI both clear the bar: each documents both containment capabilities in full. 171 of the 556 platforms it grades clear it. See the self hosted platform ranking

This comparison is published by Agentic Index, an independent agentic AI vendor research platform. AutoGPT and Relevance AI are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 1,084 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded

Choose AutoGPT if

  • Free self hosting with no ceiling is the deciding factor.
  • A continuous runtime for always on agents is the requirement.
  • Open source is how you want your dependencies to work.

Choose Relevance AI if

  • A polished no code builder speeds adoption with people who will never open a repository.
  • Pro at $19 a month, billed annually, costs less than self hosting anything.
  • A workforce metaphor with clear tooling is what your non technical team will understand.
Feature
A
AutoGPT
R
Relevance AI
Action & orchestration

Integrations & Tool Calling

Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools.

Workflow Orchestration

Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps.

Triggers & Channel Coverage

How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools.

Knowledge & context

Knowledge Grounding & RAG

Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers.

Memory & State Persistence

Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer.

Control & trust

Human Oversight & Guardrails

Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls.

Security, Identity & Governance

RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy.

Observability & Auditability

Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior.

Deployment & Data Residency

Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting.

Solution readiness

Prebuilt Agents, Templates & Packs

Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value.

Platform extensibility

Model Flexibility & Routing

Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys.

APIs, SDKs & MCP Extensibility

Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems.

Testing, Debugging & Optimization

Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment.

Specialist automation

Browser & Computer Use

Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone.

Pricing snapshot

Sourced from the Index pricing dataset · open each vendor's profile for full detail.

Pricing
A
AutoGPT
R
Relevance AI

Entry price

Lowest public entry point

Free to self host the open source platform with the customer's own model API keys and infrastructure. The hosted cloud starts at Pro, $50 per month billed monthly with a 7 day free trial, with Max at $320 per month. Pro at $19 a month billed annually or $29 monthly, Team at $234 a month billed annually or $349 monthly, and Enterprise at custom pricing.

Pricing confidence

How public the numbers are

Public, partial Public, partial

Billing

Primary billing axis

The Pro or Max subscription covers Otto and Expert chat usage, with Max at 8.5 times Pro. Workflow runs draw from a prepaid credit wallet at the same rate on every plan, with a spending cap per Expert. A plan subscription with two meters. Actions count each tool run, and Vendor Credits pay model and tool costs at provider rates with no markup.

Variable cost

Workload / overage exposure

High variable cost High variable cost

Free tier / trial

Try before you buy

Free tierTrial
No free tier

Buying motion

Self-serve vs sales call

Self-serve Self-serve

Pricing verified

When this pricing was last checked

Product updates

Newest first, each linked to its source.

AutoGPT

  • · Human approval / guardrails

    AutoGPT Platform v0.8.3 narrows what AutoPilot asks about: ordinary work inside its sandbox now runs without asking, while outward commands and unrequested deletes of the user's files still need approval.

    Source
  • · Human approval / guardrails

    AutoGPT Platform v0.8.2 gives AutoPilot three modes, Ask First, Auto and Unsupervised, and workflows it starts now pause before an irreversible action.

    Source
  • · Security / enterprise

    AutoGPT Platform v0.8.0 generates secrets per installation, refuses the previously published default encryption key, and removes legacy HS256 JWT verification.

    Source

Relevance AI

  • · Agent capability

    Relevance AI rolled out a multi-feature update introducing the Invent interface for agent creation and adding Google's Gemini 3.5 Flash as a selectable language model across all workflows.

    Source
  • · Integrations

    Relevance AI added Confluence Knowledge Sync, project-level public-agent controls, and an Android app, improving enterprise knowledge connectivity, governance, and mobile workforce access.

    Source
  • · Pricing / packaging

    Relevance AI split pricing into Actions and Vendor Credits, enabled BYO API keys, removed markup on vendor costs, and sunset the Business plan.

    Source

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