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 | ||
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Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
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AutoGPTIntegrations & Tool Calling Block categories span an MCP tools block, a Claude Code block, an E2B sandbox block, image, video and music generation via Ideogram, Flux, VEO3, Fal, Replicate and MusicGen, a generic HTTP Request block with multipart upload, host-scoped authentication and safe-redirect protection, a read-only SQL Query block, Reddit blocks via PRAW, and Pinecone and Mem0 blocks. Automations import from n8n, Make.com and Zapier. A Block Development SDK lets customers build, register and ship custom blocks using a provider pattern, with auto-generated block documentation surfaced in builder search. A Run Agent block executes another agent as a sub-agent, and library operation blocks add agents from the store programmatically. Through the MCP tools block, the platform calls out to other systems. Sourceagpt.co pricing page, docs.agpt.co and agpt.co block documentationread 2026-08-31 |
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Relevance AIIntegrations & Tool Calling Agents call tools built in a no code tool builder and connect to a catalog of more than 2,000 integrations, and an MCP client lets them use tools from outside MCP servers. Sourcerelevanceai.com/pricingread 2026-09-27 |
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Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
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AutoGPTWorkflow Orchestration A Run Agent block runs another agent as a sub-agent within a workflow, taking the agent's graph ID, version and input data and returning its outputs, with input and output schemas defining the data passed between parent and child, for modular workflows, specialized agents called from a main orchestration agent, and dynamic routing by input type. The visual builder composes blocks with branching, looping and routing logic, and AI reasoning blocks include an AI Condition block that lets a model decide a branch. Agents run continuously and on schedules, with execution, scheduling and notification managers in the backend. How failed sub-agents are retried, and whether branches run in parallel, is not described. Sourceagpt.co and docs.agpt.co block documentation, agpt.co home and pricing pagesread 2026-08-31 |
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Relevance AIWorkflow Orchestration Workforces connect several agents and tools on a canvas with conditions on the edges between them, agents can hand work to subagents, and the tool builder supports looping and branching steps. Sourcerelevanceai.com/docs/build/workforces/workforce-features/approvals-and-escalations.mdread 2026-09-27 |
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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. |
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AutoGPTTriggers & Channel Coverage Webhook blocks give an inbound event route, scheduling blocks give recurrence with a dedicated scheduling manager in the backend, and a public REST API exposes agent execution programmatically. Agents run continuously and trigger from external sources, with execution, scheduling and notification managers and websockets for real-time communication in the backend. A sub-agent block allows one agent to start another. No chat, email, Slack or messaging channel through which a person addresses an agent is offered beyond the platform's own interface. Sourceagpt.co misc block documentation, agpt.co home and pricing pages, docs.agpt.co platform documentationread 2026-08-31 |
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Relevance AITriggers & Channel Coverage Scheduled triggers let an agent act on its own on a recurring schedule or send messages at set future times, and agents also start from integration events, custom webhooks, an API trigger and tools used as triggers. Sourcerelevanceai.com/docs/build/agents/build-your-agent/agent-triggers/scheduled-triggers.mdread 2026-09-27 |
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| Knowledge & context | ||
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Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
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AutoGPTKnowledge Grounding & RAG A Vector and Memory block category covers Pinecone vector storage and Mem0 long-term memory, connecting agents to a vector index the customer keeps and queries. Data transformation blocks include a spreadsheet reader, XML parser, text encoding and replacement and list and dictionary manipulation, an HTTP Request block supports multipart upload for document retrieval, and a read-only SQL Query block reaches the customer's own platform data. Mem0 blocks separately support knowledge building by accumulating facts over time. AI reasoning blocks include a Fact Checker. The customer supplies the Pinecone index, since AutoGPT bundles no knowledge base of its own, and no chunking strategy, embedding model, retrieval configuration or citation behavior is described. Sourceagpt.co pricing page, docs.agpt.co platform blocks documentationread 2026-08-31 |
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Relevance AIKnowledge Grounding & RAG Knowledge sets are built from uploads (CSV, PDF, Excel, JSON, audio), website extraction, manual entry, and syncs from Google Drive, SharePoint and Notion, and an agent either takes the whole set in its prompt or searches it by retrieval with relevance thresholds. Sourcerelevanceai.com/docs/build/knowledge/create-knowledge.mdread 2026-09-27 |
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Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
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AutoGPTMemory & State Persistence Mem0 memory blocks let an agent add memories that persist across workflow executions, optionally scoped to the run or the agent and tagged with metadata, retrieve the latest memory or all memories with the same scoping, and search memory, with context review, memory export and listing memories to find outdated or incorrect information among the uses. Memory controls let the user review and forget stored facts and preferences when memory is enabled, and a persistent key-value storage block is shared across tasks and workflows. How long memories are kept is not stated. Sourceagpt.co basic blocks documentation and pricing pageread 2026-09-29 |
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Relevance AIMemory & State Persistence Long term memory lets an agent remember information across different conversations through save to memory and delete from memory tools, alongside short term memory that holds extracted fields for one conversation. Sourcerelevanceai.com/docs/build/agents/build-your-agent/memory.mdread 2026-09-27 |
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| Control & trust | ||
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Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
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AutoGPTHuman Oversight & Guardrails A Human In The Loop block pauses workflow execution and presents data to a human reviewer for approval, waiting until the reviewer approves or rejects it and routing the data to separate approved and rejected outputs, with an option letting the reviewer edit the data before deciding and an optional review message explaining the decision. Uses include reviewing AI-generated content before publishing and requiring manager approval for purchases, access requests or configuration changes. Approval gates can be placed anywhere in a workflow, including nested workflows, with execution pausing for review and then resuming. Guardrails beside the approval step include per-task LLM budget caps, a spending cap per Expert, host-scoped HTTP credentials and safe-redirect protection. Sourceagpt.co basic blocks documentation and pricing pageread 2026-09-29 |
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Relevance AIHuman Oversight & Guardrails Approval settings are configured per edge, so a sensitive tool can require approval while routine ones run automatically; in approval required mode the agent drafts its action and waits, and a reviewer approves, rejects or adds guidance from the task view. A let agent decide mode and escalations also exist. Sourcerelevanceai.com/docs/build/workforces/workforce-features/approvals-and-escalations.mdread 2026-09-27 |
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Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
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AutoGPTSecurity, Identity & Governance Access controls include OAuth 2.0 based single sign on, Google sign-in, API key generation, rotation and revocation, a credentials manager with scope filtering, host-scoped HTTP credentials, OAuth callback hardening and token validation, DNS-rebinding and safe-redirect protection, ClamAV scanning of uploaded files, and admin impersonation with audit trails. Admin controls and roles and security and compliance options are listed for a Team plan marked coming soon. No security certification, attestation or trust page is published, and no SAML, SCIM or role based access control is available on the current plans. Sourceagpt.co pricing page and docs indexread 2026-09-29 |
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Relevance AISecurity, Identity & Governance Relevance AI offers role based access control, SSO and SAML, directory sync, audit logs, PII masking and encryption at rest, and states SOC 2 Type II compliance. SSO, RBAC and audit logs sit on the Enterprise plan. A trust center at trust.relevanceai.com carries the report list. Sourcerelevanceai.com/enterpriseread 2026-09-27 |
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Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
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AutoGPTObservability & Auditability Cost is shown in dollars for every task, node and block, and runs stream live over WebSocket with step counts and activity summaries. Task history is searchable, and any entry opens in the builder with all execution steps preserved. Per-model token consumption, cache hits and cost are tracked on every task, admin impersonation carries audit trails, and a read-only SQL Query block gives access to the customer's own platform data including custom analytics views. The execution diagnostics and analytics dashboards are admin tools for self hosters and are not exposed to cloud customers. No retention period for run history, or reasoning trace for AI blocks beyond inputs and outputs, is described. Sourceagpt.co pricing page and block documentationread 2026-09-29 |
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Relevance AIObservability & Auditability Execution traces cover agent invocations, individual LLM calls, workforce runs and condition evaluations, and audit logs cover creation, publishing, deletion and permission changes; on the Enterprise plan both stream to the customer's S3 for OTEL backends. A tasks view shows every agent and workforce run with errors and pending approvals, and views of run cost and outcomes sit alongside it. Sourcerelevanceai.com/docs/enterprise/streaming-events.mdread 2026-09-27 |
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Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
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AutoGPTDeployment & Data Residency The platform is open source with a public repository and self-hosts free via Docker Compose, with the customer supplying their own model API keys so data and inference remain on their own infrastructure, and Llama among the pre-integrated models allows local model execution. The hosted cloud provides Pro and Max subscriptions, with a Team plan marked coming soon, and a pay-as-you-go credit wallet. Platform code is licensed under Polyform Shield, which permits use, modification and self-hosting but bars building a competing product, while the wider repository is MIT. No region selection or data residency commitment for the hosted cloud is documented. Sourcegithub.com/significant-gravitas/autogpt, agpt.co pricing page, docs.agpt.co self-hosting documentationread 2026-08-31 |
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Relevance AIDeployment & Data Residency An organization picks its region at signup from three named regions, US (N. Virginia), EU (London) and AU (Sydney), and the region cannot be changed afterward without support. The service is hosted SaaS, and Relevance AI does not describe a self hosted or VPC option. Sourcerelevanceai.com/docs/admin/project-management/ids.mdread 2026-09-27 |
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| Solution readiness | ||
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Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
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AutoGPTPrebuilt Agents, Templates & Packs AutoGPT runs a public marketplace of community-built agents carrying ratings and real run counts, with one-click adds to a personal library. Library operation blocks add an agent from the store to a personal library using its store listing version ID, returning the library entry and agent graph IDs for execution, and retrieve all library agents with search and pagination, for uses such as agent provisioning, onboarding flows that seed starter agents, and adding agents on demand when a user asks for a capability. Store listing version IDs pin the adopted version. Sourceagpt.co library and store operations block documentation, agpt.co home and pricing pagesread 2026-08-31 |
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Relevance AIPrebuilt Agents, Templates & Packs A marketplace carries agents and tools from Relevance staff and verified builders, free or paid, that can be cloned into a project and customized, alongside agent and tool templates and curated multi agent systems such as a BDR agent sold through sales. Sourcerelevanceai.com/docs/get-started/marketplace/introduction.mdread 2026-09-27 |
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| Platform extensibility | ||
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Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
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AutoGPTModel Flexibility & Routing OpenAI, Anthropic, Groq and Llama models come pre-integrated, with the model chosen per block, and third-party integration guides show additional providers connected through AI blocks. Self-hosting is free with the customer supplying their own model API keys, while the hosted cloud uses a pay-as-you-go credit wallet for agent runs. AI reasoning blocks including AI Condition, Structured Response, AI Conversation, AI List Generator and Fact Checker each carry model configuration. No automatic routing between models at run time is described. Sourceagpt.co pricing and home pages, docs.agpt.co platform documentationread 2026-08-31 |
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Relevance AIModel Flexibility & Routing Each agent picks its model from several providers, including Anthropic Claude, OpenAI and Gemini, and can set a backup model, recommended from a different provider, that retries a failed task once. LLM integrations cover OpenAI, Gemini, Anthropic, Azure and OpenRouter. Sourcerelevanceai.com/docs/build/agents/build-your-agent/agent-settings/language-model.mdread 2026-09-27 |
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APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
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AutoGPTAPIs, SDKs & MCP Extensibility A public REST API with an OpenAPI schema and generated SDK clients supports programmatic agent creation and execution, and a Block Development SDK lets customers build, register and ship custom blocks using a provider pattern that configures credentials and per run costs, with auto generated documentation surfacing custom blocks in builder search. The platform is open source with a public repository and free self-hosting via Docker Compose; platform code is licensed under Polyform Shield with the wider repository MIT. The MCP tools block works in the other direction, with the platform calling out, and no first party MCP server exposes AutoGPT agents to external assistants. Sourcegithub.com/significant-gravitas/autogpt, docs.agpt.co and dev-docs.agpt.co block SDK guide, agpt.co pricing pageread 2026-08-31 |
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Relevance AIAPIs, SDKs & MCP Extensibility A TypeScript SDK, @relevanceai/sdk, runs agents, tasks, messages and workforces with streaming, an API trigger covers other languages, and an MCP server at mcp.relevanceai.com gives MCP clients OAuth access to a project's agents, tools and knowledge. Sourcerelevanceai.com/docs/sdk/introduction.mdread 2026-09-27 |
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Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
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AutoGPTTesting, Debugging & Optimization The plan comparison lists Correctness and Accuracy Scoring, quality scores for each execution with alerts on regressions, and a dry-run self-repair loop in which newly generated workflows are simulated and errors caught and fixed automatically. Run-from-builder execution, task presets and version-pinned schedules support testing a specific workflow version. Both appear only as single lines in that table, and the scoring method, test sets and recorded expected outputs are not described. The execution analytics and diagnostics dashboards are admin tools for self hosters and are not exposed to cloud customers. Sourceagpt.co pricing pageread 2026-09-29 |
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Relevance AITesting, Debugging & Optimization Test sets hold tests that simulate users and are scored by reusable checks, so versions can be compared on the same tests; publishing can require chosen test sets to pass at a minimum rate and block on failure, and monitor dashboards score live tasks against the same criteria with sampling and trend charts. Agent evaluations sit on the Enterprise plan. Sourcerelevanceai.com/docs/build/agents/evals/introduction.mdread 2026-09-27 |
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| Specialist automation | ||
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Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
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AutoGPTBrowser & Computer Use Stagehand Blocks bring AI powered browser automation through Stagehand and Browserbase: Stagehand Act performs click, fill, type, press, scroll and select actions described in natural language, alongside Extract and Observe, and each block requires the customer's Browserbase project ID. Browser automation also runs through a Chromium-backed agent browser, and self hosters bring their own keys and infrastructure for browser automation and other features that rely on third-party services. The browser engine is a third party service the customer connects, and the E2B sandbox block runs code. Sourceagpt.co Stagehand blocks documentation and pricing pageread 2026-09-29 |
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Relevance AIBrowser & Computer Use Browser steps (click, type, scroll by natural language or selector) run through Airtop, a separately sold browser engine that needs the customer's own Airtop account and API key. Relevance AI does not describe a browser or computer use agent of its own. Sourcerelevanceai.com/docs/build/tools/tool-steps/airtop-browser-automation/page-interaction.mdread 2026-09-27 |
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Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | A AutoGPT |
R Relevance AI |
|---|---|---|
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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. |
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Pricing confidence How public the numbers are |
Public, partial | Public, partial |
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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. |
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Variable cost Workload / overage exposure |
High variable cost | High variable cost |
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Free tier / trial Try before you buy |
Free tierTrial
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No free tier
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Buying motion Self-serve vs sales call |
Self-serve | Self-serve |
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Pricing verified When this pricing was last checked |
Product updates
Newest first, each linked to its source.
AutoGPT
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· 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.
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· 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
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· 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.
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· 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.
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· 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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