Relevance AI
Low/no-code platform for building AI agents and multi-agent workforces that autonomously run real business tasks.
By Relevance AI · 4.5/5 Value-Position score (estimate)
Positioning guardrails
Best for
- Enterprise GTM, sales and customer-success teams that want governed agents running prospect research, qualification, follow-up and pipeline roll-ups.
- Support and operations leaders automating high-volume triage, routing and back-office workflows with human-in-the-loop approvals.
- Companies that need agents working on their own data with SSO, RBAC, audit logs, data residency and PII masking.
- Teams that prefer a no-code builder plus Marketplace templates over building agent infrastructure themselves.
- Organizations ready to embed a vendor deployment team for a few weeks to get to production.
Ideal size: 100–5,000 employees people · Scale-up or enterprise with defined GTM or support playbooks and an internal owner for agents
Not for
- SMBs shopping for a cheap self-serve chatbot with published per-seat pricing; Relevance AI is quoted through sales.
- Buyers who need one narrow point tool (for example document OCR) rather than a platform they must configure and govern.
- Organizations without a process owner; the model expects you to map use cases, write evals and own outcomes.
- Regulated buyers requiring on-premises or air-gapped deployment, which no source documents.
Value metrics scorecard
Time-to-Value
2–4 weeks
~21 days to first production value
Total Cost of Ownership
On request
Enterprise plan quoted through sales; no list prices published. Consumption is metered in credits and actions, with published cost-per-task examples around $0.09.
Implementation Friction
3/5
Engineering + admin effort required
Value-Position score
out of 5 · model estimate
Full cost breakdown
Mandatory implementation fee
None
Seat tiers
Enterprise includes unlimited users, projects and workforces; a Team plan is referenced in docs but not publicly priced.
Add-on costs
- Additional actions and credits consumed beyond the plan allowance (usage is billed in credits and actions).
Company & support
Who is behind Relevance AI, and how your team gets help once it is live.
Company
- Founded
- Not recorded
- Headquarters
- Not recorded
How you get support
- PhoneNot listed
- EmailNot listed
- Live chatNot listed
- Support portal / ticketsNot listed
- Community forumAll plans
- Help centre / docsAll plans
- Dedicated account managerEnterprise only
- In person / on-siteNot listed
- Hours
- Not recorded
- Response time
- Not stated
Documentation points to the support team, a user community and troubleshooting guides; the pricing page lists a dedicated account manager on Enterprise. No support phone line, support email address or response-time SLA is published.
“Not listed” means the vendor’s public pages don’t mention that channel, not that it is unavailable. Ask about it during evaluation.
Market position
Where Relevance AI sits against its closest alternatives. Pick any two of cost, speed, friction and buyer score, and up to 9 companies to compare.
Quadrant view
Typical annual cost × Time-to-value
The lines cross at the median of the solutions shown, so about half sit on each side of each line. A dashed ring marks an outlier pinned to the edge; hover for its value.
Companies on the chart 6 / 10
- Relevance AI
- Suralink
- Shelf
- Guru
- Accelo
- Notion
Add or change companies
Up to 10 companies including Relevance AI. Listed closest first.
Stack fit signal
Compatibility with standard B2B ecosystems.
Ships an official MCP server. Connects to Claude Code, Claude Desktop, ChatGPT connectors and Cursor out of the box.
AI & MCP readiness
What Relevance AI ships in AI, and what it asks of your ecosystem.
AI features shipped
Invent acts as an in-product AI solutions engineer that helps teams scope and build agents. Agents and multi-agent workforces run autonomously with evals, approvals, escalation, tracing and cost monitoring. Chat includes an Exa-powered people search, and agents read documents such as PPTX decks.
Your data & models
- Trains on your data
- Never trains on your data
- Runs on
- OpenAI, Anthropic, Google
- AI pricing
- Billed by usage or credits
In your ecosystem
- AI connection
- Official MCP server
- Model key
- Not recorded
- AI usage audit
- Full audit trail
Compliance attestations
* IAPP AIGP certifies individuals, not products. It means named staff hold the credential — not that the platform does.
Bottom line
Relevance AI is a low/no-code platform for building AI agents and multi-agent workforces that autonomously run sales, support and operations tasks. It ships 2,000+ integrations, a Marketplace of pre-built agents, Invent (an AI solutions engineer), plus guardrails, evals, RBAC, audit logs and MCP access. Customers such as Autodesk, Canva and Qualified report pipeline and hours saved. Pricing is enterprise-only through sales, with consumption billed in credits and actions, so expect a custom quote and a security review.
Frequently asked questions
How fast can we get an agent into production?
The vendor's rollout plan maps use cases in weeks 1-2, deploys a first team of agents from week 3, and moves to production-ready pilots plus new use cases from week 4. Relevance says some use cases can be stood up in hours using Invent or Marketplace templates. Budget roughly 2-4 weeks to first production value, with an embedded deployment team getting you live before training your own team to build.
What does Relevance AI cost?
No list prices are published. The pricing page shows a single Enterprise plan ('Talk to sales') covering unlimited users, projects, workforces and agents, custom vendor credits, agent evaluations, and a dedicated account manager. Consumption is metered in credits and actions, and the homepage cites an average cost per task of about $0.09 across models. Expect a custom annual quote rather than a self-serve price.
Does Relevance AI train on our data?
The homepage security section states 'No training on your data' alongside data residency, PII masking and audit logs. The privacy notice separately says personal information may be used for internal quality control and training purposes in the context of improving the services, so regulated buyers should confirm the data-processing terms and model-provider handling in writing during procurement.
Can we integrate it with our existing stack?
Yes. Relevance documents 2,000+ integrations across categories from Sales & CRM to Security & Identity, names Slack and Salesforce in its integrations headline, supports Microsoft Teams and Google Drive/Calendar triggers, and lets agents call any API through a no-code tool builder. It also exposes an MCP server so MCP clients can connect using the user's own permissions, plus OTEL and Delta Share export.
What governance exists for autonomous agents?
Agents support human-in-the-loop approvals, escalation and version control, with SSO/SAML and role-based access control at the workspace level. Monitoring covers real-time dashboards and full agent tracing with cost visibility. Enterprise customers get Evaluations, including LLM-judge scoring, sampling at 10/50/100% of runs, per-check cost breakdowns, and A/B testing with analytics.
Which teams use Relevance AI today?
Published customers include Autodesk, Canva, Lightspeed, SafetyCulture, Qualified and Send Payments, spanning technology, financial services and energy consulting. The platform is marketed to sales, customer success, support, marketing, HR, operations and research teams, and the homepage cites outcomes such as a $7M pipeline built with 35+ agents and 40 hours saved weekly.