Relevance AI
Relevance AI is an innovative platform designed to help businesses create and deploy autonomous AI teams, essentially constituting an AI Workforce. The platform...
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What is Relevance AI?
Relevance AI is the home of your AI Workforce - a low/no-code platform where anyone can build and recruit teams of AI agents to complete tasks on autopilot. The platform enables domain experts to design playbooks that agents execute autonomously, scaling what used to take entire teams. It's designed for GTM and high-growth teams who want to unlock agentic ROI at enterprise scale.
Key features include: Invent (build agents by describing what you want in plain language), a no-code drag-and-drop builder for creating agents from scratch, MCP support for programmatic building with Claude Code/Codex, Evals for holding agents to quality standards, 100+ native integrations expanding to 1,000+, native triggers for CRMs/email/calendar, multi-LLM support (OpenAI, Anthropic, Cohere, A21), monitoring dashboards with real-time visibility into agent activity/performance/cost, RBAC access controls, version control with full history, audit logs, human-in-the-loop approval gates, SSO/SAML enterprise authentication, PII masking, and multi-region data residency (AWS us-east-1, eu-west-2, ap-southeast-2).
Relevance AI is for ops and revenue teams closest to the work, domain experts who own agent quality and outcomes, GTM engineers building programmatically, and enterprises requiring security/governance at scale. Notable customers include Qualified (35+ AI agents, $7M pipeline), Send Payments (40 hours weekly saved), and Zembl (30% more customer conversions).
Relevance AI pricing
Pricing model: Freemium
Relevance AI offers a credit-based pricing model with a freemium tier. Free tier: 100 credits/day for 1 user. Pro: $19/month for 1 user with 10,000 credits/month. Team: $199/month for 10 users with 100,000 credits/month. Business: $599/month for unlimited users with 300,000 credits/month. Enterprise: Custom pricing with custom vendor credits, unlimited agents/tools/users/projects/workforces, 2,000+ integrations, calling & meeting agents, enterprise triggers, agent evaluations, A/B testing & analytics, SSO/RBAC/audit logs, and dedicated account manager. Extra AI credits available on all paid tiers as top-up packs. Additional storage purchasable as separate add-on.
Relevance AI pros
- Free tier available with 100 credits/day for evaluation
- Low entry price at $19/month for Pro plan
- No-code builder requires no coding skills
- Invent builds agents from plain language descriptions
- 1,000+ native app connectors available
- Multi-LLM support - route to any provider for best cost/performance
- Full orchestration with parallel streams and deep nesting
- Built-in Evals for quality control across every task
- Native triggers for CRMs, email, calendar without external orchestration
- Real-time monitoring dashboards for activity, performance, and cost
- Enterprise security with SSO/SAML, RBAC, audit logs, PII masking
- Version control with full history and instant rollback capability
- Human-in-the-loop approval gates on any action
- Multi-region data residency for compliance requirements
- Pre-built templates and Marketplace for quick starting points
- LLM provider switching without integration costs
- Built-in batch processing across entire datasets
- Transparent pricing with credit pass-through
- Live chat support with dedicated CSM for enterprise
- 4.5 stars on G2 with 'Leading Enterprise Agent Vendor' recognition
Relevance AI cons
- Slow browser performance with extensions like Grammarly
- Enterprise plans require talking to sales - no transparent pricing
- Higher-tier plans expensive at $199-$599/month for smaller teams
- Credit-based system can become costly at scale
- Limited documentation found for advanced features
- Requires SOC 2 compliance understanding for enterprise deployment
- Browser lag issues reported by some users
- May require learning curve for non-technical users despite no-code claim
Frequently asked questions about Relevance AI
What are AI chains?
AI chains (also known as LLM chains) enable combining multiple steps of Large Language Models like GPT with other transformations like document retrieval, vector search, and API requests to build advanced functionality. These workflows can be deployed as a single endpoint that receives input, runs it through chain steps, and provides output.
How can I deploy my first chain?
Getting started is simple: create a free Relevance AI account, open the Chain Notebook starting from blank slate or using a template. Once happy with results in the Notebook, deploy as an embeddable form or API endpoint.
Which LLMs do you support?
Relevance AI supports OpenAI, Anthropic, Cohere, and A21. If you want to use a different provider, contact them via live chat and they'll add it to the list.
How does Relevance AI handle data security?
Chains are ephemeral by nature - they don't store input or output. Datasets are stored in their SOC 2 Type II compliant platform. All data is encrypted in-transit and at-rest.
Why use Relevance AI instead of the GPT API directly?
Relevance AI lets you select any LLM provider including OpenAI's GPT. Benefits include: seamless transition from prompts to chains without new code, effortless LLM-provider switching, enhanced monitoring and cost tracking, streamlined versioning control with rollback capability, simplified collaboration involving non-technical team members, and intuitive Notebook experience for experimenting with chains.
What is the Notebook?
Relevance AI's Notebook is a best-in-class product for creating and experimenting with AI chains. Like Jupyter notebooks transformed Data Scientists' ML workflows, the Notebook makes working with LLM chains exceptionally easy with convenient interface, individual block executions, exploration/experimentation phases, and peer collaboration for review and improvement.
How can I contact support?
Log into the dashboard, select the help icon from top-right, and select live chat to communicate with their team. Enterprise customers can also contact their dedicated CSM.
What regions can I deploy chains to?
Relevance AI offers regions in AWS us-east-1 (N. Virginia), eu-west-2 (London), and ap-southeast-2 (Sydney).
Can I run chains in batch across large amounts of data?
Yes, all chains can be run in batch across an entire dataset. This functionality is built-in with Relevance AI's datasets.
Why is Relevance AI running slowly in my browser?
Slow performance, lag, or crashes may be related to browser extensions, particularly Grammarly. Turn off browser extensions before using Relevance AI's tool builder. If problems continue after disabling extensions, reach out to support via live chat.