Relevance AI
No-code AI agent and workflow builder - drag-and-drop interface to build custom AI tools, agents, and multi-step automations without writing code.
Relevance AI is a no-code platform for building AI agents, custom tools, and automated workflows that connect LLMs to external data and APIs. Its visual builder lets teams create AI assistants that can search the web, query databases, read documents, call APIs, and execute multi-step reasoning chains - all without backend code. Each tool or agent is built from configurable steps (LLM calls, conditional logic, data transforms, API calls) and can be triggered manually, via API, or on a schedule. Relevance AI is used by sales teams automating prospect research, marketing teams generating personalized outreach at scale, and operations teams building internal AI assistants for data retrieval and reporting. The platform supports connections to 100+ integrations and all major LLMs.
Key Features
- Visual agent builder - drag-and-drop steps for LLM calls, API requests, data transforms, and conditionals
- Tool library - 50+ pre-built tools (web search, scraping, enrichment, CRM write-back) ready to chain
- Multi-agent orchestration - build teams of specialized agents that delegate tasks to each other
- Data store integration - connect the agent to vector stores, SQL databases, and uploaded documents
- LLM selection - switch between OpenAI, Anthropic, Google, Mistral, and open-source models per step
- API and webhook triggers - run agents from external systems or on a scheduled cron
- 100+ integrations including Salesforce, HubSpot, Slack, Notion, and Google Workspace
Use Cases
- Sales teams automating prospect research - agent looks up company, finds decision-maker, drafts personalized outreach
- Marketing teams building content generation pipelines that pull briefs from Notion and publish to CMS
- Operations teams creating internal AI assistants that answer queries grounded in company databases
- Developers prototyping multi-agent AI workflows before investing in custom infrastructure
Pros
- Visual builder lowers the barrier to multi-step agent construction - sales and ops teams build without engineers
- LLM flexibility per step means the right model (fast cheap, or powerful expensive) is used for each task
- Pre-built tool library eliminates the need to write API integrations for the most common data sources
Cons
- Free plan 100 credits/day depletes quickly on complex multi-step agents during testing
- Advanced orchestration patterns (feedback loops, dynamic routing) require understanding agent architecture
- Run latency for complex multi-step agents can be slow - not suitable for real-time user-facing interactions
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