Why it matters
- No-code agent building makes AI automation accessible to non-technical teams (sales ops, marketing ops, HR).
- Multi-agent orchestration enables complex workflows where multiple AI agents collaborate on tasks.
- 50K+ teams using it validates the platform across diverse business use cases.
- Pre-built tool integrations (Google Search, LinkedIn, CRM APIs, email) reduce setup time for common agent tasks.
Key capabilities
- No-code agent builder: Define agent goals, tools, and behaviors without writing code.
- Tool builder: Create custom tools that agents can use — API calls, web search, data lookups.
- Multi-agent orchestration: Build workflows where multiple specialized agents collaborate.
- Agent memory: Agents remember context across sessions — past interactions, learned preferences.
- Pre-built integrations: Google Search, LinkedIn, HubSpot, Salesforce, Gmail, Slack, and more.
- LLM-agnostic: Works with GPT-4o, Claude, Gemini, and local models.
- Team collaboration: Share agents and tools across your organization.
- Analytics: Track agent performance, cost per task, and success rates.
Technical notes
- Interface: No-code visual builder; optional code customization
- LLMs: GPT-4o, Claude 3.5, Gemini, and custom models
- Integrations: 100+ via native connectors; Zapier for others
- Security: SOC 2 Type 2 (Enterprise); SSO on Business+
- Pricing: Free (limited runs); Team ~$19/mo; Business ~$199/mo; Enterprise custom
- Company: Relevance AI; Sydney, Australia; founded 2020; raised ~$10M
Ideal for
- Business operations teams (sales, marketing, HR, support) who want AI automation without engineering resources.
- Revenue operations teams building AI-powered sales prospecting and outreach at scale.
- Organizations that have identified specific repetitive knowledge-work tasks to automate.
Not ideal for
- Technical teams who prefer code-first agent frameworks (LangChain, CrewAI, AutoGen).
- Complex data pipeline automation where n8n or Zapier are more appropriate.
- Applications requiring real-time customer-facing AI interactions (latency expectations are different).