Relevance AI
Bot platforms software
AI chatbots software
Vector database software
Robotic process automation (RPA) software
Agentic AI software
AI agent builders software
AI agents
AI customer support agents software
AI SDRs software
Conversational intelligence software
Generative AI software
Database software
Process automation software
AI call center tools
AI reply tools
AI answer tools
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What is Relevance AI
Relevance AI is a platform for building and running AI agents that can execute multi-step workflows across business tools and data sources. It targets operations, sales, support, and product teams that want to automate repetitive knowledge work using LLM-driven agents and integrations. The product combines an agent builder, workflow orchestration, and data/knowledge components to support retrieval-augmented generation (RAG) and tool use. It is typically used to deploy internal agents (e.g., research, ops, SDR assistance) and customer-facing agents where controlled actions and integrations are required.
Agent workflow orchestration
The platform focuses on building agents that can plan and execute multi-step tasks rather than only handling single-turn chat. It supports chaining actions, calling tools, and structuring workflows that resemble business processes. This makes it suitable for operational automations where an agent must take actions in external systems, not just respond to messages.
Integrations for tool execution
Relevance AI is designed to connect agents to third-party applications and internal services so they can perform actions such as creating records, updating systems, or triggering downstream steps. This reduces the need to build custom glue code for common business workflows. Compared with chat-first bot tools, the emphasis is more on task execution and automation across systems.
RAG and knowledge grounding
The product supports grounding agent responses and decisions in company data via retrieval patterns commonly used for RAG. This helps teams build agents that reference internal documents and structured data rather than relying only on a base model. It is useful for use cases like support deflection, internal Q&A, and research agents where traceability to source content matters.
Complexity for simple chatbots
Teams that only need a basic website chatbot or simple lead-capture flow may find the agent-and-workflow approach heavier than necessary. Building reliable multi-step agents typically requires more design work, testing, and monitoring than rule-based conversational flows. For lightweight conversational deployments, implementation effort can be higher than chat-centric tools.
Governance and risk controls vary
Agentic automation introduces risks such as unintended actions in connected systems, data leakage, and inconsistent outputs. Organizations often need strong controls around permissions, auditability, and environment separation to use agents safely in production. Depending on the deployment model and configuration, some enterprises may need additional governance tooling and processes beyond what the platform provides out of the box.
Vector database fit is situational
Although the product supports knowledge retrieval patterns, organizations with established data platforms may prefer to standardize on a dedicated vector database or existing data infrastructure. Data residency, performance tuning, and lifecycle management requirements can push teams toward specialized database products. As a result, Relevance AI’s data layer may not be the best fit for every enterprise architecture.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Free | $0 per month | 200 Actions / month; bonus vendor credits shown on signup; Unlimited Agents & Tools; 1 Workforce; 1 User & 1 Project; (annual view shows 30‑day task history); no credit card required. |
| Pro | $19 per month (annual billing) or $29 per month (monthly billing) | Annual: 30,000 Actions / year + $240 vendor credits / year. Monthly: 2,500 Actions / month + $20 vendor credits / month. 2 Build Users; Unlimited Workforces; Schedule tasks; Bring Your Own LLM; 90‑day task history; Unused credits roll over. |
| Team | $234 per month (annual billing) or $349 per month (monthly billing) | Annual: 84,000 Actions / year + $840 vendor credits / year. Monthly: 7,000 Actions / month + $70 vendor credits / month. 5 Build Users; 45 End Users; 5 Shared Projects; Calling & Meeting Agents; A/B testing; Analytics; Higher concurrency; Priority support. |
| Enterprise | Custom pricing | Custom Actions & Vendor Credits; Unlimited Users & Projects; Enterprise controls (RBAC/SSO/Multi‑org), Dedicated account manager & implementation; contact sales. |
Additional (top‑ups / add‑ons available on official site): Extra Actions — $40 per 1,000 actions; Extra Vendor Credits — $20 per 10,000 credits; Extra Knowledge Storage — $100 per GB.
Seller details
Relevance AI Pty Ltd
Sydney, Australia
2019
Private
https://relevanceai.com/
https://x.com/relevanceai
https://www.linkedin.com/company/relevance-ai/
