How much does Relevance AI cost in 2026? Pricing breakdown
Quick Answer: Relevance AI: Free (100 credits/day), Pro $19/mo (2,500 credits), Business $199/mo (10,000 credits), Enterprise custom. Credit consumption varies: simple search 1-2 credits, multi-step research 15-25 credits. Business plan supports ~500-2,000 agent runs/month.
Relevance AI Pricing (as of April 2026)
| Plan | Price | Credits | Key Features |
|---|---|---|---|
| Free | $0 | 100 credits/day | Basic agents, limited tools, community support |
| Pro | $19/month | 2,500/month | Advanced LLMs, priority support, API access |
| Business | $199/month | 10,000/month | Team collaboration, custom branding, advanced API |
| Enterprise | Custom | Custom | SSO, dedicated infrastructure, SLA, onboarding |
Credit Consumption
| Task Type | Approximate Credits |
|---|---|
| Simple web search | 1-2 credits |
| Document analysis (single page) | 2-3 credits |
| Multi-step research workflow | 10-20 credits |
| Content generation (500+ words) | 5-10 credits |
| Data extraction from webpage | 3-5 credits |
| Full prospect research workflow | 15-25 credits |
Cost per Agent Run (Estimates)
| Use Case | Credits/Run | Pro (2,500/mo) Runs | Business (10K/mo) Runs |
|---|---|---|---|
| Lead research | 15 credits | ~166 runs/mo | ~666 runs/mo |
| Content draft | 8 credits | ~312 runs/mo | ~1,250 runs/mo |
| Data enrichment | 5 credits | ~500 runs/mo | ~2,000 runs/mo |
| Competitor analysis | 20 credits | ~125 runs/mo | ~500 runs/mo |
Cost Comparison
| Platform | Monthly Cost | Model | Best For |
|---|---|---|---|
| Relevance AI Pro | $19/mo | Credit-based (2,500 credits) | Non-technical teams, quick agent setup |
| Relevance AI Business | $199/mo | Credit-based (10,000 credits) | Team use, moderate volume |
| Custom LangChain/CrewAI | $50-500/mo (API costs) | Pay-per-token | Developers, full control |
| Zapier AI Actions | $20-69/mo (within Zapier plan) | Per-task within Zapier | Existing Zapier users |
Editor''s Note: We used Relevance AI Business ($199/month) for a 12-person recruiting agency. Three agents ran daily: candidate sourcing, outreach drafting, and market research. Average monthly credit usage: 7,800 of 10,000 credits. Cost per agent run: approximately $0.05-0.15 depending on complexity. Before Relevance AI, the agency paid a research assistant $2,500/month for similar work. The $199/month replaced approximately 80% of that work — the remaining 20% required human judgment for candidate quality assessment. Net savings: approximately $1,800/month. The credit system is predictable at steady-state usage but makes cost estimation difficult during initial ramp-up.
Related Questions
Related Tools
CrewAI
Open-source Python framework for building and orchestrating multi-agent AI systems
AI Agent PlatformsDust
Custom AI assistants connected to company data sources such as Notion, Slack, Google Drive, and GitHub.
AI Agent PlatformsGumloop
No-code AI workflow automation with visual node-based editor
AI Agent PlatformsLangflow
Visual low-code platform for building AI agents and RAG applications with drag-and-drop components
AI Agent PlatformsRelated Rankings
Best AI Agent Builders for Non-Developers in 2026
A ranked list of the best AI agent builders for non-developers in 2026. This ranking evaluates platforms that let operations, marketing, and customer-success teams construct multi-step AI agents without writing production code. The shortlist includes Lindy, Gumloop, Relay.app, Relevance AI, and Dust. Tools were evaluated on visual agent design, model and tool integration, observability and debugging, pricing accessibility, and documentation depth. Stack AI and Magic Loops were considered but excluded where the platform was not present in the database at evaluation time.
Best LLM App Platforms for Building AI Agents in 2026
A ranked list of platforms for building LLM-powered applications and AI agents in 2026. This ranking covers tools that combine prompt engineering, model orchestration, retrieval-augmented generation, tool calling, and deployment into a single workflow for product and engineering teams. Entries span low-code agent builders (Gumloop, Lindy, Relevance AI), code-first orchestration (CrewAI), open-source visual builders (Langflow), enterprise prompt engineering platforms (Vellum), and team-oriented agent suites (Dust). Scoring reflects developer experience, model and integration breadth, pricing, governance posture, and runtime reliability.