Relevance AI
No-code builder for AI agents and multi-agent 'teams'
Overview
A low-code platform for assembling AI agents and orchestrated agent teams that handle research, sales prospecting, support triage and data work. Aimed at ops and revenue teams that want custom agents without building from scratch.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 13 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- 100 credits/day
- Core agent builder
- Community support
- 2,500 Actions/mo
- $20 Vendor Credits included
- Scheduling
- 7,000 Actions/mo
- $70 Vendor Credits included
- Team collaboration
- Custom Actions & credits
- SSO / advanced controls
- Dedicated support
What you can produce with Relevance AI
- No-code AI agent builder
- Multi-agent 'teams' orchestration
- Prebuilt agent templates (e.g. BDR / sales prospecting)
- Custom tools and developer APIs
- Large third-party integration library
- LLM-agnostic with pass-through (no-markup) Vendor Credits
- Scheduling and triggered runs
ASEAN Perspective
Relevance AI in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Relevance AI's abstraction is the draw: build a single agent, give it tools and workflows, then chain several into a "team" that runs a whole process. It started life as a vector/data platform and pivoted into agents, and the developer story is real, custom tools, APIs and a big integration set. Since September 2025 it prices on two meters, Actions (task runs) and Vendor Credits (the raw LLM compute), and it doesn't mark up the model cost, which keeps bills honest but adds a layer to reason about. The honest caveats: agents still need careful prompt and tool design plus monitoring, credit spend gets unpredictable as usage climbs, and the sheer breadth overwhelms first-timers. Reviewers on G2 land around 4.3, with the learning curve and cost creep as the standard complaints. Best for ops and go-to-market teams that want production agents faster than coding them; global-English only, with Australian roots but no SEA-specific localization.
What people say
Relevance AI is a Sydney-founded startup, launched in 2020 by Daniel Vassilev, Jacky Koh and Daniel Palmer. It began as a developer-first vector/data platform and repositioned around building AI "teams" of agents. It's venture-backed, including a $24M round led by Bessemer Venture Partners, with Insight Partners and King River Capital among the holders.
The product lets non-engineers assemble agents from tools, prompts and workflows, then orchestrate several agents together to run tasks like research, sales prospecting, support triage and data processing. There's enough depth underneath (custom tools, APIs, a large integration library) that developers can extend it rather than hit a ceiling.
Pricing changed in September 2025 to a two-meter model that reviewers spend a lot of time explaining. You pay for Actions (task runs) and separately for Vendor Credits, the underlying LLM compute. Relevance doesn't mark up Vendor Credits, the model provider's cost passes straight through, and unused Vendor Credits roll over indefinitely. The published ladder runs from a free plan up through Pro and a Team plan at $234/month on annual billing (7,000 Actions plus $70 in Vendor Credits), with Enterprise on custom pricing. Overages run about $80 per 1,000 extra Actions.
On reception, Relevance AI holds roughly 4.3 out of 5 on G2 across about 21 reviews and is listed on Gartner Peer Insights. The two complaints that show up again and again: a real learning curve getting agents configured well, and unpredictable credit consumption once you scale past experiments into production runs. Neither is unusual for agent platforms, but both are worth budgeting for, in time and money.
For context, the field it competes in, Lindy, Gumloop and similar builders, is crowded and moving fast, so the two-meter transparency and the multi-agent orchestration are the main reasons buyers pick it over lighter automation tools. There's no SEA-specific localization; access is standard global English, and support is remote.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including Relevance AI's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Relevance AI unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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