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Relevance AI vs Lindy
A plain-English comparison to help you choose between them.
Both build AI agents without code; the framing differs. Lindy sells delegation: agents as employees briefed in plain language, strongest on the personal-operations loop of inbox, meetings, CRM and follow-ups, from prebuilt templates. Relevance sells a workforce platform: multi-agent teams assembled from tools and triggers, with bring-your-own-key cost control and usage transparency for scaling deliberately. Pick Lindy to delegate your own working loop fastest; pick Relevance to build and run a coordinated agent fleet with visible economics.
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Side by side
- Summary
Relevance AI is a no-code platform for building an AI workforce: autonomous agents assembled from tools, triggers and instructions, deployed against real work such as outreach, research and operations tasks. Multi-agent teams coordinate on bigger jobs.
Its cost posture is unusually transparent: usage is metered in vendor credits passed through at wholesale with no markup, which keeps the economics visible while agents scale.
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As with every agent platform, always-on autonomy is earned: usage climbs with ambition, and supervision precedes trust.
- Best for
- Building autonomous agents without code
- Multi-agent teams coordinating on real work
- Wholesale vendor-credit cost control
- Usage transparency while agents scale
- Sales, research and ops agents in production
- Cost
- Freemium (Free tier + paid plans)
- Ease
- Openness
- Hosted service
- Data
- Agents act across connected business tools; treat credential grants as the security boundary they are.
- Summary
Lindy is a platform for building AI agents that do real work across your existing tools. Each agent, a Lindy, is set up in plain language rather than code: describe the job, connect the apps it needs, such as email, calendar, a CRM or Slack, and set the rules it must follow.
Agents run on triggers rather than waiting to be asked. Typical deployments triage and draft email, schedule and reschedule meetings, prepare briefs before calls, take notes and send follow-ups, keep HubSpot or Salesforce records current and chase leads. A library of prebuilt templates covers the common jobs, so a first agent is usually assembled rather than designed.
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Lindy has moved from a free-plan model to subscription tiers with a short trial, and now presents itself as an AI assistant for the whole work loop rather than a single-purpose bot. It suits people who want delegation, not another dashboard.
- Best for
- Delegating whole jobs such as inbox triage or meeting scheduling to an agent
- Building agents in plain language without code or flowcharts
- Keeping CRM records current from email and meeting activity
- Meeting preparation, notes and follow-ups handled end to end
- Starting from prebuilt agent templates rather than a blank canvas
- Cost
- Paid only
- Ease
- Openness
- Hosted service
- Data
- Agents hold live access to email, calendar and connected tools; grant scopes per agent, per job.
Pricing
- Relevance AI
Free·$19·$234·Custom
Prices as of August 2026.
- Free
- Free
- Pro
- $19per monthbilled annually; $29 per month if billed monthly
- Team
- $234per monthbilled annually; $349 per month if billed monthly
- Enterprise
- Price on applicationno list price published
- Lindy
$49.99·$99.99·$199.99·Custom
Prices as of August 2026.
- Plus
- $49.99per month
- Pro
- $99.99per month
- Max
- $199.99per month
- Enterprise
- Price on applicationno list price published
By area
Where each one pulls ahead, area by area.
| Area | Relevance AI | Lindy |
|---|---|---|
| By job | ||
| AI agents & automation | Relevance AI gives agent coverage for a whole function, sized in roles rather than workflows | Lindy delegates inbox triage and first-draft replies to an always-on agent, which is one recognisable job rather than a function |
| By task | ||
| Automation & agents | Relevance AI builds an AI workforce, assembling multi-agent teams that cover whole functions such as research, outreach and operations, with wholesale vendor-credit metering keeping costs visible as agents scale | Lindy is sized to one job rather than a function: describe it in plain language, connect the tools it needs, and a single agent works to its own judgement inside your rules |
Common questions
Which gets a first agent working sooner?
Lindy: its templates cover the common jobs and the describe-and-connect setup is genuinely quick. Relevance rewards a little more assembly with more control over what the agents are made of.
What does bring-your-own-key mean practically?
Relevance lets you plug in your own model keys, so AI costs run at provider rates under your visibility rather than bundled into platform pricing. For heavy agent fleets that transparency compounds; for light use it matters little.
Which handles multi-agent coordination better?
Relevance, by design: agent teams working together on bigger jobs is a core primitive. Lindy's strength is depth on individual delegated roles rather than orchestrated fleets.
Related comparisons
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Tool facts last checked August 2026