Lindy AI

Lindy is an AI teammate for handling email, meetings, research, scheduled routines and work across connected applications. It combines persistent workspace context, more than 40 built-in skills, computer use, model choice, MCP support and approval controls. The current product is broader than a simple agent builder: Lindy is positioned as a daily assistant that can operate through Slack, iMessage, inboxes, meetings and business tools.

What is Lindy?

Lindy can answer questions, summarise information, draft communications, update connected systems and run recurring tasks. It can join or process meetings, organise shared notes, prepare follow-up and work across thousands of integrations. Users can choose among major AI models and create custom skills when built-in capabilities are insufficient.

The strongest value comes from continuity. Persistent workspace context, connected inboxes and a meeting library allow the assistant to work with more background than a one-off chat. That also makes permission design and data governance essential.

Current Lindy pricing

Lindy currently offers a seven-day free trial and the following per-user monthly plans:

• Plus: $29.99 per user per month with 3,000 credits per user.
• Pro: $99.99 per user per month with 15,000 credits—five times the Plus allowance.
• Max: $199.99 per user per month with 35,000 credits, intended for heavy workloads.
• Enterprise: custom pricing with Max capabilities plus HIPAA support and a signed BAA, shared usage with bonus credits, audit logs, onboarding, enablement and dedicated support.

Each seat contributes its credits to a shared team pool. Administrators can allocate credits by seat. When the pool is depleted, Lindy pauses instead of automatically creating an overage charge.

How Lindy credits work

Credits measure work performed rather than a fixed number of messages. Lindy’s current examples show wide ranges:

• Everyday asks: roughly 2–250 credits for answers, summaries, lookups, tool updates, meeting close-out and reply drafting.
• Deep work: roughly 250–1,000 credits for competitor research, support triage, proposals and basic HTML artefacts.
• Big builds: roughly 1,000–2,500 credits for dashboards, multimedia decks, internal tools and heavy scheduled workflows.

Actual usage depends on the selected model, context, connected actions and retries. A Plus seat can support many small tasks or only a few large builds. Evaluate cost per approved outcome, not credits per prompt.

Core capabilities

Inbox management

Lindy can connect up to five inboxes, summarise messages and draft replies in the user’s voice. Start in draft-only mode. Require human approval for external communication, financial commitments, legal matters and sensitive personnel issues.

Meetings and follow-up

The product supports meeting recording, notes, a shared library, preparation, scheduling and follow-up. Recording requires participant notice and consent where applicable. Verify transcription accuracy, speaker attribution and retention before relying on notes for decisions.

Slack and iMessage access

Lindy can operate as a Slack-native teammate in threads and mentions and can be reached through iMessage. Convenient channels make the assistant easy to use but may expose business context outside its primary interface. Administrators should define which channels and workspaces are permitted.

Scheduled routines

Daily briefs, nudges, catch-ups and scheduled work can run without a fresh prompt. This supports proactive assistance but requires monitoring. Assign an owner, cap credits and make every schedule easy to pause.

Skills, integrations and MCP

More than 40 skills are included and users can build their own. Thousands of integrations and MCP support extend Lindy to additional tools. Review every permission, especially write access. Custom skills and MCP servers should be tested and versioned like code.

Computer use

Computer use lets Lindy interact with applications that lack a direct integration. It expands coverage but is less deterministic than an API. Restrict it to approved systems, isolate high-risk actions and require confirmation before deletion, purchase, account changes or publication.

Model selection

Major models are available, allowing users to trade speed, reasoning and cost by task. Model changes can alter behaviour, data flows and credit consumption. Keep an approved list and regression-test important routines before switching.

Approvals and human oversight

Lindy advertises approvals as a built-in feature. Use them as a core control rather than an inconvenience. Separate information retrieval and drafting from consequential action. A human should approve outbound messages, CRM changes, payments, calendar commitments and access changes.

Approval screens must show enough context to make a real decision. Review the source data, proposed action, destination and side effects rather than approving a vague summary.

Security and privacy

Lindy states that data is encrypted in transit and at rest, is not sold and is not used by Lindy or its providers to train AI models. The company says users control permissions and can change or revoke access.

Published security materials reference SOC 2 Type II certification audited by Johanson Group, GDPR, HIPAA and PIPEDA compliance. Enterprise includes HIPAA support and a signed BAA. Buyers should request the current SOC 2 report, penetration-test evidence, subprocessor list and the exact contractual scope for their use case.

Lindy says deletion requests, access rights and residency requirements are supported. Organisations should confirm retention periods for email, meetings, files, prompts and outputs, plus whether connected providers temporarily store data.

Best use cases

• Email triage and reply drafting.
• Meeting preparation, notes and follow-up.
• Daily briefs and scheduled operational routines.
• Research and proposal generation.
• CRM, support and project-tool updates.
• Cross-application work with human approvals.

Advantages

• Broad daily-assistant experience across channels.
• Persistent context and shared meeting knowledge.
• Major model choice, skills, integrations and MCP.
• Built-in approvals for human oversight.
• Shared team credits with administrative allocation.

Limitations

• Per-user pricing becomes expensive for larger teams.
• Large tasks can consume thousands of credits.
• Persistent context and inbox access increase privacy exposure.
• Computer use is less predictable than direct APIs.
• Agent behaviour changes across models and connected tools.
• Enterprise governance and BAA support require sales engagement.

How to evaluate Lindy

1. Use the trial for one inbox, one meeting workflow and one routine.
2. Keep communication in draft-only mode during testing.
3. Measure credits, corrections, completion time and manual review.
4. Test missing context, ambiguous instructions and provider outages.
5. Review every integration scope and scheduled job.
6. Confirm retention, training commitments and enterprise evidence.
7. Estimate team cost using pooled credits and realistic big-build volume.

Best alternatives

ChatGPT and Claude are simpler for analysis and conversation. Microsoft Copilot and Google Gemini integrate with their productivity suites. n8n provides more deterministic workflow control and self-hosting. Gumloop focuses on shared AI agents and skills, while Zapier Agents connects a broad SaaS ecosystem.

Verdict

Lindy is a capable AI teammate for professionals who want one assistant across email, meetings, research, schedules and connected tools. Its model choice, integrations, persistent context and approvals create real operational value. The trade-offs are per-user cost, variable credits and the risk of broad access. Start with a bounded workflow, preserve human approvals and expand only after measuring reliability, credit use and privacy exposure.