Lindy is an automation platform that uses AI to function as a digital teammate. Instead of building long chains of triggers and actions, you create AI agents that understand context and automate workflows across tools like Gmail, Slack, HubSpot, and Google Calendar.
The platform blends reasoning and execution, moving beyond rule-based automation. Teams can hand off repetitive scheduling, lead follow-ups, and customer communication to AI. With a credit-based pricing model and compliance standards like SOC 2 and HIPAA, Lindy sits between traditional workflow builders and modern AI assistants.
Key features
Lindy helps teams automate complex workflows through intelligent agents that understand context and perform actions automatically. Its features center on reasoning, communication, and control so work can move with less manual input.
AI agent builder
Create agents that understand instructions in plain language and take action automatically. Agents can manage messages, schedule meetings, or update records without requiring detailed logic trees. This setup makes it easier to automate unstructured work that traditional tools struggle with.
Knowledge base and context
Upload company data, process documents, or FAQs so agents can reference them during execution. The knowledge base gives context, helping agents write accurate emails, answer questions, or make decisions that fit internal standards.
Integrations
Lindy connects with over 25 popular apps, including Gmail, Slack, HubSpot, and Google Calendar. These integrations let agents automate messages, schedule meetings, and update CRM data across systems. While the catalog is smaller than platforms like Make or Zapier, it covers the most common tools used in sales, operations, and customer support.
Visual workflow builder
A low-code interface lets users define steps, triggers, and actions with simple inputs. You can test and adjust each workflow from one screen. It feels closer to designing a teammate’s process than coding a workflow.
Security and compliance
Lindy supports SOC 2, GDPR, HIPAA, and PIPEDA compliance. This makes it viable for teams handling sensitive data while keeping setup light. Enterprise controls like detailed roles and audit logs are still expanding.
Pricing and plans (2025)
Lindy uses a credit-based pricing model. Every time an agent runs a task, it consumes credits based on the model size and complexity. A short message or database update might use only a few credits. Longer reasoning tasks, large data lookups, or multi-step actions use more.
This model gives flexibility but makes forecasting important. Credits are the core unit of billing, similar to how Zapier charges by task. Lindy lists examples to help teams estimate costs, such as sending an email (7 credits), replying in a thread (3 credits), or making a short phone interaction (265 credits). Each plan increases the monthly credit limit and unlocks more features.
| Plan | Monthly credits | Plan inclusions | Best for |
|---|---|---|---|
| Free | 400 | Up to 400 tasks and 1M-character knowledge base. | Testing and personal use. |
| Pro | 5,000+ | Premium actions, larger 20M-character knowledge base, basic phone features. | Small teams and active workflows. |
| Business | 30,000+ | Premium actions, premium phone features, priority support. | Growing teams managing higher volume. |
| Custom business | 100,000+ | Account manager, custom agent implementation, advanced support. | Enterprise environments or tailored deployments. |
Lindy does not list public pricing. Teams can test the platform through the free plan and contact sales when they need higher limits. Costs vary by model size and complexity, typically ranging from about one cent to ten cents per task.
As a result, Lindy’s credit model gives teams flexibility to scale usage, though costs can fluctuate as workloads grow. Because pricing depends on task complexity, tracking credit consumption early helps teams stay efficient and manage spending.
Pros and cons
Choosing a workflow automation platform often comes down to how it balances flexibility, control, and cost. Lindy brings strong innovation through AI-driven agents but also introduces new trade-offs that teams should understand before scaling.
Pros
- AI agents that handle unstructured work. Lindy goes beyond rules and triggers, using reasoning and company context to manage tasks like follow-ups, scheduling, or communication.
- Flexible usage model. Credits let teams pay for activity rather than fixed tiers, making it easier to scale up or pause as workloads change.
- Strong compliance coverage. SOC 2, HIPAA, GDPR, and PIPEDA support make Lindy usable in regulated industries.
- Visual builder with low setup overhead. Teams can design and deploy agents without coding, shortening the time from idea to execution.
- Natural language setup. Workflows can be created or refined in plain language, lowering the barrier for non-technical users and speeding adoption.
Cons
- No public pricing. Costs require a sales conversation, which limits transparency for smaller teams comparing tools.
- Credit forecasting can be complex. Usage varies by task type and model, so estimating monthly spend takes monitoring and adjustment.
- Smaller integration catalog. Coverage is growing but narrower than established tools like Zapier or Make.
- Enterprise controls still developing. Role management and audit logs are less mature than in long-standing automation platforms.
- Newer ecosystem. As a younger product, reliability and support processes may continue to evolve.
Lindy vs relay.app
Lindy and relay.app both bring AI into workflow automation, but they differ in how much control teams retain. Relay focuses on structured workflows with AI helping draft, summarize, or approve steps. Lindy aims for autonomy, where agents reason through context and act without constant input. The choice comes down to how hands-on your team wants to be.
| Feature | Lindy | relay.app |
|---|---|---|
| Automation model | AI agents that act as digital teammates, reasoning through context and executing tasks end to end. | AI-assisted workflows where humans stay in the loop for approvals or review. |
| Workflow design | Visual builder for configuring agents and triggers in plain language. | Step-based visual builder with paths, conditions, and human review points. |
| Use of AI | Central to execution. Agents interpret requests, reference data, and act independently. | Supports AI summaries, text generation, and logic assistance within structured workflows. |
| Pricing model | Credit-based usage. Each task consumes credits based on complexity and model size. | Step-based pricing with limits on workflow steps and AI credits per month. |
| Integrations | Connects to Gmail, Slack, HubSpot, and core business tools. Smaller catalog focused on communication-heavy workflows. | Broad coverage across modern SaaS tools, with deeper integrations for common business apps. |
| Control and oversight | Autonomous agents. Limited checkpoints once an agent runs. | Strong human oversight with manual or conditional approvals. |
| Best for | Teams ready to delegate repetitive outreach, scheduling, or support tasks to AI. | Teams that want AI help but prefer to approve or adjust each workflow step. |
Pick Lindy if you want to automate full workflows where AI acts independently. It suits teams ready to hand off email, scheduling, and follow-up tasks to intelligent agents.
Choose relay.app if you want structure and control. It works best for teams experimenting with AI automation while keeping humans involved in key decisions.
Read our review: relay.app Review (2025): Who Should Use It and Why?
Bottom line
Lindy stands out for merging workflow automation with intelligent reasoning. Its agents act like digital teammates, handling communication and coordination across tools such as Gmail, Slack, and HubSpot. This gives teams a faster way to automate work that normally requires judgment or back-and-forth messaging.
The platform fits startups and small teams exploring automation before committing to larger systems. It works best for operations, sales, or recruiting teams managing repetitive outreach or scheduling.
Lindy is an early look at how AI can take on real operational tasks. For teams willing to experiment and refine, it offers automation with depth and intelligence rather than surface-level speed.
