Lindy reference architecture

Lindy Reference Architecture

Overview

Production-ready architecture patterns for integrating Lindy AI agents into applications. Covers webhook integration, multi-agent societies, event-driven pipelines, and high-availability patterns.

Prerequisites

• Understanding of Lindy agent model (triggers, actions, skills)
• Familiarity with webhook-based architectures
• Production requirements defined (throughput, latency, reliability)

Architecture 1: Simple Webhook Integration

Single agent triggered by your application, results sent via callback.

┌─────────────┐       POST (webhook)       ┌──────────────┐
│  Your App   │ ─────────────────────────→  │ Lindy Agent  │
│             │                             │              │
│  /callback  │ ←─────────────────────────  │ HTTP Request │
│             │       POST (callback)       │   Action     │
└─────────────┘                             └──────────────┘

Implementation:

• Your app sends webhook with callbackUrl field
• Lindy agent processes and responds via Send POST Request to Callback
• Your app receives results asynchronously

Best for: Simple automations (email triage, lead scoring, content generation)

Architecture 2: Event-Driven Pipeline

Multiple event sources feed agents through a central webhook router.

┌──────────┐
│ Stripe   │──webhook──┐
└──────────┘           │
                       ▼
┌──────────┐     ┌───────────┐     ┌──────────────┐
│ Shopify  │──→  │  Router   │──→  │ Lindy Agents │
└──────────┘     │  Service  │     │              │
                 └───────────┘     │ • Order Bot  │
┌──────────┐           ▲          │ • Support Bot│
│ Your App │──webhook──┘          │ • Analytics  │
└──────────┘                      └──────────────┘

Implementation:

// Event router — maps events to specific Lindy agents
const agentWebhooks: Record<string, string> = {
  'order.created': process.env.LINDY_ORDER_AGENT_WEBHOOK!,
  'customer.support_request': process.env.LINDY_SUPPORT_AGENT_WEBHOOK!,
  'analytics.daily_report': process.env.LINDY_ANALYTICS_AGENT_WEBHOOK!,
};

app.post('/events', async (req, res) => {
  const { event, data } = req.body;
  const webhookUrl = agentWebhooks[event];

  if (!webhookUrl) {
    return res.status(400).json({ error: `Unknown event: ${event}` });
  }

  await fetch(webhookUrl, {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env.LINDY_WEBHOOK_SECRET}`,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({ event, data, callbackUrl: `${BASE_URL}/callback` }),
  });

  res.json({ routed: true, agent: event });
});

Best for: Multiple event sources, different agents per event type

Architecture 3: Multi-Agent Society (Delegation)

Specialized agents collaborate through Lindy's built-in delegation system.

┌─────────────────┐
│ Orchestrator    │
│ Lindy           │
│ (receives       │
│  initial task)  │
└───┬────────┬────┘
    │        │
    ▼        ▼
┌────────┐ ┌────────┐
│Research│ │Analysis│
│ Lindy  │ │ Lindy  │
└───┬────┘ └───┬────┘
    │          │
    ▼          ▼
┌─────────────────┐
│ Writer Lindy    │
│ (synthesizes    │
│  final output)  │
└─────────────────┘

Setup in Lindy:

1. Create specialized agents with Agent Message Received triggers
2. Orchestrator uses Agent Send Message action to delegate
3. Each agent completes its specialty and sends results forward
4. Writer agent synthesizes and delivers final output

Key decisions:

Decision	Option A	Option B
Context passing	Full context (accurate, expensive)	Selective context (cheap, focused)
Error handling	Agent retries	Orchestrator retry logic
Parallelism	Sequential delegation	Parallel delegation with merge

Best for: Complex tasks requiring multiple specialties (research + analysis + writing)

Architecture 4: Scheduled Pipeline

Agents run on schedules, each feeding data to the next.

                    Schedule: Daily 6 AM
                         │
                         ▼
                  ┌──────────────┐
                  │ Data Fetch   │ Pulls from APIs/databases
                  │ Lindy        │
                  └──────┬───────┘
                         │ Agent Send Message
                         ▼
                  ┌──────────────┐
                  │ Analysis     │ Processes & summarizes
                  │ Lindy        │
                  └──────┬───────┘
                         │ Agent Send Message
                         ▼
                  ┌──────────────┐
                  │ Report       │ Formats & delivers
                  │ Lindy        │
                  │  → Slack     │
                  │  → Email     │
                  └──────────────┘

Best for: Daily reports, weekly digests, scheduled data processing

Architecture 5: Chat + Knowledge Base

Agent deployed as customer-facing chatbot with RAG-powered responses.

┌──────────────┐     ┌──────────────┐     ┌──────────────┐
│  Website     │     │ Lindy Agent  │     │ Knowledge    │
│  (Embed      │◀──▶ │              │◀──▶ │ Base         │
│   Widget)    │     │ Chat Trigger │     │ PDFs, Docs,  │
└──────────────┘     │ + KB Search  │     │ Websites     │
                     │ + Condition  │     └──────────────┘
                     │ + Escalate   │
                     └──────────────┘
                            │
                            ▼ (if escalation needed)
                     ┌──────────────┐
                     │ Slack DM to  │
                     │ human agent  │
                     └──────────────┘

Deploy the embed widget:

<!-- Paste near end of <body> tag -->
<script src="https://embed.lindy.ai/widget.js"
  data-lindy-id="YOUR_AGENT_ID"></script>

KB configuration:

• Sources: Product docs, FAQ PDFs, knowledge articles
• Fuzziness: 100 (semantic search)
• Max Results: 5 (balance relevance vs context size)
• Auto-resync: every 24 hours

Best for: Customer support, FAQ bots, internal knowledge assistants

Architecture Decision Matrix

Pattern	Throughput	Latency	Complexity	Cost
Simple webhook	Low-Med	2-15s	Low	Low
Event-driven pipeline	High	5-30s	Medium	Medium
Multi-agent society	Low-Med	30-120s	High	High
Scheduled pipeline	Batch	N/A	Medium	Predictable
Chat + KB	Interactive	2-10s	Low-Med	Per-message

Error Handling

Pattern	Failure Mode	Recovery
Simple webhook	Agent fails	Retry webhook with backoff
Event-driven	Router crash	Queue events, replay on recovery
Multi-agent	Delegation fails	Orchestrator retries or skips
Scheduled	Missed schedule	Next run catches up
Chat + KB	KB empty	Fallback to generic response + escalate

Resources

• Lindy Introduction
• Delegation 101
• Building a Chatbot
• Lindy Embed

Next Steps

Proceed to Flagship tier skills for enterprise features: multi-env, observability, incident response, data handling, RBAC, and migration.