name: lindy-reference-architecture description: 'Reference architectures for Lindy AI agent integrations.

Use when designing systems, planning multi-agent architectures,

or implementing production integration patterns.

Trigger with phrases like "lindy architecture", "lindy design",

"lindy system design", "lindy patterns", "lindy multi-agent".

' allowed-tools: Read, Write, Edit version: 1.16.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

saas
lindy
lindy-reference compatibility: Designed for Claude Code

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:

Create specialized agents with Agent Message Received triggers
Orchestrator uses Agent Send Message action to delegate
Each agent completes its specialty and sends results forward
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

Next Steps

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

Reference Architectures for Lindy AI Agents

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