Da mensagem ao resultado. Automaticamente.

Cada fluxo abaixo costumava custar uma hora a alguém. Todos os dias.

Email Spreadsheet Web App Logistics App WhatsApp
📧 Gmail · Inbox ops@acmedist.example
deliveries_05_04.xlsx — parsing...
#CustomerAddressStatus
001Brown, M.Oak St 47, 3FUploading
002Smith, J.Elm Ave 212Uploading
003Davis, A.Maple Rd 88Uploading
+ 31 more rows...
Extracting delivery data...
Web App — Delivery Manager
0
Total
0
Pending
0
Done
001
Brown, M.
Oak St 47, 3F
Pending
002
Smith, J.
Elm Ave 212
Pending
003
Davis, A.
Maple Rd 88
Pending
Loading deliveries...
9:41 AM🔋 87%
🚐 Logistics App
Route A — 12 stops · Est. 14:30
001
Brown, M.
Oak St 47, 3F
002
Smith, J.
Elm Ave 212
Delivered ✓
003
Davis, A.
Maple Rd 88
💬 Logistics Team · Orchestra
Workflow — real time Processing
📧
Gmail
Inbound email
🔍
Email Filter
Rule engine
✓ from: trusted sender
✓ has: spreadsheet
Sheet Parser
Extract deliveries
🖥️
Web App
External API · load
Other rules
Different path
Logistics App
Status: delivered
🚚
Logistics Agent
Claude · supervised
💬
WhatsApp Group
Team notification

Waiting for incoming email...

Arraste. Ligue. Simule.

Don't know where to start? The AI will help you. Double-click any node to configure it — or ask the AI tab to fill it for you. Hit Simulate to see it run. No API credits burned, no real agents firing. Book a call to see a live flow against your actual data.

01
Connect
Drag a channel node

WhatsApp, Telegram, voice, email, webhooks — all in the palette on the left. Drag one onto the canvas.

02
Route
Wire it to an agent

Connect Router → Intent AI → your agent. Double-click to configure. No manual rules. No if/else spaghetti.

03
Simulate
Hit ▶ and watch it run

Agents run in parallel. One crashes — it restarts itself. You wake up to results, not pages.

Encontramos a sua equipa onde ela já está

No new apps. No training. Just the tools your people already use.

WhatsApp
Telegram
Gmail
Voice / Phone
Webhooks
REST APIs
Scheduled Jobs

Parece o n8n.
Construído para a escala do WhatsApp.

Zapier, Make, n8n — great tools. Built on Python or Node.js. They work until they don't. When an agent crashes at 3 am nobody notices, everything stops, and you wake up to silence.

Orchestra is built on Elixir OTP — the same battle-tested runtime that powers WhatsApp (2B users), Discord, and Riot Games. Agents are supervised processes. One crash = one restart in <5ms. The rest keep running. You stay asleep.

Python
Zapier · Make · IFTTT
Node.js
n8n · Activepieces
Elixir OTP
Orchestra
Concurrency Sequential tasks
queue-based, one at a time
Shared process heap
one V8 GC pause stalls every agent
Millions of actors
every agent truly parallel
Throughput ~2k msg/s ~10k msg/s ~1M+ msg/s per node
Agent crash Flow stops.
manual restart required
Process dies.
everything it owned goes down
Restart in <5ms.
all other agents untouched
Deploy update Full restart
active flows interrupted
Restart required
downtime guaranteed
Hot swap — zero downtime
running sessions unaffected
State on crash Lost Lost Supervisor restores it
Distribution Cloud-only vendor lock-in Manual (k8s, PM2) Built into the VM
just connect nodes
Async events Polling / webhooks
artificial delays
Callbacks / async-await
still single-threaded
Native message passing
truly async, no blocking
Orchestra vs Zapier

What you'd build to replace Orchestra

To run reliable agent workflows at WhatsApp scale yourself, you'd need this stack — and these monthly bills.

Do It Yourself Stack
Cloud infra (compute, queues, Redis) $350/mo
Monitoring + alerting (Grafana, PagerDuty) $150/mo
LLM API keys (Anthropic, OpenAI, Whisper) $380/mo
WhatsApp Business API fees $220/mo
Build time amortised (60h @ $100/h ÷ 12) $500/mo
Ongoing maintenance (10 hrs/mo @ $100/h) $1,000/mo
Total $2,600/mo
ONE TOOL
Orchestra
Message queue — built in
Process supervision — built in
Distributed state — built in
Auto-restart on crash — built in
AI self-healing — built in
Zero DevOps overhead
Total $299/mo

LET IT
BREAK.

The system reads its own logs when it fails.
You wake up to a post-mortem, not a page.

Traditional ops: alert fires at 3am → on-call engineer wakes up → reads logs → fixes → goes back to sleep. That costs $4,200 every time.

Orchestra agents crash, read their own error logs, search for the root cause, apply the fix — and report to Slack. You wake up to a post-mortem, not a page.

🔴
Agent crashes at 03:14
OTP supervisor restarts in <5ms
🔍
Error log analysed by AI
Root cause identified in 8 seconds
Fix applied automatically
Config patched, service restored
📲
You get a WhatsApp at 09:00
"Incident resolved. 14 min downtime. RCA attached."
// 03:14:22 — Auto-recovery log
❌ [invoice-agent] DBError: connection pool exhausted
⚙️ Supervisor: restarting in 3ms...
✓ Agent restarted. Checking last 100 error lines.
AI: root cause = DB pool_size=5, peak load=47 conns
AI: fix = increase pool_size to 25, apply now? yes
✓ Config updated. No downtime. Pool: 25.
📲 WhatsApp → You: "Resolved. 14min. RCA saved."
// 03:14:36 — Total elapsed: 14 seconds
// On-call pages sent: 0
// Engineers woken: 0

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