Your workflows are still
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Wire LLMs, APIs, and custom logic into autonomous agents that execute multi-step workflows while you sleep. No Zapier duct-tape. No Python glue scripts. Just agents that run.
Agents Deployed
0
across 342 orgs · updated 05:10:54
Tasks Completed · Last 24h
0
+12.4% vs prior day · p99 latency 3.2s
Avg Execution Time
1.4s
median across all agent types · SLA 5s
Every column you were
about to check manually.
Technical evaluation criteria, side by side. Click any row to expand rate limits, webhook schemas, and retry policies.
Quick-start via CLI or API
Orchestrate ships a single CLI command that scaffolds your first agent with model binding, retry policy, and webhook endpoint pre-configured.
$ npm install -g @orchestrate/cli $ orchestrate init --model gpt-4o --name invoice-parser ✓ Agent scaffolded in ./agents/invoice-parser ✓ Webhook endpoint: https://run.orchestrate.io/agt-001 ✓ Retry policy: 3x exponential backoff $ orchestrate deploy → Agent live in 4.2s
Model registry — 40+ providers
Orchestrate maintains a live model registry covering OpenAI, Anthropic, Google Gemini, Mistral, Cohere, and 35+ open-source models via Ollama and HuggingFace endpoints. Model routing can be rule-based (cost, latency, capability) or AI-selected per task.
// model_config.yaml
model:
primary: gpt-4o
fallback: claude-3-5-sonnet
routing:
cost_ceiling: $0.02/task
latency_sla: 3s
auto_failover: trueDAG-based execution graph
Orchestrate models workflows as directed acyclic graphs (DAGs). Each node can branch to N downstream nodes based on output conditions, model confidence scores, or arbitrary custom logic. Cycles are supported for retry loops.
// workflow.json (excerpt)
{
"nodes": {
"classify": { "model": "gpt-4o-mini", "next": ["approve", "escalate", "reject"] },
"approve": { "action": "crm.updateStatus", "next": ["notify"] },
"escalate": { "action": "slack.alert", "condition": "confidence < 0.7" }
}
}Three-layer error recovery
Layer 1: Per-step retry with exponential backoff (configurable). Layer 2: Fallback model routing when primary LLM fails or exceeds latency SLA. Layer 3: Dead-letter queue with human escalation webhook for unrecoverable failures.
retry_policy:
max_attempts: 3
backoff: exponential
initial_delay: 500ms
max_delay: 30s
on_exhausted:
action: dead_letter_queue
notify: ops@yourco.com
include: [trace_id, inputs, error]Immutable execution traces
Every agent execution produces a cryptographically signed trace log including: model inputs/outputs, tool calls, latency breakdown per step, token counts, cost attribution, and operator identity. Logs are queryable via API and exportable to S3, Datadog, or Splunk.
GET /v1/traces/agt-001/exec-2026022705104
{
"trace_id": "tr_8xK2mN9pQ",
"agent": "invoice-parser",
"duration_ms": 1243,
"steps": [
{ "step": "extract", "model": "gpt-4o", "tokens": 847, "cost": 0.0042 },
{ "step": "validate", "tool": "schema_check", "passed": true },
{ "step": "post", "action": "crm.create", "status": 201 }
],
"signed": "sha256:a3f9..."
}Flat per-execution pricing — no task multiplication
Zapier bills per task, meaning a 10-step workflow processing 100 records = 1,000 tasks billed. Orchestrate bills per agent execution regardless of internal step count or record volume. A 50-step workflow processing 10,000 records = 1 execution billed.
Rate limit specifications
Orchestrate rate limits are enforced at the organization level, not per-workflow. Burst allowance is 3× sustained rate for up to 60 seconds. Limits scale automatically with plan tier and can be raised on request with 24h SLA.
// Rate limit headers on every response X-RateLimit-Limit: 10000 X-RateLimit-Remaining: 9847 X-RateLimit-Reset: 1740632400 X-Burst-Remaining: 29847 Retry-After: (only on 429)
Graph-based orchestration.
Branching logic that doesn't hit a ceiling.
1import { Agent, workflow } from '@orchestrate/sdk';23const invoiceAgent = new Agent({4 model: 'gpt-4o',5 fallback: 'claude-3-5-sonnet',6 retry: { max: 3, backoff: 'exponential' },7});89export const invoiceWorkflow = workflow({10 trigger: { type: 'webhook', path: '/invoices' },11 steps: [12 {13 id: 'extract',14 agent: invoiceAgent,15 prompt: 'Extract line items and total from invoice',16 output: 'structured',17 },18 {19 id: 'validate',20 tool: 'schema.validate',21 schema: InvoiceSchema,22 on_fail: 'dead_letter',23 },24 {25 id: 'route',26 branch: [27 { if: 'total > 10000', next: 'human_review' },28 { if: 'confidence < 0.8', next: 'human_review' },29 { else: 'auto_approve' },30 ],31 },32 ],33});
Avg First-Year ROI
147%
Based on 342 production deployments
Ops Cost Reduction
30%
Analyst estimate, automated workflows
Hours Saved / Week
12.5h
Per operator using agent automation
Engineering teams who
stopped building and started shipping.
"We replaced four Zapier zaps, two Python cron scripts, and a shared spreadsheet with one Orchestrate workflow. It's been running for six weeks without a single page."
Marcus Okonkwo
VP Engineering · Meridian Fintech
6 wks
zero incidents
"The spec comparison sold my CTO in one meeting. We didn't have to build a deck — we just sent the link. Closed the eval in 9 days."
Priya Venkataraman
Engineering Lead · Stackwise Labs
9 days
eval to contract
"LangChain gave us flexibility but no guardrails. Orchestrate gave us both. The audit logs alone justify the cost — our compliance team went from skeptical to enthusiastic."
Devon Hargrove
CTO · Elevate Health Systems
SOC 2
audit passed
"We were 3 weeks into building our own orchestration layer when we found Orchestrate. We stopped immediately. The branching logic handles cases we hadn't even designed for yet."
Fatima Al-Rashidi
Head of Automation
50%+
of companies expected to adopt AI orchestration platforms by 2025
Gartner Analysis
85%
of enterprises report improved operational efficiency after adopting AI agent orchestration
Industry Report 2025
50%+
of companies expected to adopt AI orchestration platforms by 2025
Gartner Analysis
23%
CAGR — AI orchestration market 2023–2028
Market Research
300%
long-term ROI reported by teams with connected multi-step automation
McKinsey Ops Study