SYSTEM NOMINAL
|UPTIME 99.97%|8 RUNNING · 2 QUEUED · 2 IDLE2026-05-30 06:52:26 UTC

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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

Agent Status Grid
8 Running2 Queued2 Idle
Agent IDWorkflowModelTasksLatencyStatus
agt-001invoice-parserGPT-4o2,8470.9s
RUNNING
agt-002crm-enricherClaude 3.55,1021.2s
RUNNING
agt-003lead-qualifierGPT-4o1,2931.1s
RUNNING
agt-004contract-reviewerClaude 3.5
QUEUED
agt-005data-normalizerGemini 1.58,8410.7s
RUNNING
agt-006support-routerGPT-4o-mini3,2170.4s
RUNNING
agt-007report-generatorGPT-4o
IDLE
agt-008email-drafterClaude 3.5
QUEUED
agt-009code-reviewerGPT-4o4,1292.1s
RUNNING
agt-010ticket-triageGPT-4o-mini9,9040.3s
RUNNING
agt-011forecast-agentGemini 1.5
IDLE
agt-012doc-indexertext-embed-33,3660.6s
RUNNING
Showing 12 of 1,247 agents · Auto-refresh 2sLast sync: 06:52:26 UTC
Spec Sheet

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.

SpecificationOrchestrateZapierLangChainn8n
Setup
Time to first agent
< 5 minutes
15–30 min
2–4 hours
30–60 min

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
Infrastructure required
None (managed)
None (managed)
Full stack (self-managed)
Self-host or cloud
Models
Supported LLMs
40+ models
OpenAI only
All (code required)
12 via nodes

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: true
Logic
Branching depth
Unlimited (graph)
2 levels (Paths)
Unlimited (code)
5 levels

DAG-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" }
  }
}
Parallel execution
Yes
No
Yes
Yes
Reliability
Error recovery
Auto-retry + fallback model
Manual replay only
Custom code required
Workflow-level retry

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]
Uptime SLA
99.9% (contractual)
99.9% (best-effort)
Self-managed
99.5% (cloud)
Observability
Audit logging
Full trace + inputs/outputs
Basic task history
Custom (LangSmith)
Execution logs only

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..."
}
Compliance
SOC 2 Type II
Yes
Yes
No
No
Data residency (EU/US)
Yes
No
No
Yes
Cost
Pricing model
Per execution (flat)
Per task (step × records)
Infrastructure cost
Per workflow run

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 limits
10,000 exec/min (Enterprise)
100 tasks/min
API-dependent
500 exec/min (cloud)

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)
Data sourced from public documentation · Last verified Feb 2026Download full spec PDF →
Execution Engine

Graph-based orchestration.
Branching logic that doesn't hit a ceiling.

Live Execution · invoice-parser
RUNNING
TriggerWebhook · Schedule · API call
🧠ClassifyGPT-4o · confidence score
BranchRoute by confidence threshold
🔗EnrichCRM lookup · data append
PostWrite to Salesforce · Slack alert
Step: Branchexec time: 0.79s
model: gpt-4o
tokens_in: 847
tokens_out: 213
confidence: 0.94
next_branch: auto_approve
workflow.ts
1import { Agent, workflow } from '@orchestrate/sdk';
2
3const invoiceAgent = new Agent({
4 model: 'gpt-4o',
5 fallback: 'claude-3-5-sonnet',
6 retry: { max: 3, backoff: 'exponential' },
7});
8
9export 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

Connects to
OpenAIAnthropicGeminiSalesforceHubSpotSlackGitHubPostgresStripeNotionJiraLinearZapierTwilioSendGridOpenAIAnthropicGeminiSalesforceHubSpotSlackGitHubPostgresStripeNotionJiraLinearZapierTwilioSendGrid
Field Reports

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 profile photo

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 profile photo

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 profile photo

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 profile photo

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

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