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that actually ship.

The orchestration runtime for AI agents that need to run in the real world — not just the notebook.

Parallel DAG ExecutionSelf-Healing SwarmsFull Observability
400+ engineers on the waitlist
octaclaw / swarm-7f2a · MarketAnalystSwarmLIVE
Researcher
Analyst
Writer
Critic
[00:00]systemMarketAnalystSwarm initialized
[00:01]orchGoal parsed → 4 parallel task lanes
[00:01]agent-1tool: web_search(q='AI infra market')
[00:02]agent-2tool: code_exec(lang=python)
[00:02]systemCheckpoint α saved — state persisted
[00:03]agent-1Retrieved 32 sources — aggregating...
[00:03]orchParallelism: 4/4 active lanes
[00:04]agent-3Drafting executive summary (sec 2/5)
[00:04]agent-2Schema: 14 competitor profiles built
[00:05]systemCheckpoint β saved
[00:05]orchETA: 12s — on schedule
[00:06]agent-4Critic: reviewing draft…
[00:00]systemMarketAnalystSwarm initialized
[00:01]orchGoal parsed → 4 parallel task lanes
[00:01]agent-1tool: web_search(q='AI infra market')
[00:02]agent-2tool: code_exec(lang=python)
[00:02]systemCheckpoint α saved — state persisted
[00:03]agent-1Retrieved 32 sources — aggregating...
[00:03]orchParallelism: 4/4 active lanes
[00:04]agent-3Drafting executive summary (sec 2/5)
[00:04]agent-2Schema: 14 competitor profiles built
[00:05]systemCheckpoint β saved
[00:05]orchETA: 12s — on schedule
[00:06]agent-4Critic: reviewing draft…
awaiting orchestrator...
Elapsed: 6.2s
4 agents · Live

Completed in 6.2s

4 agents · 48 tool calls

Routes to any model provider
  • AAnthropic Claude
  • GPTOpenAI GPT-4o
  • GGoogle Gemini
  • GGroq
  • MMistral AI
  • CCohere
  • xxAI Grok
  • MMeta LLaMA
  • PPerplexity
  • TTogether AI
  • AWSAWS Bedrock
  • AzAzure AI
<0ms
DAG planning latency
0+
Concurrent agents
0+
Model providers
0%
Deterministic replay
Capabilities

Everything you need to shipagents to production.

OctaClaw handles orchestration, fault tolerance, and observability so you can focus on what matters.

GOALAGENT·AAGENT·BAGENT·COUTPUTresearchanalyzesynthesize
Core Architecture

Parallel DAG Execution

Decompose any goal into directed acyclic task graphs. Specialist agents execute concurrently across independent lanes — eliminating bottlenecks by orders of magnitude.

faster than sequential
parallel agent lanes
Anthropic Claudeactive
OpenAI GPT-4oactive
Google Geminiactive
Groq LLaMAactive
xAI Grok
Mistral AI
Cohere
+ 1 more
Routing

Universal Model Router

Route each agent to the optimal provider. One API across Anthropic, OpenAI, Gemini, Groq, and more.

Running3/3 active
Fault Detectedagent-2 timeout
Re-routingswarm adapting
Recoveredcheckpoint used
Reliability

Zero-Config Recovery

Automatic fault detection and re-instantiation. Swarms self-heal without human intervention.

live telemetry● LIVE
[00:00]systemSwarm initialized
[00:01]orch4 parallel tasks created
[00:01]agent-1tool: web_search(…)
[00:02]agent-2tool: code_exec(python)
[00:02]systemCheckpoint α saved
[00:03]agent-132 sources retrieved
[00:03]orch3/3 active lanes
[00:04]agent-3Drafting section 2/5…
[00:00]systemSwarm initialized
[00:01]orch4 parallel tasks created
[00:01]agent-1tool: web_search(…)
[00:02]agent-2tool: code_exec(python)
[00:02]systemCheckpoint α saved
[00:03]agent-132 sources retrieved
[00:03]orch3/3 active lanes
[00:04]agent-3Drafting section 2/5…
Observability

Real-Time Telemetry

Every agent action and tool call streamed live. Full structured traces with run IDs and on-demand replay.

68%
α
Saved
β
Saved
γ
Saved
δ
Saved
Replay from checkpoint β
Debugging

Deterministic Replay

Every swarm run is checkpointed. Replay any execution from any point — for debugging, auditing, or compliance. No black boxes.

web_searchcode_execbrowserfile_ioapi_calldb_queryemailcalendar+ 42 more
Tooling

50+ Built-in Tools

Web search, code execution, browser automation, file I/O, API calls, database queries — agents have a full toolkit out of the box.

How It Works

From intent to executionin three steps.

No pipelines to wire up. No agents to babysit. Describe the goal — OctaClaw handles everything from planning to delivery.

01
Natural language → structured plan
Goal Input

“Research competitors, draft a 10-page market analysis, and create an executive summary.”

parsing...
Research
Analysis
Writing

Define Your Goal

Describe what you need in plain language. OctaClaw parses your intent, identifies required capabilities, and generates a structured execution plan automatically.

02
Parallel agent instantiation
ResearcherReady
AnalystReady
WriterStandby
CriticReady

Swarm Assembled

Specialist agents are instantiated with their own tools, context windows, and objectives. The orchestrator coordinates resource allocation across the entire swarm.

03
Fault-tolerant execution
execution progressLIVE
Research phase
100%
Analysis phase
100%
Writing phase
68%
Review phase
0%

Autonomous Execution

The swarm executes in parallel, self-corrects on failure, and delivers results with full audit trails, checkpointed states, and deterministic replay capability.

Developer Experience

Ship in minutes,
not weeks.

A clean, typed SDK for Python and TypeScript. Describe your goal, choose your model, and let OctaClaw handle the orchestration.

  • Fully typed Python & TypeScript SDKs
  • Streaming results and real-time hooks
  • Built-in retry, checkpointing, and replay
  • OpenTelemetry compatible trace exports
Free during beta
1import asyncio
2from octaclaw import OctaClaw, Swarm
3 
4client = OctaClaw(api_key=os.environ["OCTACLAW_KEY"])
5 
6# Define your goal in plain language
7result = await client.swarm.run(
8 goal="Analyze Q4 competitor landscape and"
9 " produce an executive summary",
10 model="claude-3-5-sonnet-20241022",
11 parallel=True,
12 max_agents=6,
13)
14 
15# Full telemetry available on every run
16print(f"✓ Completed in {result.elapsed_ms}ms")
17print(f"✓ Agents used: {result.agent_count}")
18print(result.summary)
Completed in 4.2s · 4 agents · 48 tool calls · 32 sources
Private beta · Now open

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