Now in Beta

The platform to build & ship
AI agents

Build and Ship AI Primitives. Composable, inspectable, and boundary-first agents you can trust, debug, and deploy with confidence.

Start BuildingView on GitHub
Open Source
SOC 2 Ready
Enterprise Grade
from openknot import Agent, Boundary, Tool# Define clear boundariesboundary = Boundary(    allow=["read:docs", "search:web"],    deny=["write:admin", "delete:*"])# Compose your agentagent = Agent(    name="research-assistant",    boundary=boundary,    tools=[Tool.search, Tool.summarize],    memory="conversation")# Ship with confidenceagent.run("Analyze the quarterly report")

Built for teams who need AI they can rely on

AI Engineers
Platform Teams
Startups
Enterprises
Research Labs
DevOps Teams
10x
Faster development
99.9%
Uptime SLA
Open
Source
50+
integrations

Composable

Mix and match agents, tools, and memory systems like building blocks

100%
traceable

Inspectable

Full visibility into every decision with complete audit trails

Zero
trust issues

Boundary-first

Clear guardrails and policies that keep your AI operating safely

Why teams choose OpenKnot AI

Build AI systems that your team can understand, your stakeholders can trust, and your users can rely on.

Composable by Design

Build agents from reusable, well-defined components. Mix specialists, tools, and memory systems like building blocks.

agent = compose(  analyst,  writer,  tools=[search, summarize])
  • Modular architecture
  • Reusable components
  • Clean abstractions

Governable & Auditable

Every decision your agent makes is traceable. Define policies, enforce boundaries, and maintain complete audit trails.

audit.trace(agent_id=70">"research-1")70">"text-muted-foreground/50 italic"># 50">=> 147 decisions logged70">"text-muted-foreground/50 italic"># 50">=> 0 boundary violations70">"text-muted-foreground/50 italic"># 50">=> Full replay available
  • Full audit trails
  • Policy enforcement
  • Compliance ready

Predictable in Production

Ship with confidence knowing exactly how your agents will behave. Clear boundaries prevent unexpected actions.

boundary.check(action=70">"delete:user")70">"text-muted-foreground/50 italic"># 50">=> DENIED: action not in allowlist70">"text-muted-foreground/50 italic"># 50">=> Fallback: human_approval()
  • Behavior guarantees
  • Clear boundaries
  • Real-time monitoring

Multi-Agent Orchestration

Coordinate complex workflows across specialized agents with automatic handoffs and context sharing.

Model Agnostic

Use any LLM provider. Switch between OpenAI, Anthropic, or local models without code changes.

Built-in Workflows

Pre-built patterns for common use cases like RAG, tool calling, and multi-step reasoning.

How it works

Four simple steps to build production-ready AI agents with clear boundaries and full auditability.

01

Define Boundaries

Start by declaring what your agent can and cannot do. Set clear policies, permissions, and guardrails that keep your AI operating safely within defined limits.

boundaries.yaml
1# Define what your agent can access
2boundaries:
3  name: "research-agent"
4  allow:
5    - "read:public-docs"
6    - "read:user-owned"
7    - "search:web"
8  deny:
9    - "write:admin"
10    - "delete:*"
11    - "access:pii"
12  rate_limit: "100/hour"
02

Bind Tools + Memory

Connect your agent to the tools and context it needs. Bind APIs, databases, and memory systems with type-safe interfaces that enforce your boundaries.

tools.yaml
1# Connect tools and memory
2tools:
3  - name: "search_documents"
4    params: { query: string, limit: int }
5    returns: DocumentResult[]
6  
7  - name: "create_summary"
8    params: { content: string, style: enum }
9    returns: Summary
10
11memory:
12  type: "conversation"
13  ttl: "24h"
14  max_tokens: 8000
03

Compose Specialists

Combine specialized agents for complex workflows. Each specialist handles its domain, while the orchestrator manages handoffs and maintains context.

agents.yaml
1# Compose multi-agent workflows
2specialists:
3  analyst:
4    role: "data interpretation"
5    model: "gpt-4o"
6    
7  writer:
8    role: "content generation"  
9    model: "claude-3-opus"
10    
11  reviewer:
12    role: "quality assurance"
13    model: "gpt-4o"
14
15orchestrator:
16  type: "sequential"
17  fallback: "human_review"
04

Deploy with Confidence

Ship to production with built-in monitoring, rollback capabilities, and real-time alerting. Scale automatically while maintaining full auditability.

deploy.yaml
1# Production deployment config
2deploy:
3  environment: "production"
4  replicas: 3
5  
6monitoring:
7  traces: true
8  metrics: true
9  alerts:
10    - type: "boundary_violation"
11      notify: ["slack", "pagerduty"]
12    - type: "latency_spike"
13      threshold: "2s"
14      
15rollback:
16  enabled: true
17  keep_versions: 5

Explore our products

Tools that make OpenKnot faster to adopt, easier to explore, and ready for production use.

AI-Powered

Chat-with-Files

Chat with any docs site or GitHub repo

Get structured summaries with citations. Ideal for onboarding, audits, and quick answers from large codebases.

View on GitHubTry the demo

Docs-aware answers

Turn any docs URL into a searchable knowledge base.

Repo intelligence

Query folders, files, and APIs with contextual insights.

Fast exploration

Get the gist quickly with minimal setup.

VS Code

OpenClaw Extension

AI coding assistant for VS Code

Install OpenClaw inside VS Code with guided setup, one-click connect, and auto-reconnect. Stay in your editor while OpenClaw keeps a ready terminal session.

Install ExtensionQuick start guide

Guided install

Set up in minutes with prompts and safe defaults.

One-click connect

Launch from a status shortcut.

Open source

Browse and contribute improvements.

More products coming soon

Built for real-world applications

Use OpenKnot AI to build trustworthy AI experiences across any industry.

Customer Support

Intelligent Support Agents

Deploy AI agents that handle customer inquiries with empathy and accuracy, while staying within defined response boundaries.

80% reduction in first-response time
Consistent tone and brand voice
Seamless human handoff when needed
Complete conversation audit trails
Learn more
Research & Analysis

Research Assistants

Build agents that synthesize information from multiple sources, generate insights, and maintain clear attribution.

Cross-reference multiple data sources
Automatic citation and attribution
Learn more
E-commerce

Shopping Assistants

Create personalized shopping experiences with agents that understand preferences while respecting privacy.

Personalized recommendations
Privacy-preserving personalization
Learn more
Internal Tools

Enterprise Assistants

Build internal AI tools that help teams work faster while maintaining strict data access controls.

Learn more
Automation

Workflow Agents

Automate complex multi-step workflows with agents that can coordinate across systems.

Learn more
Data Processing

Data Agents

Process and analyze large datasets with agents that maintain data governance policies.

Learn more

Frequently Asked Questions

Everything you need to know about getting started with OpenKnot AI.

OpenKnot AI is built with boundaries as a first-class concept. While other frameworks focus on capability, we focus on controllability. Every agent you build has clear, enforceable limits on what it can do, making it suitable for enterprise and regulated environments where trust and auditability are essential.

Still have questions? Join our community

Start building today

Ready to build AI you can actually trust?

Join teams already building reliable, auditable AI agents with OpenKnot AI. Start for free, scale when you are ready.

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