ANROK
The AI Agent control plane
Anrok orchestrates multi-agent systems with adaptive routing, durable memory, governance, and observability—so agent workflows can run reliably in production.Agent demos are easy. Operating agent networks across real tools, real data, and real constraints is the hard part. Anrok provides a kernel-like runtime that coordinates agents, enforces policies, and makes behavior traceable and repeatable.
Why Anrok?
As teams move from prototypes to production, the same failure modes show up again and again:
- Coordination complexity: brittle handoffs across specialized agents and tools
- Context overload: memory, summarization, retrieval, and context budgeting become a systems problem
- Reliability gaps: partial failures, tool errors, retries, and safe fallbacks need a real runtime
- Governance needs: permissions, audit logs, policy enforcement, and approvals
- Cost control: uncontrolled token and tool-call sprawl without routing and schedulingAnrok turns agent workflows into operable systems—with controls you can measure, debug, and trust.
How It Works
Anrok is a lightweight infrastructure layer for intelligent agent communication and task orchestration. Think “agent OS” meets “control plane”: it routes work, coordinates collaboration, manages memory, and provides governance + observability across distributed LLM agents.
01.
Routing
Choose the right model / agent / tool at each step
02.
Orchestration
Multi-agent workflows with durable state and checkpoints
03.
Memory
Managed long-horizon context with lifecycle controls
04.
Governance
Policies, approvals, and auditability
05.
Observability
Traces, replay, evaluation signals, and cost telemetry
06.
Secure
Built into every aspect
Production-grade orchestration, end to end
Build with your preferred frameworks. Operate with a control plane designed for reliability, governance, and scale.1) Stateful orchestration runtime
Run complex workflows with branching, loops, and checkpoints—designed for long-horizon tasks and resumability.2) Adaptive routing & arbitration
Route each step to the best agent/model/tool based on policy, telemetry, cost budgets, latency targets, and confidence thresholds.3) Managed memory
Persist and retrieve context safely: summarization, retrieval, context packing, provenance, retention controls, and secure handling of sensitive data.4) Governance & safety controls
Permissions, approvals, human-in-the-loop gates, policy enforcement, and audit logs—built for enterprise constraints.5) Agent observability (“AgentOps”)
Trace every session, debug failures with replay, measure quality, and monitor spend and reliability over time.
Use Cases
01.
Enterprise
Coordinate multi-step actions across systems with strict permissions, auditability, and safe escalation paths.
02.
Customer support
Route tasks across retrieval, tools, and specialist agents while maintaining consistent policy controls and traceability.
03.
Developer productivity
Run long-horizon coding and incident-response workflows with checkpointing, replay, and cost-aware routing.
Get In Touch
Interested in being part of the future? Get in touch whether you're an interested beta user, partner or funding provider.
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