One line to production‑ready agents.
Anchor is the stateful runtime layer that adds persistent sessions, exact replay, and NVIDIA acceleration to any agent — without changing your code.
# Before
client = OpenAI()
# After — one line change
client = OpenAI(
base_url="https://anchor.maximlabs.co/v1"
)Everything your agents need in production.
Zero-code infrastructure that works with any framework — LangChain, CrewAI, AutoGen, LangGraph, or your own custom agents.
Persistent Sessions
Agents that remember
Stateful agent sessions backed by Redis Streams. Full context across every step — no more mid-task context loss.
Replay Engine
Debug any failure in seconds
Re-execute any past agent run exactly as it happened. Swap models, test alternatives — all on real historical data.
Simulate Mode
Test without cost
Run shadow copies of any session with zero tool costs. A/B test prompts, models, and routing against production data.
Hybrid Routing
Right model, right time
Automatically route each step to the optimal endpoint. Cheap calls go public, complex reasoning uses your NVIDIA NIM.
Observability Dashboard
Full visibility, zero instrumentation
Execution graphs, cost forecasting, token budgets, and GPU ROI — all via OpenTelemetry. No SDK changes required.
Anomaly Detection
Catch loops before they cost you
Automatic loop detection, cost spike alerts, and lightweight NIM-powered root cause analysis for enterprise governance.
Watch Anchor handle a real failure.
An agent run fails mid-task. Anchor preserved every step. One click replays it — with NVIDIA NIM — at zero extra cost.
▋Simulate a production agent run
State is always preserved
Every step is written to durable storage before the next begins. Failures never lose context.
Replay at zero tool cost
Stored tool responses are replayed — no re-calling external APIs. Only the LLM step re-runs.
NVIDIA NIM on complex steps
Hybrid routing upgrades to NIM automatically for steps that need longer context or stronger reasoning.
How Anchor works
Anchor sits between your agent and the LLM provider. Every call is intercepted, enriched, traced, and persisted for replay.
Anchor is the production harness for every NVIDIA Agent Blueprint.
NVIDIA Blueprints ship powerful inference. Anchor provides the runtime layer they're missing — persistent sessions, exact replay, and GPU-optimized routing. Zero code changes required.
Multi-Agent Warehouse Automation
Persistent sessions keep inventory, order, and logistics agents synchronized across thousands of concurrent warehouse events — with exact replay for any failed run.
Ambient Healthcare
Exact replay and simulate mode let healthcare orgs test clinical decision agents against real historical sessions — at zero cost and zero patient data risk.
Cybersecurity Response
Anomaly detection flags runaway loops and cost spikes in real time. Full audit trails and OpenTelemetry traces satisfy compliance requirements out of the box.
Data Flywheels
Hybrid routing sends data-intensive steps to on-prem NIM while keeping ICMS warm hints active — eliminating KV-cache cold starts and recovering 20–40% GPU utilization.
The layer no one else owns.
Anchor operates at the infrastructure layer — below every framework, above every provider. No other solution offers zero-code setup, native NVIDIA optimization, and infrastructure-level replay simultaneously.
Why no one else builds this
Model providers — Optimize for their own models — not cross-provider infrastructure. OpenAI and Anthropic have no incentive to build vendor-neutral replay.
LiteLLM — Stays stateless by design — it's a routing proxy, not a runtime harness. Stateful sessions would break their architecture.
Observability tools — Require SDK instrumentation and are post-hoc only. They can observe, but they cannot replay or simulate.
Frameworks — Require you to build inside their stack. LangGraph and Letta are great — but you can't drop them in without code changes.
Frequently asked questions.
No. Anchor is an OpenAI-compatible API proxy. You change one line — your base_url — and everything else stays the same. No SDKs, no wrappers, no lock-in.
Anchor works with any OpenAI-compatible provider: OpenAI, Anthropic (via adapter), NVIDIA NIM, Azure OpenAI, Groq, Together, and more. We route through LiteLLM, so if LiteLLM supports it, we do too.
Yes, Anchor acts as a proxy — your requests pass through our infrastructure for session management, tracing, and replay. All data is encrypted in transit and at rest. We offer self-hosted deployments for enterprise customers who require full data sovereignty.
Every agent session is backed by Redis Streams. We store the full context — messages, tool calls, model responses — so your agent can resume exactly where it left off, even across process restarts.
Replay lets you re-execute any past agent run with the exact same inputs, but with a different model, prompt, or configuration. It's like git bisect for AI agents — find exactly where things went wrong.
Those are observability platforms — they watch your agents. Anchor is a runtime layer — it actively manages sessions, routes models, detects loops, and optimizes inference. We're infrastructure, not monitoring.
Yes. We're committed to a generous free tier for individual developers and small teams. Pricing details will be announced at launch. Join the waitlist to be the first to know.
Enterprise self-hosted deployments are on our roadmap. Our initial launch will be a managed cloud service. Contact us if you need on-premise deployment.
Be the first to deploy.
Sign up for early access. We'll reach out when Anchor launches — and you'll be first in line for API keys.
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