Agentic control infrastructure

The control layer for AI agents navigating complex markets.

Deploy, monitor, govern, and improve business-critical AI agents — with policy enforcement, evaluation, and a system of record built into the core of your infrastructure, not bolted on.

Policy-gated execution Every action traced Human approval built in
Agentic workforce governance

Your agents watch the markets. We watch your agents.

We provide both — the agents and the governance infrastructure that makes them reliable. Embedded deep in your stack, not installed as a plugin: policy, evaluation, observability, and a record of every decision.

Finance· E-commerce· Operations· Enterprise automation
The control layer

Everything agents need to be trusted in production.

Most agent projects stall between demo and deployment. The missing piece is not model capability — it is control: policy, evaluation, observability, and accountability.

POLICY

Governed autonomy

Define what agents can do, when they need approval, and how actions are reviewed. Policy enforcement runs inside the agent loop — not around it.
EVALS

Evaluation-first deployment

Test agent behavior before production and keep measuring it after launch. Scenario suites, regression gates, and quality thresholds at every stage.
TRACES

Full-run observability

Trace decisions, tools, prompts, outputs, costs, failures, and human interventions across every agent run — down to the single tool call.
RECORD

A system of record for agents

Not a log — a system of record. Every decision, order, and approval your agents make is captured in a durable, queryable store. Attribution, replay, and audit come built in.
Inside an agent run

Every action checked, traced, and recorded.

Policy checks in the loopEvery proposed action is evaluated against codified limits before it executes — not reviewed after the fact.
Human approval where it mattersHigh-risk actions are held and routed to the right reviewer, without breaking the rest of the workflow.
A sealed audit trailWhen the run completes, the full decision record is written — attributable, reviewable, and durable.
Explore the platform
Architecture

The agent harness around every agent.

An agent reasons, acts on the market through a policy gate, and each observation closes the loop. We are the harness around it — observability tracing every action live, on an immutable system of record beneath. Fully autonomous workflows run inside sandboxed limits; human-in-the-loop workflows hold judgment calls for approval.

Fully autonomous
Agent harness
action
approved
observation
Observability
every action traced live
Human oversight
Supervises the workforce — not each decision
Agent
Reasons · plans · calls tools
Policy gatein bounds
Guardrails: limits · permissions
Market
Exchanges · platforms · storefronts
Agent
Reasons · plans · calls tools
Policy gatein bounds
Guardrails: limits · permissions
Human oversight
Supervises the workforce — not each decision
Market
Exchanges · platforms · storefronts
↻ observation returns to the agent
System of recordImmutable · replayable · audit-ready — the foundation beneath the harness
RUNS AUTONOMOUSLYExecution within limitsRebalancing & repricingBid & budget pacingMonitoring & surveillance
Flagship product · Finance

EigenTrader OS: the control layer, applied to trading.

Our flagship vertical product — both the control layer and the system of record for trading operations. Every order that reaches the broker is captured, attributed to its strategy, and replayable. It lives on its own site; explore it there.

Forward-deployed engineering

We embed. We don't bolt on.

Our engineers deploy into your infrastructure and solve the market problem at its core — pilot first, instrumented from day one, measured against real baselines.

01

Embed with your team

Our engineers deploy into your infrastructure — your data, your brokers, your APIs, your constraints — and map one high-value workflow at its core.
02

Instrument the loop

We wire in policy gates, traces, and evaluation suites around your agents, integrated with your existing stack.
03

Operate in production

Agents go live with monitoring, approval flows, and audit trails — and keep improving against measured baselines.

Deploy agents you can actually trust.

Start with a focused pilot around one high-value workflow. We help map the workflow, instrument the agent loop, define policies, and measure production readiness.