Agent Infrastructure

Autonomy you can supervise.

Agent Infrastructure is the runtime that makes autonomous agents safe to deploy in production-critical workflows. Capability scopes, sandboxed execution, step-level traces, and policy gates are first-class — not hooks bolted on after the fact.

▍ The product

What an operator sees.

Agent Trace — every model call, tool invocation, and policy decision in a single run, with arguments and results inspectable inline. Replay any prior run deterministically; branch from any step to test an alternative.

Agent Trace·run/AGT-2026-04-29-1041 · plant-ops · maintenance_coordinator

Awaiting human

STEPS4

TOOL CALLS2

POLICY HITS1 / 0

TOKENS1.4k

10:41:08.022MODELOK
plan(maintenance_window)
claude-edge-7b · 824 tok
10:41:08.401TOOLOK
outage_calendar.query
window=2026-04-30..05-02

10:41:08.612TOOLAPPROVE

outage_calendar.create_draft

asset=PUMP-44 · 6h

args

{ "asset": "PUMP-44", "window": "PT6H", "crew": "TEAM-3" }

result

{ "draft_id": "DR-44-04-30", "requires": ["shift-lead.approval"] }

10:41:08.822HUMANWAIT
operator.shift-lead.review
queued · expires in 09:48

Illustrative interface — values are design fixtures, not benchmarks

▍ The problem

Demoing an agent is easy. Running one against your production systems is not.

Most agent frameworks were designed in environments where the worst case is a wasted API call. In a critical environment the worst case is a misrouted shipment, a wrong dosage, or an unsanctioned trade. Agent Infrastructure starts from the assumption that every action is potentially regrettable — and engineers in pause, replay, override, and rollback as core primitives.

▍ Capabilities

What ships in the box.

Capability-scoped tools

Tools are declared with explicit scopes: which data they may read, which systems they may write, which roles may invoke them. Out-of-scope calls are refused at the runtime layer.

Sandboxed execution

Each agent runs in an isolated sandbox with deterministic resource limits, network egress controls, and customer-owned secrets brokering.

Step-level trace + replay

Every step — model call, tool invocation, branch — is recorded with full provenance. Any agent run can be paused, rewound, branched, or replayed deterministically.

Policy gates

A pluggable policy layer evaluates each proposed action against your rules. Allow, deny, or escalate to a human — with the rationale recorded.

Human-in-the-loop

First-class approval primitives: pause for review, route to role, capture override reasoning, then resume with full context preserved.

Rollback channel

For every destructive action an agent takes, the runtime maintains a structured undo path — wired into the target system where supported, journaled where it is not.

▍ Use in sector

Concrete deployments.

Reference scenarios — drawn from active design-partner conversations and prior operator engagements.

DEFENSE
Mission-planning agents that draft course-of-action options against current intelligence, with every tool call recorded and every recommendation routed through a human gate before exit.
ENERGY
Maintenance-coordination agents that schedule outages across regulated assets — proposing, but never executing, until the operator on shift approves.
HEALTHCARE
Documentation agents that draft clinical notes from operational telemetry, with every PHI access scoped and recorded for compliance review.
PUBLIC SECTOR
Casework triage agents in benefits administration, surfacing recommendations to caseworkers — with every escalation captured for due-process review.

Step-level provenance per run

Traced

Per-task isolation, no shared state

Sandboxed

Structured rollback channel

Reversible

Tools · data · roles

Capability-scoped

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Decision Intelligence

Edge Inference