Flagship capability
Agentic Automation & Orchestration
Agents reason. Automations act. People decide. We build all three — and the orchestration layer that runs them as one governed process.
What we build
- AI agents that act, not just answer — they read documents and tickets, query your systems through APIs, tools and MCP servers, and carry a task to completion
- Agentic orchestration — long-running, multi-step processes where agents, deterministic automations and people each do the part they are best at
- Human-in-the-loop by design — agents propose, people approve: review queues, escalation paths and sign-off before anything irreversible
- Durable execution — retries, fast and slow lanes, heartbeats, idempotent state and stale-run cleanup, so a process survives a crash without doing anything twice
- Deterministic guardrails — validation gates and a second-model judge sit between an agent's output and the real world; what fails is held, not shipped
- Platform-neutral, API-first — agents, connectors and services built to sit alongside the automation platform you already run, and to cover what it does not reach
- Accelerators to start from — document intake, grounded support agents, guarded operations agents and agent evaluation gates, packaged as agentic solution accelerators
- Run-level observability — every run records its inputs, sources, model and prompt version, tool calls, approver and cost
How we build it
How an agentic process is put together
Six layers, every one of them something we have running in production.
01 · Reason
Agents
Models handle what rules cannot: unstructured documents, ambiguous requests, exceptions. Each agent gets a narrow job, its own tools and least-privilege credentials.
02 · Coordinate
Orchestration
A durable workflow owns the process end to end — sequencing agents, automations and approvals, pausing for a person and resuming without losing state.
03 · Act
Deterministic automation
Anything that can be a rule is a rule. API calls, scheduled jobs and UI automation do the repeatable work; the agent never improvises where code is enough.
04 · Decide
People in the loop
The agent proposes, a named person confirms. High-impact actions sit behind approval, role allowlists, rate limits and a kill switch.
05 · Verify
Guardrails
Deterministic gates check every output — schema, sources, banned actions — and a second model judges the rest. Failures are held for review, never served.
06 · Prove
Evidence
Each run leaves a record an auditor can follow: what came in, what the agent saw, which version decided, who approved. See controls-ready automation.
Proof · Industrial operations
An AI operator assistant that can propose a machine write — and never execute one alone
For an automated 36-axis industrial cutting line we built the operator and maintenance console around the motion controller. Its assistant answers in English and Spanish from 2,531 pages of drawings and drive manuals, citing the page. It reads the controller through tools and can propose a write — but execution requires a person confirming in the interface and then passes a kill switch, a role and plant-network allowlist, a rate limit and an audit log. Two deterministic gates run on every answer: one blocks anything that reads like bypassing an interlock or E-stop, the other blocks any cited parameter that does not exist in the manuals. The console was built ahead of commissioning and runs today against a test-bench controller.
Agentic automation at Data Subsystems
Agents, the orchestration that runs them, and the controls that make them auditable.
Flagship capability
Controls-Ready Automation · SOX, ITGC & ITAC
Engineered against IT general controls, with application controls and an evidence trail built into every workflow.
How we make it auditable →New
Agentic Solution Accelerators
Reusable building blocks extracted from systems we built and operate — a first automated process live in weeks.
See the accelerators →Have something that needs to ship?
Tell us what you're building. We'll tell you how we'd build it — and what it'll take.