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Services

AI agents that are designed to be tested.

We help teams define agent goals, tools, failure modes, and human oversight — then build systems that can be measured before they scale.

Research-grade evaluationProduction-minded engineeringResponsible handover

Evidence note: This page describes capability and method. It does not claim completed client agent portfolios until verified case studies are approved.

Problems we address

Demo agents that break in production

Multi-step tools without evaluation or permission boundaries.

Unclear ownership

Nobody knows when an agent should escalate to a human.

Capabilities

Agent architecture

Tool schemas, memory boundaries, and escalation rules.

Evaluation harnesses

Scenario tests for reliability, not only happy-path demos.

Integration

Connect agents to existing APIs and workflows with least privilege.

How engagements typically run

01

Define tasks & risks

What the agent may and may not do.

02

Prototype under eval

Small tool set; measure failure modes.

03

Harden

Permissions, logging, and human-in-the-loop paths.

04

Deploy carefully

Limited rollout with monitoring.

Questions

Not yet as named client publications. Until approved case studies exist, we describe capabilities and evaluation practice — we do not invent client results.

Talk with us about ai agents.

Share constraints and goals — we will respond with a technical discovery path.

Built for accountable delivery

Clear scope. Technical evidence. A team that can ship.

We begin with the operating constraint, agree on what success looks like, and build a delivery path your technical and business teams can review.

01

Defined outcomes

Scope, constraints, milestones, and decision owners before build work starts.

02

Evidence at every stage

Evaluation plans, working artifacts, and reviewable technical decisions—not presentation-only progress.

03

Production handover

Integration, observability, documentation, and an operating path for the teams who own the result.