Workflow design
Identify where AI can remove real friction, then connect models to the APIs, tools, and review steps the work requires.
02 — APPLIED AI
Move AI from promising demo to dependable workflow.
Design AI-assisted tools with evaluation, observable behavior, useful fallbacks, and human judgment built into the operating model.
Discuss this serviceWHAT WE CAN BUILD
Depth where the system needs it.
Each engagement is shaped around the operating reality of your product, team, and release process.
Evaluation harnesses
Create repeatable datasets, scoring rules, regression checks, and acceptance thresholds for model behavior.
AI-assisted testing
Apply models to test design, failure triage, trace analysis, and coverage discovery with deterministic checks around them.
Reliability controls
Add structured output, timeouts, retries, audit trails, monitoring, and human approval where the risk calls for it.
THE OUTCOME
An AI workflow the team can evaluate, observe, improve, and safely use—not a black box it has to trust on faith.
WHAT YOU LEAVE WITH
Working software and clear ownership.
The goal is a useful system your team understands—not an opaque handoff that creates another dependency.
- 01Opportunity and risk assessment
- 02Working AI-enabled workflow
- 03Evaluation dataset and regression suite
- 04API and tool integrations
- 05Observability, fallback, and review controls
RELEVANT TOOLKIT
PythonC#LLM APIsRESTStructured evaluationsCI/CDHuman reviewTelemetry