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PH1 core capbility
YEARS EXPERIENCE
3 to 5 years
TYPICAL CLIENT
VP Product, Head of AI, Director of UX Research, CTO
NECESSARY TIMELINE
Less than 2 months
Our POV
Engineering evals measure output against test cases, which is necessary and not sufficient. What decides whether an AI product succeeds is what happens when a person with their own goal uses that output inside a real workflow.
Single-turn tests tell you a feature worked once. Multi-turn evaluation shows whether trust compounds or degrades across a sequence, which is where most AI products actually fail and where standard evaluation is most blind.
What We Do
Build evals from real tasks. The workflows your customers actually run, multi-turn, rather than isolated prompts chosen because they are easy to score.
Detect silent failure. Output that looks acceptable on a dashboard and is not delivering value — including inconsistency, where the same input returns different answers.
Hand over the pipeline. Eval sets and scoring built for your pipelines and documented, so your team keeps running them release over release.
What We'll Deliver
Multi-turn eval set built on real customer workflows
Silent failure documentation with severity and segment
Inconsistency analysis and its trust implications
Prioritised fix list ranked by what each failure costs
Eval sets and scoring delivered for your pipelines
A reusable framework your team runs on future releases
When This is Essential
An AI product is live and something is wrong that metrics cannot locate
Retention or churn signals diverge from activity dashboards
Before scaling an AI feature to a broader or less expert audience
Customer success is escalating trust issues analytics cannot see
Before a release that depends on consistent AI performance
Combine With These Services
Golden Dataset Research — define what a correct output is first
AI Failure Mode Research — find the failures that threaten the brand
AI Trust & Confidence Research — measure whether people rely on it
Part of AI Product Evaluation and Prototyping & Testing.
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Submissions