Specialized
AI Feature Implementation
An AI feature that ships with a measured accuracy number instead of a demo that impressed a meeting.
What this engagement is
The hard part of shipping an AI feature is not the model call — it's knowing whether the output is good enough to put in front of a customer, and knowing it again after the next prompt change. Teams that skip measurement end up with a feature whose quality is an impression, and impressions don't survive the first bad output a customer screenshots.
We build the evaluation set first, with your subject matter experts, from your real data and your definition of a correct answer. The feature — retrieval, prompting, orchestration — is then developed against that set, with scores reported weekly against a baseline. The accuracy bar is agreed before the build starts, and if the approach can't clear it, you hear that from us rather than from your users.
Production hardening is part of the engagement, not an afterthought: cost and latency budgets per request, fallback behavior for low-confidence outputs, and a defined path to human review where the stakes require it. The evaluation harness ships in your CI, so every future change to prompts or models is scored automatically after we're gone.
Who this is for
- Product teams with an approved AI feature and no evaluation practice
- Companies with a document-heavy process worth automating carefully
- Teams whose AI prototype impressed leadership and then stalled before production
What you get
- Production AI feature integrated into your product
- Evaluation set built from your data with scored baselines
- Automated evaluation running in CI on every change
- Cost and latency monitoring per request
- Fallback behavior and defined human review paths
Scope
Exactly what the quoted price covers
The scope document for this engagement lists both columns below in writing. Nothing moves between them without a conversation.
Included in the engagement
- Evaluation set built with your experts, plus a written accuracy bar
- The feature itself: retrieval, prompts, orchestration, guardrails
- CI evaluation harness scoring every future change against the baseline
- Cost, latency, and confidence monitoring with alerting
- Human review workflow for low-confidence or high-stakes outputs
Not included
- Training or fine-tuning a custom model — we build on proven hosted models
- Model provider costs (billed to your account directly)
- Features beyond the single agreed use case
Working together
What we need from you
Fixed dates only hold when both sides show up. These are the commitments we ask for in exchange for ours.
- 01
A subject matter expert for evaluation sessions — the person who knows a right answer when they see one
- 02
Representative real data, including the difficult cases
- 03
A product owner who can decide where the accuracy bar sits
Process
How it runs
- 01
Define correct
We build the evaluation set with your subject matter experts and agree the accuracy bar before writing the feature.
- 02
Build against evals
Retrieval, prompting, and orchestration developed with scores reported weekly against the baseline.
- 03
Production hardening
Cost controls, latency budgets, fallbacks, and human review paths for low-confidence outputs.
- 04
Handover
Evaluation harness in your CI so your team can keep measuring after we're gone.
Also in Specialized
Scope a ai feature implementation engagement.
Send us the situation in a few sentences. You'll get a scope, a price, and a date back — or an honest no.