Task-specific evaluation
Compare quality, latency, cost, licence terms and deployment constraints against representative examples.
Models & Applied AI
The right intelligence for the task.
Evaluate models and engineer useful capabilities across language, voice, documents, images and prediction.
Discuss your AI projectSERVICE ILLUSTRATION · NOT A LIVE PRODUCT
Which AI capabilities and models fit this task?
What the engagement delivers.
Applied capabilities
Engineer prompts and context, extraction, classification, voice or vision pipelines. Predictive analytics depend on suitable historical data.
An improvement path
Use model routing, retrieval or fine-tuning when the evidence supports it. Record regression cases before changing a model.
ILLUSTRATIVE APPLICATION
Route documents by what they contain
Compare candidate models on a reviewed sample of incoming documents. Extract required fields, flag uncertain results and send them for review.
Connected to the right systems.
Foundation-model APIs and hosted open-weight models have different data flows, operating needs and licences. We make those differences explicit.
With the right controls.
Validate structured outputs, test known failure cases and define confidence or review rules appropriate to the task.
Where it runs.
How it stays useful.
Choose external APIs or hosted inference based on the task and constraints. Training a foundation model from scratch is not a routine starting point.
What shapes the scope?
Available examples, modalities, evaluation depth, throughput, latency and any fine-tuning work determine the scope.
Explore your requirementsDo we need our own model?
Usually the first step is evaluating existing models and a well-designed application. A proprietary foundation model is not a prerequisite.
When is fine-tuning useful?
When a measured behaviour gap and a suitable training dataset justify it. It is not a substitute for retrieving current company information.
What should AI do
for your business?
Tell us what you want to build, connect or improve.
We’ll help define the architecture, the delivery and what it takes to run it.