Task & baseline
Define representative inputs, desired outputs, evaluation criteria, and an appropriate baseline.
Capabilities / AI Model Engineering
AI Model Engineering
Develop, adapt, evaluate, and deploy models around a defined task, authorized data, and a practical operating budget.
Engineering mandate
We deliver this capability through engagements tailored to your organization’s requirements.
Specialized intelligence. Deliberately engineered.
A specialized model is a means to a business outcome, not a default requirement. Data quality, task definition, baseline performance, deployment constraints, and the cost of training and operation determine whether adaptation is useful.
The first decision is whether the task calls for a conventional model, retrieval over existing knowledge, adaptation of an available model, or another approach. Training a foundation model from scratch requires a separate feasibility and commercial assessment.
Technical scope
The capability in detail.
- Custom machine learning and prediction models
- Domain adaptation and supervised fine-tuning
- Parameter-efficient fine-tuning
- Distillation, compression, and quantisation
- Training and inference pipeline engineering
- Model evaluation, benchmarking, and serving
Architecture considerations
How the pieces fit together.
Data & adaptation
Assess authorized datasets, quality, coverage, and the suitability of a training or adaptation route.
Evaluation & efficiency
Assess task performance alongside latency, compute, failure modes, and deployment requirements.
Serving & lifecycle
Plan versioning, model deployment, monitoring, and a controlled improvement process.
Concrete outputs
A scope you can evaluate.
Outputs, acceptance criteria, ownership, provider dependencies, and operating responsibilities are agreed in the statement of work.
- Task definition and data feasibility assessment
- Model adaptation or development plan
- Experiment and evaluation records within the agreed scope
- Serving pipeline and model lifecycle handover
Illustrative enterprise applications
Where this engineering can help.
Domain-specific classification and extraction
Application area to assess through discovery and a representative evaluation.
Task-specific prediction or language adaptation
Application area to assess through discovery and a representative evaluation.
Private model serving and inference optimization
Application area to assess through discovery and a representative evaluation.
Application examples describe intended uses, not completed customer engagements.
Explore your
engineering requirements.
Share your context, systems, and the capability you need to develop.