Architecture recommendation
Assess existing models, private deployment options and operating constraints before selecting an approach.
Custom LLM Development
Build a language-model solution around your company’s knowledge, deployment needs and business tasks.
Book a ConsultationThe business need
General-purpose AI may lack reliable company context or the deployment controls a particular workflow requires.
What we deliver
Knowledge retrieval
Where appropriate, implement retrieval-augmented generation (RAG) so responses use approved source material.
Evaluation and tuning
Create task-specific evaluation examples; consider fine-tuning only when evidence supports it.
Our approach
Define the task and deployment requirements, assess source quality, compare a baseline with retrieval or tuning, and validate the selected solution before release.
What we measure
Retrieval relevance, grounded-answer quality, unsupported answers, latency and operating cost.
Frequently asked questions
Does this mean training a model from scratch?
Usually no. Many engagements adapt an existing model using retrieval, configuration or fine-tuning. Training from scratch is a different undertaking and is not assumed.
Related services
01
AI Strategy & Advisory
Choose where AI belongs in your business, and turn priorities into an actionable implementation roadmap.
02AI Implementation & Integration
Put AI to work inside your business tools, knowledge sources and everyday processes.
03AI Agents & Automation
Connect agents and business tools to move repeatable work forward with clear human control.
Let’s define the next stepTell us what you
Book a Consultation Tell us what you
want to improve.
Share your goals, current tools and the people involved. We’ll discuss the right scope.