Foundation Models & LLMs
Choosing and applying the right large language and foundation models — across providers and open-weight options — to power copilots, agents and AI features with the accuracy, cost and data control your business needs.
Where this fits in your AI stack
There is no single 'best' model — only the best fit for a given task, budget and risk profile, and the landscape shifts monthly across OpenAI, Anthropic, Google, Meta and the open-weight community. We stay vendor-neutral, benchmark on your data, and design a multi-model approach so you get the right accuracy and cost without locking yourself to one provider.
The right model for every job
Frequently asked questions
Which LLM should we use?
It depends on the task — reasoning, speed, cost, context length, data residency and safety all matter. We benchmark candidates on your own data and usually recommend a multi-model approach rather than betting on one.
Should we use open-weight models?
Open models (Llama, Mistral and others) can run in your own cloud for control, privacy and cost, and are excellent for many tasks. We help you weigh them against hosted frontier models per use case.
Can we switch models later without a rewrite?
Yes — we abstract the model behind a clean interface and routing layer, so you can swap or add models as the landscape evolves without re-engineering your application.