SV-24 / SERVICES
Large language model solutions, engineered for production
Getting an impressive LLM demo is easy. Getting a reliable, affordable, safe system into daily use is the hard part.
Getting an impressive LLM demo is easy. Getting a reliable, affordable, safe system into daily use is the hard part. It requires picking the right model, structuring data, testing rigorously and planning for cost, latency and change. We build LLM-powered features and products with production in mind from the start.
What’s included
- Use-case assessment and feasibility, including where an LLM is not the right tool
- Model selection across commercial and open-source options, balancing quality, cost, privacy and latency
- Prompt engineering, structured outputs and tool or function calling
- Retrieval-augmented generation with vector search, chunking and re-ranking
- Fine-tuning or adaptation where it demonstrably beats prompting
- Evaluation frameworks, regression tests and red-teaming for safety and reliability
- Observability, caching, cost controls and governance
Best for
Product teams adding AI features, businesses summarising or extracting from documents at scale, and organisations moving a prototype into production.
How we work
- Define the task and success measures. 2) Prototype and evaluate options. 3) Build the production pipeline. 4) Monitor, improve and control cost.
What you receive
Production LLM service, evaluation suite, prompt and configuration repository, monitoring and a cost model.
The result
A dependable AI capability that your team can trust and afford to run.
Frequently asked questions
Should we fine-tune a model?
Often prompting with good retrieval is enough. We test both and recommend fine-tuning only when the evidence supports it.
What about vendor lock-in?
We design abstraction layers where sensible, so you can change models as the market moves.