GenTechCloud
Almost everyone has a Generative AI demo. Far fewer have Generative AI in production, delivering measurable value every day. The gap rarely comes down to the model itself — it comes down to the engineering and discipline around it.
Here's the work that turns an impressive prototype into a dependable solution your customers and teams rely on.
1. Ground the model in your data
A general model knows a lot about the world and nothing about your business. Retrieval-augmented generation (RAG) connects the model to your own content — documentation, tickets, policies, product data — so answers are specific, current, and traceable to a source.
Done well, retrieval is where most of the quality comes from. It needs clean data, sensible chunking, good embeddings, and a retrieval strategy tuned to how your users actually ask questions.
2. Measure quality before you trust it
If you can't measure it, you can't ship it responsibly. We build evaluation suites that score responses for accuracy, relevance, safety, and tone against real examples — so you can compare approaches objectively and catch regressions before users do.
- Golden datasets that reflect real user intent
- Automated scoring plus targeted human review
- Continuous evaluation as data and models change
3. Add guardrails and a human path
Production systems need boundaries: input and output filtering, PII handling, prompt-injection defenses, and clear fallbacks. For higher-stakes decisions, a human-in-the-loop step keeps people in control where it matters.
The goal isn't a model that's always right. It's a system that's safe, honest about uncertainty, and easy to oversee.
4. Run it like real infrastructure
Once live, you need observability into quality, latency, and cost; alerting when things drift; and a way to improve continuously. Treating GenAI as a living system — not a one-off project — is what keeps value compounding.
The short version
Pilots prove possibility. Production proves value. The bridge between them is retrieval, evaluation, guardrails, and operations — and that's exactly the work we specialize in.