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Yesinfosolutions
AI engineering

LLM applications, integrated into production software.

Integrating OpenAI, Anthropic, Google and open-source or private models into production software.

An LLM application is not just an API call wrapped in a UI. It is a piece of production software with the same requirements as everything else you run: predictable latency, error handling, cost control, logging, and a plan for what happens when the model is wrong. We treat the model as one component in a larger system, not the system itself.

What this involves

Capabilities.

Model selection based on task, cost and latency, not defaulting to whichever is newest
Prompt and context engineering for consistent, reviewable output
Fallback and retry logic for model or provider outages
Cost monitoring and rate limiting built in from day one
Where it connects

Fits into what you already run.

Your existing backend and APIs
Authentication and access control already in place
Logging and observability tooling
Billing and usage tracking systems
How we approach it

Four steps, not a leap.

01

Define the task precisely

A vague task produces a vague, unreliable system regardless of the model behind it.

02

Prototype on real data

Test against your actual data early, not a clean sample set.

03

Add monitoring before scale

Logging and cost tracking go in before usage grows, not after something breaks.

04

Keep models swappable

Architect so a different model can replace the current one without a rewrite.

Let's talk

You bring the problem.We figure out the technology.

No sales pressure. We will first understand what you are trying to fix, then tell you honestly how we would approach it, including when the answer is simpler than you think.

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