By Challenge
LLM features that ship to production — proper prompt engineering, cost monitoring, fallback paths, and an eval suite that catches regressions.
Everyone's talking about AI. You need it in your product before competitors do, but you've heard horror stories — $50K/month OpenAI bills, hallucinations breaking customer trust, prompts that work in demo and fail in production. You don't want to bolt on a half-broken ChatGPT clone.
What it actually looks like to work with us on this.
AI feature scoping — separate the useful from the gimmick
Model selection (Claude / GPT-4 / open-source) based on cost + capability
Caching + token budget controls so costs stay predictable
Prompt engineering with an eval suite (changes do not silently regress)
Streaming responses + retry logic for production reliability
Fallback paths when the LLM is down or slow
The capabilities behind this solution.
We build AI-powered features into web applications — chatbots, intelligent search, content generation, document processing, recommendation engines — using OpenAI, Claude, Gemini, or open-source models.
We integrate OpenAI, Claude, Gemini, and other AI APIs into your existing applications — with proper error handling, cost controls, caching, and fallback strategies.
Custom AI chatbots and virtual assistants that actually understand context, handle complex queries, and escalate to humans when they should — not glorified FAQ pages.
Tell us where you are and what you are trying to achieve. We will tell you honestly if we are the right fit.