Appinfinite

AI Integration & LLM Apps

We integrate LLMs (OpenAI, Anthropic, Gemini) into existing products with the same production bar as everything else we ship: cost controls, eval suites, fallback handling, and observability on what the model actually returns.

OpenAIAnthropicGeminiVector DBLangChain

A chatbot demo takes an afternoon. A feature that stays accurate, affordable, and safe under real usage takes engineering. We add LLM capabilities to existing products with the same production bar as everything else we ship.

That means retrieval scoped to your data, tool-calling against your real APIs, and an evaluation pipeline so quality is measured rather than eyeballed. We work with OpenAI, Anthropic, and Gemini, and design so you can switch providers.

Cost and latency get budgets enforced through caching and model fallbacks. Guardrails and observability sit on model output before it reaches users, which matters most in regulated domains like healthcare and finance.

What's included

  • RAG and tool-calling architecture scoped to your existing data and APIs
  • Prompt and eval pipeline so quality is measured, not eyeballed
  • Cost and latency budgets enforced with caching and model fallbacks
  • Guardrails and observability on model output before it reaches users

What changes in the codebase

balance.ts
export async function getBalance(userId: string) {
  const res = await fetch(`/api/legacy/balance/${userId}`);
  return res.json(); // no retry, no timeout, no typed shape
  const res = await client.balances.get(userId, {
    retry: 3, timeoutMs: 2000,
  });
  return BalanceSchema.parse(res);
}

Industries we build for

FAQ

AI Integration & LLM Apps FAQ

Straight answers before you get in touch.

Still have a question?

Ask the engineers directly. Typical reply time is one business day.

hello@appinfinite.orgStart a conversation
OpenAI, Anthropic, and Google Gemini, plus open-weight models where data residency requires it. We keep the integration provider-agnostic where practical.
We ground answers in your data with retrieval, constrain outputs with structured schemas, and run eval suites on every prompt or model change.
Yes. Most of our AI work is integration into live products, which usually starts with one narrow feature and measurable success criteria.

Need ai integration & llm apps?

Tell us the scope and stack — we'll tell you honestly whether we're the right fit.

Talk to us