LLM integration services for products that ship.
We integrate GPT, Claude, Gemini, Llama and Mistral into your product and internal tools — with routing, caching, evals, observability and cost controls from day one.
LLM integration services embed large language models (like GPT, Claude, Gemini or Llama) into an existing product or internal system — covering prompt design, model routing, caching, observability, evals, security and cost optimization.
What we deliver with LLM Integration Services.
Summarize, draft, classify, search — embedded in your UX.
Pick the right model per request; fall back on errors.
Version-controlled prompts with evals and A/B tests.
Prompt, response and semantic caching; budget guardrails.
Traces, costs, latency and quality per prompt, per model.
Honest fit check.
A plain answer up front. We'd rather not sell you something you don't need.
- You want summarize / draft / classify inside an existing product
- You want routing across GPT, Claude, Gemini, and open models
- You want prompt versioning, evals, caching and observability
- You want a standalone chatbot — see AI Chatbot Development
- You need a custom ML model — see Machine Learning Solutions
- You won't expose any data — discuss on-prem routing first
Our stack, battle-tested.
Model routing by task
Starting from $700, depending on project scope and requirements.
What makes us different.
The people you meet in discovery stay involved through architecture, delivery and launch.
Metadata, schema, page performance and semantic markup are part of delivery, not a post-launch add-on.
Tradeoffs, integrations and scope changes are documented so your team can audit decisions later.
Repos, infra, analytics and documentation live in your accounts from the beginning.
Frequently asked questions
Depends on the task. We route — often Claude for writing, GPT for tool use, Llama local for privacy-sensitive, Gemini for long context.
Prompt + semantic cache, smaller models for easy tasks, budgets and rate limits, response truncation, batching where possible.
Zero-data-retention APIs, PII redaction pre-prompt, fully on-prem options with open models.
Cuibit LLM integration projects start from $700, depending on project scope and requirements. Adding a single AI feature to an existing product, a multi-model routing layer with caching and observability, and an on-prem LLM deployment are each scoped differently — written proposal after discovery.
Yes — multi-model routing is a core capability. We pick the right model per request based on task type, cost, latency and quality requirements, with automatic fallbacks on errors.
Prompts are version-controlled in code, tested against golden eval sets, and A/B tested in production. Prompt changes go through the same review process as code changes.
Related services.
Ready to start?
Tell us about your project. A senior strategist replies within one business day — with a written first take.