What We Integrate
Every Major LLM, Production-Ready
From OpenAI Assistants to on-premise Llama 4 — we integrate the right LLM for your use case, compliance requirements, and cost targets.
GPT-5.5 & OpenAI API Integration
Full OpenAI Assistants API, function calling, streaming, vision, embeddings, and fine-tuning pipeline setup for production applications.
Claude API Integration
Anthropic Claude Opus 4.7 integration with long-context document processing, complex reasoning chains, and enterprise-grade content policy configuration.
Google Gemini Integration
Gemini 3.1 Pro integration for multimodal applications, Google Workspace data connections, and real-time streaming responses.
Open Source LLM Deployment
Llama 4, Mistral, and Gemma 4 deployed via Ollama or vLLM on your private infrastructure — no data to third parties, HIPAA/SOC2 compliant.
RAG-Enhanced LLM Integration
LLM integrations powered by your enterprise data — connecting APIs, databases, and documents to any LLM via retrieval-augmented generation.
Multi-LLM Fallback Architecture
Production-grade LLM routing with automatic fallback (GPT-5.5 → Claude → Llama) — ensuring 99.9% uptime even during API outages.
Our Process
How We Ship LLM Integrations
Every integration is scoped, architected, and hardened before a line of integration code is written. No surprise scope creep, no API keys handed over blindly.
Production-Grade Only
We don't hand you a Python notebook and call it an integration. Every delivery includes middleware, error handling, cost controls, monitoring, and documentation.
01
Requirements & Model Selection
Define the exact business use case, data sources, compliance constraints, and success metrics. Select the right LLM (GPT-5.5, Claude, Gemini, or open-source) based on accuracy, cost, and latency.
02
Architecture & Security Design
Design the middleware layer, API authentication, context management strategy, rate limiting, and data flow — ensuring no PII leaks to third-party APIs without explicit controls.
03
Prompt Engineering & Evaluation
Build and test prompt templates, system instructions, and context injection strategies against your real data — measuring accuracy and hallucination rate before production.
04
Integration Build & Testing
Build the full integration layer with streaming, caching, fallback logic, retry handling, token cost tracking, and comprehensive test coverage for edge cases.
05
Deploy, Monitor & Optimise
Deploy to production with LLM observability (LangSmith, Helicone), cost dashboards, latency tracking, and a post-launch optimisation roadmap.
Technology Stack
LLM Integration Technologies We Use
LLM Providers
OpenAIAnthropicGoogleOllamavLLMHuggingFace
Frameworks
LangChainLlamaIndexLangGraphDSPyInstructor
Vector Stores
PineconeQdrantWeaviatepgvectorChroma
Observability
LangSmithHeliconeArizeWeights&Biases
Start Your LLM Integration
Book a Free Integration Architecture Call
Tell us what you need to connect. A senior AI engineer will review your stack, recommend the right LLM and integration approach, and give you a realistic delivery estimate — free, no obligation.
45-Minute Technical Call
With a senior AI engineer, not a sales rep
Model & Architecture Recommendation
Right LLM for your accuracy, cost & compliance requirements
Delivery Estimate in 24 Hours
Timeline, team size, and cost ballpark before you commit
What Happens Next
01
Discovery Call — 45-min session to map your existing stack, data sources, and compliance requirements
02
Integration Plan — LLM selection, middleware architecture, security design, and cost estimate delivered
03
Build Starts in 24h — First working integration module delivered within the first week of development
90-Day Warranty Included
Every LLM integration ships with a 90-day warranty. If anything we built breaks due to our code, we fix it at no cost — no questions asked.
Chat with our engineers nowTalk to an LLM Integration Engineer
// free 45-min call · no commitment
FAQ
Common Questions About LLM Integration
Everything you need to know. Can't find what you're looking for? Talk to us
We add LLM capabilities via API layer — connecting your existing software to OpenAI, Claude, or Gemini through a secure middleware service we build. This includes prompt engineering, context management, rate limiting, cost controls, streaming responses, and error handling. Integration typically takes 3–8 weeks depending on complexity.
GPT-5.5 excels at structured output, function calling, and broad knowledge tasks. Claude Opus 4.7 handles long documents and complex reasoning better. Open-source models (Llama 4, Mistral) keep data on-premise for compliance. Codioo selects the right model for your accuracy, cost, latency, and data privacy requirements.
A basic LLM integration (chatbot, document Q&A) starts at $15,000–$40,000. Complex integrations with RAG, multi-LLM routing, fine-tuning, and monitoring range from $40,000–$150,000+. Ongoing API costs depend on token usage — Codioo builds cost dashboards and usage controls to prevent bill shock.
Yes. For GDPR and HIPAA compliance, we build on-premise LLM systems using Llama 4 or Mistral deployed on your private cloud. No patient or personal data leaves your infrastructure. We also configure data retention policies, audit logging, and access controls for enterprise compliance requirements.
We implement multi-layer hallucination prevention: RAG with source citations (only answer from retrieved facts), confidence scoring with human escalation for low-confidence responses, output validation layers, and ground truth evaluation during development. Production systems include monitoring dashboards to track hallucination rates over time.
Ready to Integrate an LLM Into Your Product?
Book a free architecture call with a senior AI engineer. We'll scope the integration, recommend the right model, and give you a realistic delivery timeline — no sales pitch.