LLM Integration Development
ChatGPT, Claude, and custom models in your product - wired into your workflows with production-grade reliability, not just a demo API call.
Trusted by companies that ship production software on deadline
Everything you need, nothing you don't
We scope each engagement precisely so you get senior-level work on the capabilities that matter.
GPT/Claude API integration
Secure, rate-limited connections to OpenAI, Anthropic, and open-source models - with fallback routing and cost controls built in.
Prompt engineering
Structured prompts, system instructions, and few-shot examples tuned for your domain - so outputs stay consistent and on-brand.
RAG pipelines
Retrieval-augmented generation that grounds answers in your documents, wikis, and databases - reducing hallucinations in production.
Fine-tuning
Custom model training on your data for specialized tasks - classification, extraction, and tone that off-the-shelf models can't match.
Embedding search
Semantic search over your content with vector stores - so users find relevant context before the LLM even generates a response.
Content moderation
Safety filters, PII detection, and output guardrails - so AI-generated content meets your compliance and brand standards.
From API key to production LLM feature
We start with your use case and data, then build integrations that handle latency, cost, and safety at scale.
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Week 1: Use case & architecture
We map your workflows, choose the right models, and design RAG or fine-tuning strategy - with latency and cost estimates.
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Weeks 2-6: Build & iterate
API integration, prompt tuning, and retrieval pipelines ship incrementally - each sprint ends with a testable feature in your product.
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Launch: Monitoring & optimization
We add observability, caching, and fallback logic - plus documentation so your team can extend prompts and models confidently.
Renting is local, so search had to understand a place and a date range as one question rather than two filters. Mirimera built the marketplace and the software our suppliers run on, and because it is one system underneath, nothing has ever had to be kept in sync.
- Pablo
CEO, Big RentalsLLM stack we ship with
Production-proven tools for model APIs, retrieval, and serving - chosen for reliability, observability, and long-term maintainability.
- AI
OpenAI
GPT-4, embeddings, and fine-tuning APIs for the broadest capability and fastest iteration on generative features.
Anthropic
Claude models for long-context reasoning, safety-focused outputs, and enterprise-grade API reliability.
LangChain
Orchestration framework for chains, agents, and RAG pipelines with pluggable retrievers and model adapters.
- Pc
Pinecone
Managed vector database for semantic search and retrieval at scale - with low-latency similarity queries.
Python
The lingua franca of ML and AI - for data prep, model serving, and glue code between your app and LLM APIs.
FastAPI
High-performance async API layer for LLM endpoints, streaming responses, and webhook integrations.
Ready to integrate LLMs into your product?
Book a free 30-minute call. We'll discuss your use case, recommend the right models and architecture, and outline a realistic timeline.