RAG & Vector Infrastructure

Building robust Retrieval-Augmented Generation pipelines using modern vector databases and semantic search. We reduce hallucinations to near zero by grounding every response in your data.

Model Context Protocol (MCP)

Designing agentic workflows where LLMs securely interact with your internal APIs and external data sources. Standardized, observable, and safe to run in production.

LLM Fine-Tuning & Deployment

Domain-adaptive fine-tuning of open-source models (Llama, Mistral, Qwen) on your proprietary data, deployed on your own infrastructure for full data privacy and cost control.

AI Observability

Monitoring model drift, token costs, latency, and hallucination rates in production. We bring DevOps discipline to your ML lifecycle so you know when something breaks before your users do.

AI Agent Architecture

Multi-agent systems, tool-use patterns, and autonomous workflows that are observable, debuggable, and safe. We design agent architectures you can actually trust in production.

AI Integration & Copilots

Embed AI into your existing product — chatbots, copilots, content generation, classification, and semantic search. Seamless integration with your current stack, no rip-and-replace required.

Our Stack

Tools We Work With

PyTorchHugging FaceLangChainLlamaIndexPineconeWeaviatevLLMOllamaCloudflare Workers AIOpenAI APIModalReplicate
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Build Your AI Stack

Tell us about your AI use case. We'll tell you how to make it reliable, scalable, and cost-effective.

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