LLM Applications
AI features that earn their place in your P&L.
Most AI features stall in the gap between a promising demo and a system the business can rely on. We build LLM applications, autonomous agents, and RAG pipelines that clear that gap, with the eval framework and MLOps infrastructure to keep them dependable in production.
01 · What we build
Six capabilities, one team.
We start with the business outcome you are after, then assemble the capabilities that get you there. The same senior engineers stay with you across model selection, RAG architecture, agent design, and eval infrastructure.
01 · Capability
Chat & Copilot Apps
Customer-facing assistants, internal copilots, and domain-specific chatbots with RAG, tool-calling, and eval frameworks baked in from day one.
02 · Capability
Autonomous Agents
Multi-step agents that plan, use tools, and complete goals without hand-holding. We architect the loop, the guardrails, and the observability.
03 · Capability
RAG Pipelines
Retrieval-augmented generation over your private knowledge: vector stores, chunking strategies, hybrid search, and continuous reranking.
04 · Capability
Fine-Tuning & Adapters
Domain adaptation via LoRA, QLoRA, and instruction fine-tuning. We build the training pipeline, run evals, and version every checkpoint.
05 · Capability
LLM API Integrations
OpenAI, Anthropic Claude, Google Gemini, and self-hosted Llama; we handle prompt engineering, token budgeting, and multi-model routing.
06 · Capability
Evaluation Frameworks
Custom eval suites measuring accuracy, factuality, latency, and safety. CI-integrated so regressions block deploys, not users.