We compare models such as GPT, Claude, Llama, and Mistral against your real tasks, measuring accuracy, speed, and cost to choose the right one and tune it for production.

Our LLM engineers for hire help you identify high-value AI use cases, choose between prompting, RAG, fine-tuning, or agents, and plan a realistic budget and rollout.

We build AI agents that plan multi-step tasks, call tools and APIs, and take actions such as booking, updating records, or filing tickets, with human approval where it matters.

Our team sets up embedding pipelines and vector databases such as Pinecone, Weaviate, and pgvector, the search layer that lets language models find the right information quickly.

We clean, deduplicate, label, and structure your documents and datasets carefully, because the quality of the data going in determines the quality of the answers coming out.

Hire LLM engineers who implement access controls, data encryption, PII redaction, and audit logging, keeping sensitive information protected at every step of your LLM application.

We deploy open-source models such as Llama and Mistral on your own cloud or on-premise servers using tools like vLLM, giving you full control over data, cost, and uptime.

Our team tracks accuracy, latency, token costs, and user feedback in production with tools like LangSmith and Langfuse, retuning prompts and models whenever quality starts to drift.