AI Agents & LLMs Built to Scale

ExtreemTek builds AI agents and agentic workflows, integrates large language models (LLMs) and chatbots into products, builds RAG and knowledge search on your own data, and develops custom machine learning and computer vision models. Every solution is built to run in production.

We work with the Claude API, the OpenAI API and open-source Llama models, using frameworks such as LangGraph, LangChain, CrewAI, LlamaIndex and n8n. For retrieval we use Pinecone, pgvector on PostgreSQL and Qdrant, and for custom models PyTorch, TensorFlow Lite and Hugging Face.

RAG (retrieval-augmented generation) connects a language model to your own documents and data, so its answers are based on your content instead of only its training data. A business needs RAG when it wants an AI assistant or search tool that answers accurately about its own products, policies or knowledge base.

Our AI delivery runs in four stages. First a discovery and data audit produces an AI use-case and data blueprint. Then prototype and model sprints deliver a working proof of concept. Next, evaluation and guardrails produce an accuracy and safety report. Finally we launch to production with monitored MLOps.

Examples include Clawleaf, a healthcare AI platform with agentic workflows that automate clinical and administrative work for hospitals and clinics, OCR and computer vision for document processing, and voice AI. Another is LinkedIn Finder, an AI people search tool that returns ranked LinkedIn profiles from a one-sentence description.

Schedule a discovery call or send your project details using the form on this page. Founder and CEO Aqeel Wahlah personally joins the first conversation to understand your goals and identify a practical next step.