T E K D E X

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TekDex is a technology-driven consulting and engineering company. We build agentic AI, cloud-native platforms and ServiceNow solutions for enterprises worldwide.

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AI & LLM Engineering

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AI Engineering

AI & LLM Engineering

Most LLM projects stall in the same place: the prototype answers beautifully on the demo questions and falls apart on the real ones. The gap is almost never the model — it is retrieval quality, chunking, evaluation and the plumbing around the call.

We build the unglamorous parts properly. Retrieval that returns the right passage and cites it. Chunking tuned to your documents rather than a default. Evaluation you can run in CI. Guardrails written so your risk and compliance people can actually read them.

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What You Get

What ships with every LLM feature we build.

  • Retrieval that cites its sources, so answers can be checked
  • An evaluation set run in CI — no shipping on impressions
  • Guardrails and refusal behaviour written in plain language

We are deliberately unromantic about model choice. The right model is the cheapest one that passes your evaluation set, and that answer changes every few months — so we build the switch in from the start rather than hard-wiring you to one provider.

Technical Questions, Answered

Usually not, and rarely first. Better retrieval, better prompts and a proper evaluation loop solve most of what people reach for fine-tuning to fix, at a fraction of the cost. When fine-tuning genuinely is the answer, we will say so.
Wherever you decide. We build in your cloud accounts by default, and can work entirely with models that offer no-retention terms or run inside your own boundary. The data path is documented before anything is built.
By grounding answers in retrieved passages and citing them, constraining output formats, and scoring for unsupported claims in the evaluation set. You cannot eliminate hallucination — you can make it visible and rare.
The cheapest one that passes your evaluation set. That is a real answer, not a dodge: without an evaluation set the question has no defensible answer, which is why we build the set first.