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Tell us where your AI falls short.

The more concrete the better: which system, which questions it gets wrong, and how you currently judge whether an answer was good. We reply to every serious enquiry.

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Prefer not to use a form? Write to tal@sigmatorq.com.

Attachments are fine. Sample queries, a failing transcript, or an export of the documents you are retrieving over all help us answer usefully.

What happens next

  1. We read it and reply with what we would measure first.
  2. A 30 to 45 minute call to look at your actual failures.
  3. A short written scope: what we would baseline, and what it costs.

Good fits

Teams already running an LLM or search system in production who cannot say confidently how well it works, teams whose accuracy has quietly regressed without anyone being able to prove it, and teams that need a model trained or fine-tuned on their own domain data.

Include your stack if you can: model, vector database, roughly how many documents.

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