Practical AI deployments grounded in your own documents.
Business AI integration projects are the work that makes your existing systems more useful. We do not build foundation models. We deploy Azure OpenAI inside your tenant, grounded in your documents, with your security boundary and your compliance rules. No data leaves your Microsoft boundary. No prompt is used to train the base model.
Every AI engagement we run starts with a pilot, not a rollout. We pick one document set, one workflow, or one inbox. We measure the time saved before and after. If the pilot does not produce a measurable result, you have not committed to a full deployment. We have seen pilots fail, and we have walked away from them. That is a better outcome than a six-figure enterprise contract that no one uses.
A typical engagement covers document ingestion into Azure AI Search inside your tenant, retrieval-augmented generation so the model cites its sources, a human-in-the-loop approval step for anything customer-facing, prompt and response logging for audit, and a written acceptable use policy your team will actually follow.
Azure OpenAI on internal product and compliance documents. Estimator lookup time dropped from twenty minutes to two, with citations to the original PDF.
Read more →AI triage for a field-service helpdesk inbox. Pre-drafted tickets for human approval, dispatch time cut from two hours to forty minutes each morning.
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