A North American specialty manufacturing company supports customers in highly regulated, technically complex markets. Customer service teams are expected to deliver fast, accurate answers around product specifications, safety data, compliance requirements, and prior issue resolution.
But the information powering those answers lived everywhere—email inboxes, PDFs, and institutional memory.
Customer inquiries were handled manually. Finding the right answer often meant searching past correspondence, reviewing multiple documents, or relying on a handful of experienced employees.
The result:
Leadership saw the potential for AI—but only if it could be implemented responsibly.
Rather than rushing into a production AI deployment, leadership wanted proof. This proof of concept was designed specifically for the Customer Service Representative (CSR) team, where accuracy and trust matter most.
Success meant:
The answer needed to come from a working system—not a demo or slide deck.
Red Hawk Technologies
Red Hawk Technologies partnered with the organization to design and deliver a secure, executive-facing AI chatbot proof of concept built on Microsoft Azure.
From day one, the goal was simple:
Build something real, useful, and trustworthy—while setting a foundation that could scale.
The mandate was clear:
No hype. No shortcuts.
Red Hawk implemented a Retrieval-Augmented Generation (RAG) architecture that allowed our client to safely “chat with its data”—and nothing else.
Ingest real enterprise data: MSDS documents, PDS files, and product specifications were processed using Azure AI Document Intelligence.
Index for relevance and precision: All extracted content was indexed and stored as vector data in a database for vector-based retrieval to ensure the most relevant information surfaced for every question.
Generate grounded answers only: Using Azure OpenAI, the chatbot generated natural-language responses strictly from retrieved internal data—ensuring consistency, accuracy, and traceability.
Deliver a practical user experience
Secure by design
Administrators were provided a dedicated portal to manage ingestion, configure data sources, tune prompts, and monitor system health—ensuring governance and oversight from day one
The result was a secure internal AI chatbot—similar in experience to ChatGPT, but trained exclusively on the companies data.
The proof of concept:
This was not a production rollout. It was a controlled enterprise AI proof of concept, intentionally scoped to validate value, security, and accuracy before scaling.
With the PoC complete, the client now has a validated foundation for:
Most importantly, leadership gained confidence—because they could see and use the solution themselves.
Red Hawk helps organizations validate what works, eliminate risk, and build solutions designed for production not presentations.
If you’re considering enterprise AI, especially in a regulated or data-sensitive environment, proof of concept isn’t optional.
It’s how confidence is earned.
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