AI systems that answer your customers—and your own.

Every time a new supplier came in, no one really knew if that vendor was already in the system. The same company kept getting onboarded twice under slightly different names, creating duplicate payment risk and forcing procurement to reconcile records by hand. On a list of 80,000+ suppliers, catching a duplicate visually is impossible.

Built a live check that runs the moment a new supplier is submitted. It compares the new name and details against every existing vendor, catches variations that look different but mean the same company (“Acme Corp.” vs “ACME Corporation Ltd”), and either flags a likely match for review or triggers the vendor-invitation step automatically when nothing matches. Plugs directly into the tools procurement already uses.

Every new supplier now screened against 80,000+ existing records in under two seconds. Roughly 1 in 10 submissions turn out to be duplicates that would have slipped through before. The clean path is fully automated, so procurement only touches the requests that actually need judgment.

Everyone in the business had questions that needed answers from the company’s data. Only the data team could pull them. A simple question turned into a ticket, a ticket turned into a wait, and by the time the answer came back the moment had passed. Meanwhile the data team was drowning in requests instead of doing real engineering work.

Built a system that lets anyone type a question in plain English and get the answer straight from the company’s database. It understands the shape of the data, works out the right query behind the scenes, and returns results in seconds. Locked down so nothing can be accidentally broken — only safe, read-only questions get through. Runs inside the company’s own cloud so their data never leaves.

Operations, finance, and business leads now get their own answers in seconds instead of waiting days on a data-team ticket. The engineering team stopped being an ad-hoc query desk and got their focus back for real product work. Every unsafe query gets blocked before it reaches production.

On the factory floor, quality problems were only caught when someone eventually noticed them on a dashboard, sometimes days later. The information needed to spot issues early lived in three separate systems no one looked at together: work orders in one place, inventory in another, quality history in a third. By the time issues surfaced, the damage was already downstream.

Built a system that watches all three data sources continuously and pulls them into a single unified view. The moment something drifts out of spec, the right person gets a Microsoft Teams alert automatically — no dashboard-watching required. Plant leaders also got a simple exploration tool for asking questions about their operation directly, instead of waiting on a weekly report.

Quality issues that used to be caught days later now surface in minutes, straight in the Teams channel of the person who needs to act. Three previously disconnected systems now read as one operational picture. Plant teams shifted from reactive dashboard-checking to proactive alerts — which is where the actual cost savings live, because catching a bad batch early is worth vastly more than catching it late.