One Principal Engineer leads it from the first call until your team has adopted the work and trusts it. Each step shows what it means for this engagement.
Step 01
Discovery Call
30 minutes with the Principal Engineer who would lead this engagement. Free, and no sales handoff.
Step 02
Direct Assessment
Hands-on assessment of your environment, with your team.
Clients' own words, shared with their permission. Some chose to name their company.
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Over the past two years Vizius has led three IPS AI data projects:
GenAI Image Extraction Pilot (2024-25): Image-to-Text engine converts poor quality metal nameplates into structured data; now live at one repair center, with roll-out to our other facilities in the near future.
Financial Intelligence Pilot (2024-25): analytics layer analyzes shop-level P&L, job-margin, by product, end-market and customer; early tests show sharp and broad insight potential.
Data-Normalization PoC (2025): auto-mapping data normalization PoC shows exciting potential to speed ERP integration for new acquisitions.
Across these efforts Vizius has combined an invaluable empathy for the end-user experience, a strong understanding of AI capabilities, solid project discipline and a security-aware approach.
Scott MelzerCIO, IPS
Ready when you are
Thirty minutes with the Principal Engineer who would lead the work. Pick a time on the spot, or email us.
A go or no-go recommendation with production costs
Who you'll work with
A Principal Engineer, not a salesperson
Likely lead: David Hyde-Volpe or Gabriel Johnson. You talk to the engineer who does the work on AI Proof of Concept.
Questions buyers ask
Does our data leave our environment?
We build in your environment with the model you approve whenever possible, and we agree data handling up front.
What if it does not work?
Then you found out for the price of a pilot, not a production rollout. Stopping is a valid outcome.
Can we ask questions of our data in plain English?
Yes. Natural-language access to ERP and financial data is a common pilot. It was formerly sold as Chat With Your Data.
More detail
Prove it on one real process in weeks, not in a slide deck. We scope a proof of concept, build it on your data inside your environment, and measure whether it pays back before you commit to production.
Scott MelzerCIO, IPS
