Arch Platform
From Data to Expert-Level Action Automatically
Anita Vithayathil, Director of Product at Arch Systems, explains why most pilots stall and the five stages every plant goes through on the journey to autonomy.
What AI can already do on the shop floor, why pilots stall, where AI should not be used, and four filters for your next project.
THE SPEAKER
Anita Vithayathil is Director of Product at Arch Systems, leading data and AI products for manufacturing. Earlier, she led product for Cisco’s pxGrid Cloud and built an ML document classifier at Capital One that won Most Innovative Solution. B.S. Electrical Engineering, University of Florida; MBA, Cornell University.
Measuring Impact
AI use is widespread. Impact is not.
of manufacturers use GenAI today, mostly for office documents and email
productivity gain for novice workers with AI assistance (experts: +14%)
Pilot teams clean data by hand in notebooks. IT, OT, and vendors each assume someone else keeps it running. Without state context, models raise false alarms and operators fall back on tribal knowledge. The fix is a data foundation, built one stage at a time.
Each system holds its own slice. People bridge every gap by hand.
Sources publish to one namespace. Signal arrives faster, still bare.
Context joins the data. Numbers mean the same on every line and site.
Root cause and correction move from reactive to proactive.
Operations stay in lockstep with demand.
Watch the full talk on demand.
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