Apprend turns the knowledge locked in logbooks and your best operators' heads into an AI system anyone can query from the press — in seconds, not hours of page-flipping.
Every plastics manufacturer knows these pain points. Most have accepted them as the cost of doing business. They don't have to be.
Your best process tech knows Press 12 runs hot after a weekend restart and that Mold 2642 needs a specific V/P tweak when cushion drops below 5.5. None of that is written anywhere a new hire can find it. When that technician retires — and the average skilled operator is 56 years old — decades of process knowledge vanish with them.
Operators check the last page of the logbook. Critical context from two shifts ago — let alone two months ago — is invisible. Corrective actions that worked get rediscovered through trial and error instead of looked up in seconds.
A new operator starting a shift doesn't know what happened during the last three startups on their press: what adjustments were made, what QA flagged, what parameter drift has been building. Without that context, mistakes repeat.
DHR records, process sheets, scrap logs — filled out inconsistently. Corrective actions happen but don't get documented. The gaps are invisible until an audit finds them, and by then it's expensive.
No 18-month integration project. No custom hardware. No process changes to get started.
Snap photos of handwritten pages at end of shift. Our vision AI reads them — not OCR, but true AI that understands arrows, shorthand, and spatial relationships.
Every entry is structured, indexed by press, mold, and defect type. Your handwriting becomes searchable institutional memory.
"What happened last shift?" "We're getting pinholes on cavities 3 and 7." Answers in seconds — synthesized from your actual history, not a generic playbook.
Each interaction, each upload, each corrective action adds to the knowledge base. The system gets more capable over time — autonomously.
Most manufacturing software is top-down: management buys it, operators resent it. Apprend is bottom-up — operators use it because it genuinely makes their job easier.
Not OCR — vision AI that understands handwritten process sheets, including arrows, slashes, shorthand, and spatial relationships that OCR would destroy. Your existing logbooks become searchable institutional memory without changing how anyone records information.
Not trained on injection molding textbooks — trained on YOUR presses, YOUR molds, YOUR operators. It knows that Press 85 runs 300 PSI above the process card as steady-state. That knowledge comes from your data and your people.
Standard iPads. Existing WiFi. Existing logbook format. You can be running in a week. No infrastructure project. No dedicated IT resources. No training cycle before the first shift uses it.
New analytical tools, new dashboard components, new report types — proposed by the AI, reviewed by management, deployed without custom development. Your digital assistant evolves to fit your operation, not the other way around.
Not a demo environment. Not a proof of concept. Running on actual factory floors with real operators, real logbooks, and real problems to solve.
Rare combination: industrial domain expertise and frontier AI research capability in the same founding team.
Industrial automation veteran from Copia Automation. Published AI researcher with two papers on arXiv. Speaker at PyTorch Conference in San Francisco. Selected for the S4 Conference from a global applicant pool. Combines deep industrial domain expertise with frontier AI research capability — has stood on factory floors and built the systems that run them.
LinkedIn →AI research background with Stanford. Architect of I3's knowledge graph engine. Leads the Penn State Behrend research partnership on sensor-to-knowledge integration. Built the full product from the ground up — shadowed operators and plant managers on the factory floor, designed the system based on what he observed, and got operators to voluntarily adopt it. Rare combination of technical depth and hands-on operational understanding.
LinkedIn →We're at the conference. Find us and say hi, or fill out this form and we'll reach out. No sales deck, no pressure — just a conversation about whether this solves a real problem for you.