Two problems worth solving first.
Both start from the same premise: you already own the data you need. It is fragmented across disconnected systems, buried in unstructured documents, and held in the heads of a handful of specialists.
Analytical Lab Reports
A custom parsing agent turns analytical lab reports from static PDFs into structured, queryable data - mapping Parameter → Test Method → Sample → Batch, the relationships standard RAG cannot hold.
"Which samples failed pH specification in the last 30 days?"Lab analysts · analytical chemists · QC/regulatory scientists · lab directors
Read the use case →Knowledge ManagementKnowledge Twin
Eliminates the single-point-of-failure specialist - the PhD chemist holding a decade of OEM account intelligence, or the plant veterans whose know-how was never written down.
"We’re getting hazy clear coat on Mercedes Obsidian Black - what causes this?"Technical service · global quality · plant engineering · CTO/IT
Read the use case →Intelligent Document Agent · scoped to quotingBill-of-Materials item extraction
The same document engine, pointed at quote requests: it finds the BOM inside each customer’s spec sheet, reads it cell by cell, and exports into your own quoting template.
"Which of these tables is the bill of materials?"Quoting and proposal teams · application engineering · sales operations
Read the use case →Intelligent Document Agent · scoped to the QC benchThermal paper to e-log
The same document engine, pointed at the bench: bench instruments print results on thermal paper. AI Intime captures each slip, reads it into the lab record with the analyst approving what ships, and keeps the slip image as a lasting copy.
"Is that a 3 or an 8 on the faded slip?"QC lab managers and analysts · QA and data integrity · lab IT
Read the use case →Analytical Lab Reports and Knowledge Twin are the only two canonical use cases. Everything narrower is a scoping of one of them - Bill-of-Materials Extraction is the document agent scoped to quoting, Thermal paper to e-log is the same agent scoped to the QC bench, the way a deployment might be Knowledge Twin, scoped to an engineering adhesives portfolio - not a separate product.
Wondering what to solve next? The AI ROI Map collates what manufacturing leaders asked us for - and where the return actually sits.
See it against your own data.
A discovery session is a working conversation about your lab reports, your tribal knowledge, and your sovereignty constraints - not a slide deck.
On-prem. Your data never leaves your boundary.