KnowledgeAdvanced Manufacturing
Decades of engineering know-how, available to every engineer, and never leaving the plant.
An international advanced manufacturing company in Singapore deployed the Fooyo AI Knowledge Base on an NVIDIA DGX Spark unit inside its own facility, turning thirty years of reports, drawings and procedures into answers any engineer can ask for.
The Challenge
The knowledge existed. It lived in people, not in a place anyone could reach.
Senior engineers held decades of process knowledge that had never been fully written down, and retirements were approaching. New hires took years to become productive because the answers they needed were scattered across reports, drawings, procedures and email threads. Teams at different sites solved the same problems independently. And the material was far too sensitive to send to a public cloud.
- Critical know-how concentrated in a few people close to retirement.
- Long ramp-up for new engineers, with no single place to ask.
- Confidential technical documents that could not leave the company’s network.
The Solution
A knowledge system in a box the company owns.
The company deployed the Fooyo AI Knowledge Base on premises, on an NVIDIA DGX Spark unit. The language model, the knowledge graph and the documents themselves all run on that box, so nothing leaves the building. Engineers ask questions in plain language, browse the knowledge map, and follow references from one document to the next.
Ingest everything
Scanned drawings, spreadsheets, slide decks, email threads and PDFs are parsed with their tables, references and relationships intact.Structure as a graph
Products, processes, machines, materials, incidents and authors become a connected map of what the company knows, linked back to the source passages.Answer with sources, respecting access
Every answer cites the documents it drew on, and every query is filtered by who is asking before the model reads a word.How it works
From a question to a cited answer, entirely on site.
The same path for every engineer, every question, on hardware the company owns.
Step 1
Ask
An engineer asks about a process, a machine, a past incident or a procedure.
Step 2
Connect
The knowledge graph links the question to related products, incidents, changes and the people involved, across documents written years apart.
Step 3
Answer
The on-site model composes a response with the source passages highlighted.
Step 4
Verify and explore
The engineer checks the original in one click and can browse outward from any node on the map.
Know-how that stays, and spreads.
Knowledge stays when people leave
Decades of experience are captured in a system that is searchable, browsable and owned by the company, not dependent on who is still in the building.New engineers productive sooner
A new hire can draw on the company’s full history from day one, with sources shown, instead of waiting for the one person who remembers.Teams learn from each other
What the process team learned last year is available to maintenance, quality and the plant next door, without anyone having to know whom to ask.Risk removed by design
No data egress, a model under the company’s control, predictable cost, and a knowledge graph that domain experts can inspect and correct.Read the full story
Developing a prudent AI knowledge base with NVIDIA DGX Spark in Singapore.
Why prudent AI in a box beats cloud AI for sensitive knowledge, what DGX Spark makes possible, and how a graph knowledge base structures and understands a company’s data better than a pile of text chunks.
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FAQs
Fooyo builds four production AI products: an AI Knowledge Base for instant, cited answers; Kakis, a marketing AI that generates branded short-form video; Fooyo Commerce®, an AI-powered storefront; and Smart Tourism, a platform for crowd intelligence, AI guides, and bookings.
Most Fooyo products go from kickoff to production in as little as six weeks — not the six-month timelines typical of enterprise AI builds.
Yes. Every deployment runs in your private cloud, not a shared public model — your data never trains someone else's AI, and every automated workflow includes human review gates.
We work across 12+ industries in 8 countries — retail, hospitality, tourism, education, media, transport, maritime and healthcare among them — for 150+ customers since 2014.
Yes. Every Fooyo product is built to plug into your existing stack — CRM, POS, CMS, and messaging channels — rather than force a rip-and-replace.
Yes. Our Singapore HQ runs AI research and development, our Chengdu branch handles development, and our Tokyo office covers business partnerships — so our products are built for Southeast Asia and ready for China, including WeChat Mini Programs.
We start with a 30-minute demo to match your use case to the right product, then move to a scoped pilot, private-cloud deployment, and ongoing operation — we build and run the product with you.
Consultancies hand you a report and a prototype. Fooyo builds and runs the product with you — production-grade, in your cloud, with human-in-the-loop oversight — so it actually ships and keeps working.
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