5.10.23-Ecosystem-Engora

DAVID ANDERSON: Hi, everyone. I'm David from Engora. And we solve manufacturing supply chain problems with an AI that uniquely understands technical data, enabling the next generation of sourcing and design automation. We've all heard of these supply chain issues manufacturers are facing. In the next four minutes, I hope to show a lot of those problems could be solved, tomorrow, at no extra expense, because fundamentally they're not problems of product availability, but of product visibility.

We've seen companies that embrace this realization, and the AI tools that address it, have a distinct advantage over their competitors in getting to market and meeting customer needs. Manufacturers depend on industrial distributors to supply everything from the components and materials we turn into finished products to the tooling and equipment that keeps factories running. But 95% of distribution is small, local, specialized vendors who are hard to find in search.

Our sourcing process isn't nice and neat like this, it's more like this. As a consequence, manufacturers must either staff large procurement teams to manually search for parts, overpay significantly from large distributors, or suffer downtime and delays when they can't find the parts they need. Imagine how many delays could be avoided, how much money and time could be saved, how much more efficient our manufacturing could be, if you could instantly see the inventories of every nearby distributor and find the parts that meet your exact requirements.

So we built that. We built a unique machine learning pipeline that understands technical data, catalog data. This is a hard problem because we're dealing with lots of small heterogeneous data sets, and the results have to be accurate. We need to avoid the hallucinatory artifacts we see in pure large language models, like the GPT family. With this technology, we can aggregate catalogs, data sheets, vendor websites, and other sources, converting them into a standardized machine-readable format, building a living database of components and their capabilities.

Other companies have seen this problem and built their own solutions. But we're the first to automate this process end-to-end, letting us offer more results, better results, and faster results than anyone else. Let's make this concrete. We have a sleeve bearing. It has some properties, requirements we care about.

Maybe we need it to repair a machine or to finish a small batch production job. Suddenly it goes out of stock from our preferred vendor. This dot represents our one bearing from our one distributor. This network graph shows the thousands of alternative bearings available, just in our current database, just in the Boston area. Each dot is a bearing and the position roughly corresponds to their similarity.

And look at the spread of prices. The potential to save an order of magnitude, depending on your needs. Since this data is in a machine-readable format, you can instantly narrow it down to just those products that meet your exact requirements. You can respond to sourcing disruptions in seconds with confidence.

Since it's in a structured format, you can fold it back into the design process. You can consider supply chain robustness, price, and availability early in design, when it's easy to make changes, not just at the end. This opens a whole new world of generative design and design optimization.

It's kind of sci-fi. It's a trope to ask a computer to design some complex system. Think Tony Stark asking Jarvis to design the Iron Man suit. We can finally do that. We have the data on system components available in a format we can just feed into our existing optimization tools to synthesize complex designs, accelerating and eliminating errors from the design process.

It's not just bearings, of course. For example, we can do this on an end mill. This is a big deal, because if we're lacking tooling, our factories aren't running. Again, we see hundreds of alternatives, with a huge spread of prices and capabilities.

We're already working with companies from Fortune 500s to startups, to pilot all these capabilities, mostly in digital engineering and shop operations. If your company is involved in engineering design or manufacturing and you're interested in any of these process improvements now capable with our technology, from accelerated procurement and reduced downtime to generative design and design optimization, please stop by our booth. We're located near the door with the deserts, or email me. And thank you.