Industrial and Manufacturing Products

18 products · Average rating: 3.7/5 · 143 reviews

18 Industrial and Manufacturing products

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Draftaid

Industrial and Manufacturing

DraftAid is the world's first generative AI for CAD manufacturing drawings, akin to GitHub Copilot but for CAD. It drastically shortens drawing creation time, turning hours into seconds. Every product that is manufactured - from construction to aerospace, automotive, durable goods, and electronics, relies on drawings. Currently, engineers and designers painstakingly make these essential drawings manually. Draftaid streamlines this process saving teams millions in time and quality. The idea was born out of Abdullah's experience as a mechanical design team member, where he created thousands of drawings and longed for a more efficient process. Partnering with Tahsin, a neighbour with a PhD in AI, and Mohammed, a seasoned engineering VP with experience in construction software, they turned the dream into reality. Since their launch in August, DraftAid has engaged customers through targeted outreach and word-of-mouth, securing paid pilots with subsequent contracts valued at $150,000. Be a part of ushering in the new era of CAD designs!

4.2 (15)
Bucket Robotics

Bucket Robotics

Industrial and Manufacturing

Bucket Robotics is making defect detection faster, easier, and more deployable, starting with the 250M lbs of plastic wasted annually in U.S. manufacturing. Our platform turns CAD files into defect detectors. We generate synthetic, photorealistic training data to help factories catch flaws before they ship. No manual labeling, no real defects required. Our models deploy to edge hardware and integrate easily into existing automation stacks. We come from the self-driving world (Argo AI, Uber ATG, Stack AV), where we built reliable perception in high-noise, real-world environments. We're applying that experience to manufacturing: robust sensing, user-friendly interfaces, and fast iteration cycles. Manufacturers hesitate to adopt new sensing due to data concerns, integration risk, and poor UX. We’ve handled petabytes of regulated autonomy data, and built systems that earn trust. Legacy vendors like Keyence and FLIR offer hardware-centric tools with bloated pricing and outdated software. We’re building the opposite: flexible, modern tools that engineers want to use. Manufacturing is in the middle of a $700B automation wave across North America. Bucket Robotics is building the quality control infrastructure to match.

4.0 (14)
Navier AI

Navier AI

Industrial and Manufacturing

Navier AI is making CFD 1000x faster with their ML-based solver. Physics simulations, such as Computational Fluid Dynamics (CFD), are essential across many industries ranging from the design and analysis of aircraft, to weather prediction, to the development of medical devices. Today’s simulation tools use explicit numerical solvers for physical equations, such as the Naiver-Stokes equations. These solvers are complex to setup and can take ages to produce results. Navier AI is building 1000x faster simulations using physics-ML solvers. Navier AI's fast CFD platform will enable engineers to quickly explore design spaces and perform analysis-in-the-loop design optimization. They are lowering the barrier to entry for aerospace and mechanical engineers to create high performance designs.

3.8 (5)
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Mineflow

Industrial and Manufacturing

Mineflow is an AI platform for mineral exploration. We generate predictions for mineral deposit shapes and locations, empowering mining companies from initial exploration to advanced feasibility studies. Geologists need to know precisely where their deposits are because drilling is expensive. In early trials with a lithium mining company, we found that Mineflow predicts the shape of hard rock lithium deposits more than an order of magnitude more accurately than our competitors. Ryan received a BS in Artificial Intelligence from Carnegie Mellon's School of Computer Science where he helped teach both the grad-level Deep Learning course and the grad-level Search Engines course. He built ML models at Google in the Display Ads optimization org for 2 years and launched products that generated ~125m USD in ARR.

3.7 (11)