KeploreAI delivers production‑ready AI systems that solve hard, real‑world problems in days rather than months, using its autonomous AI engineering engine, PhysMind. The platform accelerates machine‑learning development by up to 90% and is already deployed in manufacturing settings such as electronic component inspection, robot guidance, and adaptive assembly‑line vision, providing high‑throughput, low‑error detection that continuously adapts to changing factory conditions.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers often rely on custom‑built machine‑learning pipelines that require extensive data engineering, long development cycles, and frequent re‑training to keep up with changing production conditions. This leads to high costs, delayed defect detection, and unreliable robot guidance on the factory floor.
Solution
KeploreAI delivers production‑ready AI systems that address these manufacturing challenges in days rather than months by leveraging its autonomous PhysMind engineering engine. The platform automatically ingests sensor and image data, builds and validates perception models, and continuously adapts them to variations in lighting, tooling wear, and part geometry. Deployed solutions include high‑throughput visual inspection for magnetic component defects and robot‑vision guidance for pick‑insert‑align tasks, achieving up to 90% faster development compared with manual ML engineering. Systems operate with 99.97% uptime, process thousands of units per hour, and maintain low false‑positive rates while self‑adjusting to evolving factory conditions.
Target Audience
Primary customers are manufacturers of electronic components, automotive assemblies, and other high‑mix, high‑volume production lines that require reliable AI‑driven inspection and robot guidance.
Features
- Autonomous AI engineering engine (PhysMind) that automates data collection, model training, validation, and continuous adaptation
- Vision inspection module detecting surface flaws, flux‑pattern anomalies, and dimensional drift across multiple SKUs with 0.8% false‑positive rate at 62 fps
- Robot‑guidance solution integrating with FANUC robots for six‑degree‑of‑freedom pick, insert, and align operations with real‑time positional error correction
- Production‑grade reliability metrics: 99.97% system uptime and throughput of 2,847 units per hour
- Continuous learning loop that updates perception models as tooling wear, fixture drift, or lighting conditions change
- End‑to‑end deployment on actual factory lines (not pilots), with built‑in validation and handoff mechanisms