We train industrial-grade vision models on photoreal synthetic data — then deploy them onto real production lines that catch defects no human, and no traditionally trained model, ever could.
Traditional defect-detection vision systems demand thousands of real-world failure images. On a well-run line, those failures barely happen — and when they do, they're rarely captured at the angle, lighting, or resolution a model needs.
Our synthetic-first pipeline generates millions of photoreal, physics-accurate defect samples — every crack, scratch, void, weld imperfection, contamination event, and miscalibration — across every lighting condition, sensor profile, and material variant your line will ever see.
We model your part, your line, and your sensor stack in a physics-accurate 3D environment — down to specular response and PBR material noise.
Procedural generators inject parameterized defects — controlled severity, distribution, and morphology — including the rare modes your real data will never contain.
Adversarial domain randomization closes the sim-to-real gap. Models trained 100% on synthetic deploy directly onto live cameras — no fine-tuning round-trip.
Compiled to your edge hardware — Jetson, Hailo, custom ASIC — with sub-3 ms inference per frame and on-device drift monitoring.
Cracks, scratches, dents, pits, corrosion, discoloration — across metal, polymer, glass, ceramic, composite.
Missing parts, misalignment, wrong components, fastener torque indicators — at line speed, every unit.
Porosity, undercut, lack of fusion, spatter, cold lap. Trained on 4M synthetic weld samples per geometry.
Solder joints, component placement, polarity, tombstoning, foreign-object detection, lifted leads.
Fill levels, foam, cap seating, leakage, contamination — for pharma, beverage, chemical lines.
On-device monitoring catches process drift before it becomes scrap. Auto-flags retraining triggers.
Body-in-white, paint, weld, final assembly.
Wafer inspection, packaging, lithography QA.
Steel, casting, forging, extrusion, additive.
Fill, seal, label, foreign object, contamination.
Composite layup, bonded joints, NDT augmentation.
Cell stack, electrode coating, module assembly.
We had spent two years trying to collect enough real defect data to train a model. Syntheia shipped a deployable system in eleven days — and it caught a porosity mode our QA team had never seen before in week one.
Our engineers scan your part, instrument your line, and capture sensor profiles. Bring CAD if you have it; we'll work without if you don't.
Your digital twin spawns. Defect generators are configured against your defect taxonomy. First million samples render overnight.
Models train on synthetic, then validate against any real samples you have. Domain randomization sweeps converge automatically.
Pilot deployment on one station. Live inference, drift monitoring, and a feedback loop into your existing MES.
Full line rollout. Syntheia is now catching defects, every cycle, on every unit. Your team owns the dashboard.
No procurement gymnastics. A 30-minute scoping call, then a fixed-fee pilot. If we don't beat your existing baseline, you don't pay.