Product & Tech
Seb
NVIDIA's open "Physical AI Data Factory Blueprint" — a reference architecture that unifies how physical-world training data is generated, augmented and evaluated, already adopted by Uber, Azure, FieldAI and others
Read: NVIDIA is codifying the "data factory" pattern one layer above capture — but its blueprint starts from synthetic/simulated data. Real-world operational capture (our layer) remains the scarce feed; borrow the vocabulary and position daXos as the logistics data factory's ground-truth input.
Last-mile tech in 2026 converges on one trajectory: agentic, AI-native, governed platforms that turn delivery from a logistics function into autonomous customer-facing infrastructure
Use: a vendor's own trend map concedes that agentic last-mile only works on governed, reconciled data. Mine the eight trends for roadmap language — especially "governed AI", which maps to our provenance/trust layer.
Samsara adds AI maintenance capabilities — repair-vs-replace decisions made from its own closed telemetry, the next workflow after last week's Agent Studio
Watch: the incumbent playbook is now visible — ship one AI-owned workflow per month, each usable only on Samsara data. Keep speccing the cross-vendor equivalent: same decision, mixed fleet, any telematics source.