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Where YAS fits in the machine-economy stack.
YAS is the risk-intelligence layer for machines: it reads live telemetry, scores risk in context, and produces a verifiable record a licensed insurer can price off. Here is how that differs from adjacent categories — described fairly, on the facts.
Data intelligence & analytics
YAS vs Palantir
Palantir builds general-purpose data integration and analytics platforms (Foundry, Gotham, AIP) across many industries. YAS is a vertical risk-intelligence layer purpose-built for machine risk, with an insurance licence and carrier capacity behind it.
| Dimension | YAS | General analytics platform |
|---|---|---|
| Focus | Machine risk — EVs, AVs, robots, humanoids — scored on one scale | Horizontal data integration and analytics across sectors |
| Output | An AURA score (0–100) plus a verifiable risk record an insurer can price off | Dashboards, models and operational tooling built per deployment |
| Regulatory standing | HK-licensed MGA (FA2648); carrier co-sign on attestation | Software vendor; no insurance licence or capacity |
| Domain context | ODD Engine tags every event with road, weather, speed and density | Context modelled bespoke per customer engagement |
| Business model | Risk rail behind operators and insurers; behaviour-based cover | Enterprise software licensing and deployment services |
Direct-to-consumer insurance
YAS vs Lemonade
Lemonade is a consumer insurance carrier with an AI-driven direct-to-consumer experience. YAS is infrastructure: the risk-intelligence layer operators and insurers build on to make machines insurable. We do not sell consumer policies; we power the risk decision behind them.
| Dimension | YAS | D2C AI insurer |
|---|---|---|
| Customer | Fleet operators, robotics OEMs, insurers and reinsurers | Individual consumers buying personal lines |
| Risk signal | Live machine telemetry — ~100 factors, 17 safety parameters, in context | Application data, behavioural signals, claims history |
| Where it sits | The rail beneath operators and carriers (B2B2B) | The carrier and brand facing the end customer |
| Asset class | Machines: vehicles, robots, humanoids, industrial assets | Homes, renters, pets, life and motor for people |
| Provenance | Cryptographic, tamper-evident record; structural neutrality | Internal claims and pricing systems |
Usage-based motor scoring
YAS vs Traditional telematics & MGAs
Traditional telematics scores drivers; legacy MGAs price off static proxies. YAS reads behaviour in its true operating context, explains every score, and attests the record so an outside party can trust it — across any machine category, not just cars.
| Dimension | YAS | Traditional telematics / MGA |
|---|---|---|
| Pricing basis | Live behaviour, scored every trip, sub-200ms — insurer prices off it | Demographics and annual proxies; periodic telematics summaries |
| Context | ODD Engine: road, surface, weather, density tagged per event | Raw event counts, limited contextual weighting |
| Explainability | Every score shows which behaviours moved it | Often a black-box score or a simple event tally |
| Coverage scope | Cars, AVs, robots, humanoids, industrial — one scale | Primarily personal or fleet motor |
| Trust model | Tamper-evident provenance; operator cannot edit its own record | Operator-reported data; weaker third-party assurance |
See where YAS already runs.
Talk to us about scoring your fleet, robots or autonomous systems.