DAISORO
Use cases

Exact-trim vehicle intelligence

The trim is where insurance risk becomes visible.

A raw VIN can stop too early. Daisoro builds source-backed vehicle evidence records around exact trim, ADAS, EV/battery, powertrain, GCC/import confidence, valuation context, and repair-relevant features.

Buyer-ready output, not a generic content page.

9-field

vehicle identity spine

446

source-traced fields per UAE trim

24

feature groups

source

evidence and certainty labels

Public-safe scope: illustrative fields, source-backed evidence, and configurable delivery. No private data, fake customer proof, complete-market claim, or public upload flow.

Buyer problem

What serious teams cannot reliably solve today.

01

Model-level enrichment can hide the exact features that affect underwriting, pricing, claims, and product decisions.

02

ADAS, EV/battery, package, source-region, and repair-context signals are often scattered across brochures, dealer pages, listings, and public references.

03

Teams need structured records that explain confidence instead of flattening uncertainty into a single unverified value.

Daisoro approach

Evidence-first intelligence, structured for data and AI workflows.

Daisoro separates observed facts, source-backed values, inferred values, and review states so buyers can scope usable output without unsupported coverage promises.

Build around the Vehicle Evidence Layer product: a normalized identity spine plus exact-trim and feature records.

Separate observed, source-backed, inferred, and needs-review fields so downstream teams can inspect confidence.

Preserve source references, captured dates, and QA state alongside machine-readable output.

Output shape

What the intelligence product can include.

Fields, evidence, and delivery formats are scoped around target markets, vehicles, channels, carriers, and the buyer workflow.

vehicle_spinemake / family / generation / year9-field normalized identity
trim_gradePremium Plusexact-trim resolution target
adas_availabilityAEB / lane keep / blind spotfeature status by trim
powertrain_varianthybrid AWDinsurance-relevant configuration
repair_contextsensor calibration flagclaims context input

CSV / JSON / schema

source-backed fields

buyer-defined workflow

9-field vehicle identity spine
exact trim resolution
ADAS/safety
EV/battery
powertrain
GCC/import
value/repair context
evidence labels
certainty labels

Workflow fit

How teams use it.

Delivery: CSV extract, JSON records, schema map, evidence pack, scoped cloud delivery, or buyer-defined pilot package depending on the workflow.

Underwriting feature enrichment before quote or renewal

Pricing support for trim, package, and powertrain differences

Claims triage with repair-relevant vehicle context

AI-ready vehicle records for product and analytics teams

Evidence and boundaries

Built for inspection before reliance.

Vehicle values are presented as marketplace-anchored context where scoped, not as transaction-price truth or official specifications.

Public brochure, dealer, marketplace, and specification references

Captured date, source tier, QA state, and conflict notes

Marketplace-anchored estimate context, not transaction-price truth

Commercial next step

Scope the evidence, output, and buyer workflow.

Pick a target country, vehicle segment, or insurer workflow. Daisoro can show the evidence shape and confidence model before a larger pilot.