DAISORO

Enterprise data intelligence

AI-ready market intelligence for decisions that cannot wait for manual research.

DAISORO builds hard-to-obtain, evidence-backed datasets for enterprise AI and commercial decision systems — starting with UAE vehicle and motor-insurance intelligence.

Evidence-backed records

AI-ready schemas

Cloud delivery

Fragmented signals become inspectable records.

record pipeline

Dealer

Brochure

Listing

Policy

Safety

TrimCapturedtrim_gradecapture 00:04
ADASStructuredadas_featuresevidence ref
PowertrainVersionedpowertrain_variantversioned
Import confidenceEvidence attachedgcc_import_confidenceqa: review
Quote roadmapScopedquote_outcomedesign partner

vh_84f3c2a9

ev_2026_0418

files / scoped api / cloud

Why now

AI decisions are limited by the data they can trust.

Enterprise models and agents only become useful when market data is structured, current, and tied to durable evidence references.

Models are available; usable market data is not.

Vehicle and insurance signals are fragmented across sources.

Underwriting, pricing, claims, and product teams need traceable facts.

Enterprise AI needs structured records, not screenshots and spreadsheets.

What DAISORO builds

From fragmented market signals to AI-ready datasets.

The missing data layer for enterprise AI decisions: market observations converted into structured, versioned, deliverable data products.

01

Market signal

02

Structured record

03

Evidence reference

04

Version history

05

Enterprise delivery

Dataset catalogue

A structured catalogue of enterprise data products.

Search and filter by industry, use case, dataset family, status, buyer role, and evidence type.

IndustryUse caseDataset familyStatusEvidence type
Open catalogue

Record anatomy

Every useful AI workflow starts with records it can inspect.

DAISORO records expose vehicle identity, source, channel, pricing, eligibility, version, evidence, and QA state so underwriting, pricing, claims, product, distribution, and data/AI workflows can reason over the data surface.

Fields an AI workflow can inspect.

vehicle_evidence_record
01record_id
02market
03make
04model_family
05generation
06model_year
07body_style
08trim_grade
09powertrain_variant
10adas_features
11ev_battery_signal
12gcc_import_confidence
13source_tier
14first_seen
15last_seen
16evidence_url
17evidence_archive_ref
18version_hash
19qa_confidence_state
record_idstringStable record identifier
vehicle_spine_idstringNormalized make/model/year/trim key
trim_gradestringObserved trim or grade label
adas_featuresarraySource-backed safety and ADAS signals
powertrain_variantstringEngine, drivetrain, EV, or battery signal
gcc_import_confidenceenumSource-region confidence state
evidence_refstringSource and archive reference

Solutions

Built for enterprise decision workflows.

DAISORO organizes datasets around recurring decision systems rather than one-off research tasks.

Delivery models

Delivered into the workflows your teams already use.

Start with sample structures, then scope repeatable delivery into analytics, data platform, or AI-agent workflows.

rail 01

CSV / Parquet / JSON

Batch files for analytics, modelling, and internal data platforms.

rail 02

Scoped API integration

Structured-record integration paths scoped before delivery for AI agents and application workflows.

rail 03

S3 / GCS / Azure Blob

Cloud push into the storage layer your teams already use.

Motion explainer

See how fragmented signals become structured data products.

A controlled product-motion surface shows the record lifecycle from public signal capture through schema normalization, evidence references, version state, and delivery.

Fragmented signals to structured records

Signal capture, schema normalization, evidence references, version history, and delivery in one product loop.

Transcript

DAISORO captures public market signals, structures them into stable records, attaches evidence references and version history, and delivers them as files, scoped API integrations, or cloud pushes.

Next step

Build the market data layer your AI systems are missing.

Scope a datasetReview sample fieldsMap delivery rails