Real work.
Real outcomes.

Eleven engagements. Ten industries. Every figure as reported.

Across industries.
Automotive Logistics Apparel Real estate Renewable energy

The record.

Real engagements, with the outcome or status each one reported. Clients are not named. Where no figure was reported, the status is shown instead of a number.

Industry / reachOperational problemReported outcome or statusMore
Logistics
India · global 3PL operator
40,000+ non-standard invoices and supporting documents per monthProcessing reduced from ~14 days to minutesDocument operations ↗
Automotive
India · global
Repeated preparation of production loss reports and management information~1,728 hours a year reclaimed; analysis from 3 days to ~7 secondsProduction loss ↗
Real estate
India
Regulated reporting across multiple assetsDelivery timeline reduced from ~2 years to ~3 monthsCompliance ↗
Apparel
South Asia · global
Order-book questions waiting for analysisAnswers in under 60 seconds, previously ~3 daysFinancial control ↗
Food services
Multiple countries
Policy review across national operations82% shorter review cycleLegal intelligence ↗
Energy services
Global
50 years of technical recordsOperational system with field-level evidenceIndustrial data ↗
Building products
North America
Conflicting commercial dataProof of concept progressed to enterprise rolloutFinancial control ↗
Chemicals
Global
Safety classification rulesSafety data sheet extraction API deployed in three daysIndustrial data ↗
Renewable energy
India
Asset performance disconnected from financial reportingFigures traceable to meter-level dataIndustrial data ↗
Capital programmes
United Kingdom
Fragmented project controlsAnswers linked to source recordsSummary only
Wildlife conservation
South Africa · Selati Game Reserve
Up to 15,000 camera-trap photos and videos a monthConcept proven; feasibility assessedWildlife conservation ↗

By kind of work.

Each page shows the engagements behind it, and illustrative use cases of the same pattern.

Bring us the work where wrong is expensive.

Start with the operational problem. We’ll work out the data, models and agents it needs, and where it should run.

Talk to us →
LondonDiscovery AI Limited · United Kingdom
HyderabadReDscvry Technology Private Limited · India
ChennaiReDscvry Technology Private Limited · India