# Industrial data · Solutions · Dscvry

> Industrial data: real work by Dscvry. Chemicals: Safety data sheet extraction API deployed in three days; Energy services: Operational system with field-level evidence; Renewable energy: Figures traceable to meter-level data.

Source: https://dscvryai.com/solutions/industrial/

# Difficult technical records. Systems-ready data.

Engagement 03 · Renewable energy · India. Figures traceable to meter-level data.

The engagement.

Renewable energy India Safety classification Technical records Solar performance

## Safety classification.

Engagement 01 · Chemicals · Global. Safety data sheet extraction API deployed in three days.

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### The challenge

Safety data sheets had to be read and classified against safety rules.

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### What was built

Safety data sheet extraction and classification.

## What changed.

As reported at the end of the engagement. The client is not named.

**3 days** To deploy the safety data sheet extraction API

## Fifty years of technical records.

Engagement 02 · Energy services · Global. Operational system with field-level evidence.

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### The challenge

Fifty years of technical records that the operation still depends on.

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### What was built

An operational system with field-level evidence.

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### Where it stands

No figure has been published for this engagement, so none is shown.

## Solar performance intelligence.

Engagement 03 · Renewable energy · India. Figures traceable to meter-level data.

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### The challenge

Fragmented solar data made generation losses difficult to identify and act on.

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### What made it hard

Inverter, meter, weather and financial data had to be reconciled by hand to quantify underperformance and its financial impact.

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### What was built

Solar performance intelligence, monitored continuously.

## What changed.

As reported at the end of the engagement. The client is not named.

**15 minutes** Plant-level visibility

**Automatic** Losses identified, quantified and prioritised

**Meter level** Every reported figure traceable to meter-level data

## See the pattern in detail.

Illustrative worked examples of the same kind of problem, showing what the AI reads and what it gives back.

Is the supplier’s evidence complete?

### Supplier quality

Find missing or inconsistent evidence.

See how →
https://dscvryai.com/use-cases/supplier-quality/

What here isn’t safe?

### Safety checks

Flag what’s unsafe or incomplete.

See how →
https://dscvryai.com/use-cases/safety-checks/

What fails next?

### Equipment failure

Spot the patterns and warn what may fail next.

See how →
https://dscvryai.com/use-cases/equipment-failure/

## More real work.

Every engagement on one page, with its reported outcome or status.

[Production loss](https://dscvryai.com/solutions/manufacturing/) [Document operations](https://dscvryai.com/solutions/logistics/) [Financial control](https://dscvryai.com/solutions/finance/) [Legal intelligence](https://dscvryai.com/solutions/legal/) [Compliance](https://dscvryai.com/solutions/compliance/) [Engineering evidence](https://dscvryai.com/solutions/software-engineering/) [Sovereign operations](https://dscvryai.com/solutions/sovereign/) [Wildlife conservation](https://dscvryai.com/solutions/conservation/) [The full record](https://dscvryai.com/solutions/)

## 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 →](https://dscvryai.com/contact/)

**London**Discovery AI Limited · United Kingdom

**Hyderabad**ReDscvry Technology Private Limited · India

**Chennai**ReDscvry Technology Private Limited · India