Energy
A regional demand forecast, ready every morning
Temperatures and regional consumption in a thermosensitivity model, refreshed every morning.
Use cases
Seven end-to-end scenarios, from source to result in production, on your infrastructure. Each one sets out the challenge, the steps, what you get, what stays with you and the capabilities it draws on from graal Data Platform and graal Agentic Platform — and each one can become your pilot.
Typical scenarios
Connectors, pipelines, lakehouse, notebooks, models, agents: every use case lists the capabilities it draws on, from the Data Platform, the Agentic Platform, or both.
Energy
Temperatures and regional consumption in a thermosensitivity model, refreshed every morning.
Industry
Anticipate failures from sensor data, and alert before downtime.
Public sector
Query your internal documents with a model hosted on your premises, and answers that cite their sources.
Insurance
Flag unusual cases and explain every score.
Research
Turn a notebook into a scheduled, governed and monitored job.
Cross-industry
Governed agents operate the Data Platform’s runs, with human approval before any write.
Cross-industry
Move from Saagie, Hadoop or a SaaS by bringing your Python and Spark jobs along.
Cross-industry
Agents prepare joiners and leavers; sensitive access waits for a human approval.
Method
A use case chosen with you, played on your data and in your infrastructure. Then you decide, on evidence.
Week 1
Scoping
One use case, written success criteria.
Weeks 2–3
Installation
graal installed on your infrastructure.
Weeks 4–7
The use case, end to end
On your data, with your teams.
Week 8
Review
Results, delivered code and decision.
One use case end to end, on your data, in your infrastructure, in 8 weeks.