Overview
Who it is for
Energy companies, utilities, renewable developers, sustainability and ESG teams inside larger organizations, and the climate technology companies building products for them. The operations are measured, regulated, and increasingly audited, and much of the work still runs through spreadsheets: emission factors in one tab, activity data pasted from exports, a calculation that only one person understands, and a report that cannot be reproduced after the fact.
What we deliver
Systems whose numbers can be defended:
- Emissions calculation with versioned emission factors, reproducible methods, and a record of every input, so that any figure for any period can be regenerated and explained.
- Sensor and meter pipelines that collect, validate, deduplicate, fill gaps by explicit rules, and log what they did.
- Audit-ready reporting. Reports that show their work, structured for the frameworks and reviewers your team answers to, and reproducible on request.
- Automated workflows for data collection from suppliers, sites, and partners, replacing the quarterly email chase with a process that has a status and a paper trail.
- Operational dashboards for energy use, emissions, data completeness, and reporting progress, on one data model.
- Cloud architecture for the data platform, with infrastructure defined as code and costs attributable.
How the engagement runs
- Listen. A 60-minute call about what is reported, to whom, from which sources, and where the process depends on one person. A one-page scope within 48 hours.
- Discover. We trace one reported figure back through every spreadsheet and export to its sources, define the data model and the calculation method, and rebuild that figure reproducibly as a working prototype. The sprint ends with a data flow diagram, the model, a factor management approach, and a build plan.
- Build. Pipelines, calculation, and reporting land week by week, each reconciled against the existing figures until the team trusts the new ones more. Weekly demos use real data.
- Hand off. Your internal owner runs a reporting cycle with us tapering, then a 90-day standby.
Typical stack
Pipelines built as code on your cloud, a relational store for the data model, factors, and audit trail, a managed warehouse for reporting, and the BI or disclosure tool your team already uses. Streaming only where sensor volume requires it; batch for everything reviewed monthly or quarterly. Infrastructure is defined as code so environments can be rebuilt and every change is reviewed.
Common starting points
The requests we hear most in this sector are an emissions figure that can be reproduced, a sensor pipeline that does not silently drop data, a supplier data collection that is a process instead of an email thread, and a report that is ready for assurance without a month of preparation. Each is a fixed-scope, fixed-term engagement with a named lead and an internal owner at the end.
The services that come up most in climate and energy are workflow automation, dashboards and analytics, and cloud architecture.