Hardware · AI Delivery
A founding team with no software experience, to a working MVP and two pilots.
Time to MVP7 weeks
Context
Two founders with strong backgrounds in hardware distribution and B2B sales spotted an opportunity to optimize energy consumption for data centers. What they didn't have was any in-house ability to build enterprise software or do the data science needed to test the idea — so the hypothesis sat unproven.
The problem
- 01No internal expertise in building enterprise applications.
- 02No data-science capability to validate whether the optimization approach would actually work.
- 03Without a working artifact, the founders couldn't approach the market or prove the concept to prospective customers.
What we did
- 01Built a forecasting algorithm in Python on a time-series model.
- 02Delivered a lightweight web app as the working interface.
- 03Wrote an ACPI power-state control module in C++ to act on the optimization in the real environment.
Results
- 01MVP ready in 7 weeks.
- 02The team took it to market and secured two pilot projects with leading data centers — turning an untested hypothesis into commercial traction.