Case Study
Enabling self installable smart energy storage
A clean energy innovator asked us to salvage a stalled build. We rebuilt the mobile and IoT software, added compliance features, and delivered a working system in six months.
About the client
A pioneering energy tech company building a consumer installable battery that avoids permits and rewiring. The team needed a partner to finish the software layer and prepare for pilots.
Related capabilities:
Summary
Scope: Mobile app, device management, compliance labeling, energy optimization.
Tech: Xamarin C#, Kaa IoT, cloud telemetry, BLE, pricing engines.
Challenge
- Prior vendor exited mid build and left an incomplete codebase.
- Compliance, safety, and labeling had to be baked into the flow.
- Energy pricing logic needed to drive charge and discharge.
- Hardware extras like speaker and lighting required app control.
Success meant turning a partial build into a field ready system without changing the industrial design or the install experience.
SequoiaAT solution
Mobile app overhaul
We redesigned the app in Xamarin and C# so users can track energy, set schedules, and manage devices with a clear UI.
Geotagging for compliance
We added geolocation based labeling so electricians and first responders can identify systems during emergencies.
Intelligent energy optimization
We implemented algorithms that respond to real time utility rates to reduce costs for end users.
IoT integration and device management
We used the Kaa IoT platform for remote monitoring, firmware updates, and diagnostics at scale.
See related services: Digital Transformation and Automation.
Impact
Faster market entry
From stalled to demo ready in under six months.
Lower deployment costs
Consumer install path and cloud tools cut onboarding effort.
Business growth
The platform helped secure commercial orders.
Investor confidence
Working demos supported a nine million dollar raise.
FAQ
How did you accelerate delivery?
We narrowed scope to core features, stabilized the codebase, and built a clean telemetry and update path so the team could iterate without risk.
Can the system adapt to new utilities?
Yes. Pricing engines run as data driven rules so regional changes do not require app releases.