TrinityBMSgrid

Fully customizable and driven by selected KPIs, TrinityBMSgrid unlocks more revenue per installed megawatt, increases uptime, and reduces operational risk.

Solution

When Batteries Run as Assets, Adding More Energy Isn’t the Trophy.
Efficiency is!

TrinityBMSgrid brings Cognivity’s adaptive AI to battery energy storage systems, enabling them to learn from real-world use, optimize themselves in real time, and evolve to meet dynamic grid demands.

By minimizing energy losses, extending system lifetime, and improving charge/discharge control, TrinityBMSgrid unlocks higher operational efficiency and revenue per installed megawatt.

The result: smarter storage, greater profitability, and lower total cost of ownership, with full data privacy and edge autonomy built in.

Operational and Technical Barriers in BESS Deployment

Monitoring & Integration

  • Many energy storage systems still use legacy software

  • Inaccurate estimates and limited diagnostics hinder performance

  • Conservative operation leads to lost revenue and inefficiencies

  • Increases operational risk for both operators and insurers

Technical Complexity

  • Battery systems differ in chemistry, architecture, and application

  • Most software lacks dynamic adaptation to these differences

  • Results in compromised safety, lower efficiency, and reduced ROI

Different use cases

  • BESS operators must handle multiple grid services in parallel

  • Services include frequency regulation, arbitrage, voltage support, peak shaving, and black start

  • Requires software that is both flexible and precise across diverse, dynamic use cases

TrinityBMSgrid AI SW Stack

We develop a hierarchical, cloud-supported (but not cloud-dependent) AI software stack consisting of three synergistic layers — enabling deep personalization at the edge and continuous generalization across the fleet.

  • Local AI runs on each BESS unit, enabling real‑time, site‑specific control based on local grid conditions and battery health.
  • Shared insights improve coordination between storage assets across the site, without exposing any raw operational data.
  • Fleet‑wide learning continuously refines the software, pushing updates to every unit to boost efficiency, uptime, and revenue.

Key Benefits

Protects revenue by improving
accuracy and reliability

Reduces downtime with remote
diagnostics and optimization

Extends lifetime through smarter
control strategies

Cuts costs by minimizing cloud
and lab needs

Scales securely with
decentralized intelligence