TrinityBMS^auto

Designed to meet the complex demands of electric mobility, TrinityBMS^auto adapts in real time on each vehicle — sharing only key insights for fleet-wide optimization while preserving privacy, minimizing bandwidth, and keeping every battery personalized.

Solution

  
  Where Batteries Learn, Adapt, and Evolve.

  With Every Drive!

TrinityBMS^auto is Cognivity’s AI software stack for intelligent, self‑learning battery systems in automotive environments. It brings adaptive intelligence directly onto each vehicle, enabling real‑time learning based on driving, climate, and terrain — without relying on constant cloud connectivity.

Rather than sharing raw data, only selected training insights are exchanged through a privacy‑aware coordination process. This allows systems with similar characteristics to benefit from shared learning, while maintaining personalization and data integrity.

TrinityBMSauto AI SW Stack

We develop a hierarchical, cloud-supported (but not cloud-dependent) AI software stack for electric mobility — consisting of three integrated layers that enable real-time adaptation on the vehicle, shared learning across similar battery types, and continuous fleet-wide improvement without sacrificing privacy or performance.

Local AI runs on each vehicle, enabling real-time, on-board optimization based on driving behavior, usage patterns, and battery condition.
Similar batteries are clustered across the fleet, enabling shared insights and coordination without exposing raw data.
Fleet-wide learning continuously improves the software, with updates delivered to each vehicle to enhance range, uptime, and battery lifetime.