On-Device AI Training
Enable secure, controlled AI adaptation directly at the edge—without cloud dependency, data exfiltration, or loss of operational control.
Learning where it matters
Tavri’s on-device training enables adaptation in environments where connectivity, latency, or policy prohibit cloud-based retraining.
Local adaptation at the edge
Models adapt using recent, environment-specific context without transmitting raw data off device.
Offline-capable operation
Training, evaluation, and validation continue even in air-gapped or disconnected environments.
Privacy-preserving workflows
Sensitive infrastructure data remains local, reducing exposure and simplifying regulatory compliance.
Controlled training authority
Retraining is gated by policy—never automatic promotion without validation.
Audit-ready learning records
Training events, inputs, and outcomes are logged for review, traceability, and incident analysis.
Why on-device training matters
In regulated and safety-critical environments, learning must be deliberate, observable, and reversible.
Reduced latency
Local learning reacts immediately to environmental changes.
Stronger compliance
Data residency and audit requirements are met by design.
Operational resilience
Systems continue improving even when disconnected.