Watch your agents. Train them to be better.
Anomaly Detection
Our policy engine checks every action in-flight. Passes are executed, anomalies are flagged for human review, and dangerous actions are stopped cold.
Agent Deployed on Device
Overmind enables per-user fine-tuning loops that run entirely on-device. Each user's model shifts at the weight level based on their own behaviour, producing a truly personalised agent.
- Each user gets their own personal agent
- Reduced cloud inference costs at scale
- Privacy thorough architecture
Per-Customer Modelling
Overmind enables a per-customer model architecture where each agent is continuously fine-tuned on that customer's own data and behaviour. A model that has structurally learned a specific customer's patterns produces materially better outputs than a generic model, however well prompted.
- Accuracy improves as customer data accumulates
- Switching cost grows with every fine-tuning cycle
- Retention moat built into the model itself
Granular Clinical Decision Support
Overmind enables institutions to fine-tune down to the granularity that actually matters in clinical settings: specific specialities, patient demographics, local formularies, and institutional protocols. Each department or network gets an agent calibrated to their precise clinical context, with a supervision layer that flags outputs outside defined confidence thresholds for clinician review.
- Demographic and speciality-level fine-tuning
- Audit-ready explainability
- Institutional knowledge baked into the model
Edge Agents for Defence
Overmind enables pre-deployment specialisation on mission-specific data and a post-mission fine-tuning loop that compounds capability across successive deployments. Agents operate within defined behavioural boundaries throughout, producing the audit trail that defence procurement requires.
- Offline AI built for communications-denied environments
- Mission performance compounds across deployments
- Sovereign control of AI capabilities