Practical AI should be explainable, auditable, and built into real workflows. We would rather ship one system a team trusts than ten demos nobody uses.
Operations first
We map the real workflow before proposing a model. The system has to fit how you actually work.
Explainable by default
Every decision the system makes can be traced, audited, and defended. No black boxes in regulated settings.
Built to be handed over
We leave you with operating models and training, not a dependency on us to keep the lights on.
Tarun Bulchandani
Tarun founded Arithim to close the gap between AI potential and operational reality. With a background spanning enterprise systems, SAP ECC environments, and regulated industry workflows, he builds AI that survives contact with real operations, where auditability, integration, and trust matter more than novelty.