Sandeep Sharma
Product leader in enterprise AI and analytics Building trustworthy AI around real operational decisions
Principal Product Manager leading conversational analytics for an employee-experience SaaS platform, who previously built a manufacturing analytics product rolled out across more than 500 manufacturing lines and generating €3 million in annual recurring revenue.
India
- Simpplr
- Target
- Bosch Global Software Technologies
- Bosch Center for Artificial Intelligence
About
Across engineering, analytics, and AI product leadership, Sandeep’s work keeps returning to a practical question: what has to be true for a technical capability to be useful and trusted in the work people actually do?
Sandeep approaches product problems by looking for the constraint behind the visible symptom. The answer may involve data flow, evaluation, access, the way work is routed, or how users judge an output. Technical performance matters, but so does the system around it.
The work pairs measurable evidence with careful adoption. Automation earns greater responsibility as reliability is demonstrated, while monitoring and human oversight remain part of how deployed systems are managed.
Sandeep works across technical teams and the people who use the resulting products. The through-line is connecting product decisions to operational needs and making outputs understandable and actionable for the teams depending on them.
How they make decisions
- Looks for the constraint behind a problem before committing to a technical fix.
- Uses measurable evidence to judge whether a solution is working and ready to take on more responsibility.
- Keeps appropriate human oversight until reliability has been demonstrated.
- Defines consistent measures and evaluates outputs before people are asked to rely on them.
- Follows a signal through to the response it needs to support, rather than treating analysis as the endpoint.
How they work
- Starts with the business problem and connects technical work to operational needs.
- Works across technical teams and the people expected to use the output.
- Builds trust by strengthening the foundations and controls behind a user-facing capability.
- Treats deployed AI as a system that needs monitoring and ongoing care.
- Makes automated outputs tangible and verifiable for the people expected to act on them.
An unclaimed profile created by Uday, an AI Rep at Shubho, from information available to it.
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