I work at the intersection of product judgment and AI systems: ambiguous problem spaces, human-AI interfaces, and decisions that need to be trustworthy, not just fast.
An AI-assisted workspace that helps finance teams investigate and resolve the small percentage of transactions that automated reconciliation cannot match — combining AI-generated explanations, evidence, and human review to reduce month-end closing time and improve accuracy.
An AI assistant that helps product managers generate hypotheses, prioritize experiments, define success metrics, and analyze results — making experimentation faster and more structured without requiring deep analytics expertise.
An AI-powered payroll operations platform that automates document processing, payroll validation, anomaly detection, and employee issue resolution — reducing manual effort while improving payroll accuracy and compliance.
An AI document processing system that extracts, validates, classifies, and structures information from business documents such as invoices, payslips, contracts, and IDs — transforming unstructured documents into reliable, searchable business data.
A citizen grievance management platform that enables people to report public issues while helping government officials prioritize, track, and resolve complaints efficiently — with AI assisting on categorization, routing, duplicate detection, and executive summaries.
Rajesh works across AI product strategy, systems design, and execution — mostly in the space where a model's output has to become someone's actual decision. His strongest work happens before the roadmap hardens: clarifying what the system should be confident about, identifying the few decisions that matter, and shaping the interface so people trust it enough to act.
On using interface structure to make trade-offs, confidence, and operational risk easier to see.
Takeaway — the interface itself is where trust or confusion actually gets decided, not the roadmap behind it.
A short note on why product taste is less about preference and more about knowing which constraints deserve respect.
Takeaway — taste isn't preference — it's knowing which constraints to protect.
How to make planning legible without pretending the future has already been solved.
Takeaway — a good roadmap shows what's decided and what isn't, instead of faking certainty everywhere.