A clearer next move.
Helping students compare active opportunities and turn limited preparation time into an explainable, editable plan.

Hi, I’m Rishika.
Fourth-year AI Engineering student at SRM Institute of Science and Technology, Chennai.
It starts withProduct case studies, prototypes, and AI workflows.
Helping students compare active opportunities and turn limited preparation time into an explainable, editable plan.

A facts-only assistant concept for Groww: concise answers about selected HDFC schemes, backed by official sources and clear product boundaries.
A factual question, within a defined scope.
Keep the scheme and its source together.
Show the source and when it was checked.
Facts only · No investment advice
An approval-gated AI workflow that turns public ChatGPT reviews into product insights and a sourced support clarification.
500 public reviews in five batches.
Themes linked to supporting evidence.
Write a product log and an email draft.
Human-approved · Draft only
A trackable recovery case that connects pickup history, a customer dispute and a reasoned support decision.
Keep the original return and attempt history.
One case, with the explanation attached.
A reasoned decision or a new pickup.
Review first · No automatic approval
A transparent review flow for buyers whose device-exchange quote changes after doorstep inspection.
Make the revised value and final price impact clear.
Show each condition finding and its deduction.
Accept, dispute, or cancel without ambiguity.
Rules-based · Manual review for exceptions
Four independent projects and one illustrative concept study.
I’ve completed NextLeap’s Product Manager Fellowship, building my product thinking through live classes, practical assignments and mentor feedback.
About the fellowshipSystems thinking, business models, user research, jobs to be done and problem framing.
User journeys, prioritisation, UX foundations, wireframes and AI-assisted prototyping.
KPI trees, North Star metrics, product-market fit, funnel analysis, experimentation and SQL.
Client-server architecture, databases, APIs and system design for product decisions.
LLMs, prompt engineering, embeddings, retrieval-augmented generation and AI agents.
Failure modes, evaluation rubrics, golden datasets, A/B tests and quality–cost trade-offs.
I’m Rishika Sahu, an AI Engineering student and aspiring product manager. I enjoy turning research, user needs, and technical constraints into clear product decisions.
My work focuses on product discovery, prioritisation, AI workflows, and consumer experiences.
More about me