I'm Ashutosh Suman — a Product Lead for UX & Web experience at Detect Technologies

I own the top of a B2B lead funnel at an industrial-AI company, officially titled Software Engineer. Before that I co-founded two ed-tech ventures and consulted for 20+ enterprise and e-commerce clients. I build AI products end-to-end — most recently DhanDost, architected so the language model never computes a number the user sees.

I decide from customer signal over internal opinion, and I’m specific about what my data does and doesn’t support.

Years Of Experience
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My Recent Work

DhanDost — AI Personal-Finance Decision Coach 0→1 · Solo product owner

An AI coach that connects real transaction data and helps Indian salaried professionals decide where the next rupee goes. Architected around one constraint: the LLM proposes strategy in words, deterministic code computes every rupee.

Finding a demand signal when the research failed — Detect Technologies · B2B discovery & influence

My buyer survey returned under 1% response. Triangulating behavioural data instead surfaced something bigger: demand was running 6x toward a different product than the one we were positioning.

Selling to the buyer by starting with the user — Uniquest · Go-to-market discovery

Institutional buyers weren’t sceptical of the programme — they were sceptical of the demand. So I inverted the motion: generate demonstrable student demand first, then approach the buyer carrying it as evidence.

Campus Connect — PRD and MVP

Coursework · Product Management & Agentic AI, Vishlesan i-HUB IIT Patna

A full product requirements document and working prototype for an AI study-group
matcher — problem statement, persona, user stories with acceptance criteria, user flow, technical requirements for MVP and scale, and launch KPIs. Built as a certification project, so the persona is constructed and the metrics are targets rather than results.

Experimentation over opinion

A/B test on a paid-traffic product page, CTA placement as the single variable — ~1,500 visitors per variant, conversion 9.8% → 14.2%. One variable, clean sample, shipped the winner.

Behaviour when intent isn't available

Surveys capture what people say. GA4, heatmaps and search capture what they do. When my survey underperformed, the behavioural stack became the primary instrument.

Constraints as product decisions

In DhanDost I removed the language model from the arithmetic path entirely. That cost capability and eliminated a class of user harm structurally rather than probabilistically.

Precision about evidence

Website-sourced leads grew ~28% year-over-year in GA4 while I owned site CRO. That’s lead growth, not a conversion lift, and traffic grew over the same window.