Repeat entrepreneur working at the intersection of AI, fintech and consumer products. Co-founded Tipplr, one of India's fastest-growing ONDC food networks, and led its acquisition by GoKhana. Now building a portfolio of AI-first products under Nexus AI — all live, links below.
work
01 / askgogo
AskGogo
Your AI assistant inside WhatsApp — remembers, reminds, splits bills, reads documents, speaks your language.
India speaks in 22 scheduled languages, but most AI assistants only understand English. AskGogo was built on a simple premise: your assistant should live where you already are — WhatsApp — and speak the language you think in.
The product is a personal operating system inside a chat thread. Long-term memory means you tell it something once and it remembers. Voice notes in Kannada, Tamil, Telugu, Hindi and Bengali are transcribed and acted on. Bill splitting, document analysis and daily briefings all live in the same conversation.
The architecture is memory-first. Every interaction is stored, indexed and retrievable, so the assistant doesn't just respond — it builds a model of your preferences, deadlines, relationships and habits over time.
Outcomes
10+ Indian languages with native voice transcription
Long-term memory with contextual retrieval across conversations
Document analysis — PDFs, Word, Excel summarised and risk-flagged
Bill split and expense tracking from plain language in group chats
Two-way Google Calendar sync with natural-language event creation
India's honest credit card intelligence — real math, not marketing.
The credit card industry in India runs on marketing, not math. Banks advertise 5X rewards without mentioning the ₹500 cap, and lounge access without the spend threshold behind it. CreditIQ was built to cut through that.
Every number traces back to something real. We read each card's published rate card — base earn rate, category multipliers, caps, exclusions — and compute the true effective return from the terms rather than the copy.
Statement Truth lets you link a real statement and replace estimates with verified figures. Smart Card Match asks seven questions and recommends the card the math picks. The redemption optimiser shows what points are actually worth across transfer partners versus the catalogue.
Outcomes
Annual value rankings computed from published earn rules — no affiliate bias
Statement Truth: link a statement, replace estimates with verified spend
Smart Card Match: 7-question flow, zero credit pull
Redemption optimiser with cached fare data, date-stamped
Ask CIRA — instant card grading and recommendations
Government schemes, made findable — eligibility, documents and application tracking for Indian citizens.
India runs thousands of central and state welfare schemes. Most citizens who qualify never apply — they don't know the scheme exists, can't work out whether they're eligible, or can't assemble the paperwork it asks for. The barrier isn't the benefit, it's the distance to it.
SaralSetu closes that distance. A six-step eligibility check covers Karnataka and central schemes in English or Kannada, then walks the citizen through document preparation, application assistance and progress tracking — with a WhatsApp channel for people who will never fill in a web form.
The hardest design constraint was trust. A platform that helps with government paperwork gets mistaken for the government, so the product states on every page that it is an independent facilitator and that final eligibility and approval decisions rest with the relevant authority. Privacy policy, terms and a data-deletion route are written against the DPDP Act 2023.
Built and operated by SetuNexa Technologies — a separate company from my Nexus AI portfolio.
Outcomes
Six-step eligibility check across Karnataka and central schemes
English and Kannada throughout, toggled in one tap
WhatsApp assistance for citizens who won't use a web form
Application tracking across preparation, verification, assignment and submission
DPDP Act 2023 privacy policy, terms and data-deletion route
Mutual fund portfolio analytics — AI signals, tax harvesting and rebalancing in one view.
Most Indian investors have no idea what their portfolio is actually doing. A CAS statement arrives every month — a dense PDF with hundreds of transactions across AMCs — and there's no easy way to make sense of it.
Upload the statement and FolioKey parses it in your browser. No passwords, no OTPs, nothing leaves your machine. The engine computes real after-tax returns, surfaces concentration risk, finds tax-loss harvesting opportunities and proposes rebalancing trades that respect exit loads, lock-ins and LTCG brackets.
It came out of a personal frustration — 11 funds across 4 apps, with no way to tell whether I was diversified or just duplicated. The first version parsed a CAS in under 30 seconds. The current one runs a portfolio health score, goal-based planning and a chat that answers "should I exit this fund?" with the data behind it.
Outcomes
Portfolio parses in-browser with zero server-side storage
Tax-loss harvesting engine surfaces realisable savings per portfolio
AI-powered lending for HORECA — from underwriting to collections.
Hotels, restaurants and cafés are the backbone of Indian food commerce, and among the worst served by formal credit. Seasonality, daily settlements and informal bookkeeping make standard underwriting models fail.
Rasoi Capital's underwriting engine runs a six-factor credit model built for HORECA cash flow. It ingests POS data, GST filings, rental agreements and utility bills to build a risk profile traditional lenders can't see, and explains every decision in plain English.
The platform covers the full loan lifecycle: application intake, AI scoring, document vault, credit manager workflow, disbursement, active loan tracking with DPD buckets, a collections engine with field agent beats, EMI restructuring and legal notice tracking.
Outcomes
Six-factor credit scoring tailored to HORECA cash flow patterns
Risk narrative explaining every underwriting decision
Full lifecycle — application → disbursement → collections → legal
Portfolio analytics with live AUM, NPA rate and city breakdown
Collections engine with DPD dashboard and field agent assignment
Deal flow intelligence for financial institutions.
Debt VC firms, banks and NBFCs drown in deal flow. Hundreds of opportunities arrive every month through email, warm intros and broker networks, and most never get properly evaluated.
AURA structures, scores and tracks every opportunity from first touch to exit — ingesting memos, decks, financials and market data into one deal profile, with an underwriting workspace for versioned documents, checklists and approvals.
Built as white-label SaaS for institutions that want modern deal intelligence without building it themselves. Multi-tenant, API-first, designed against enterprise security and compliance requirements.
Outcomes
Deal scoring from unstructured input — decks, memos, financials
Unified pipeline from origination to portfolio management
Collaborative underwriting workspace with approval workflows
Portfolio monitoring with early warning signals
White-label, multi-tenant architecture
Enterprise SaaS · in stealth
07 / tipplr
Tipplr
One of India's fastest-growing ONDC food networks — acquired by GoKhana.
India's restaurant ecosystem was fragmented, delivery platforms were extracting 25–30% commissions, and small restaurants had no direct relationship with their customers. ONDC was the opening, and we built Tipplr to be the fastest mover on it.
In under a year we went from 300 to 2,000 daily orders in 30 days, delivered 500,000+ orders, onboarded 20,000+ restaurants across 10+ cities and grew revenue 350% in six months. The platform reached profitability and was acquired by GoKhana.
The stack was built for scale from day one — real-time order routing, dynamic pricing, inventory sync with restaurant POS systems, rider allocation, and a merchant dashboard that gave restaurants visibility they'd never had.
Outcomes
300 → 2,000 daily orders in 30 days
500,000+ orders delivered across India
20,000+ restaurants onboarded across 10+ cities
350% revenue growth in six months
Reached profitability, then acquired by GoKhana
Acquired by GoKhana
gallery
Other things I've built
Weekend builds, internal tools and landing pages. Some shipped, some scratched an itch.
timeline
The path here
Twenty-two years across enterprise and startups — technology, product, execution.
2021 — Present
Co-founder & CEO · Tipplr, then Nexus AI
Scaled Tipplr into one of India's leading ONDC food networks and led its acquisition by GoKhana. Now building AI-first products full-time — AskGogo, CreditIQ, FolioKey, Rasoi Capital, AURA.
2018 — 2021
Infrastructure Head · JCPenney Services India
Owned global infrastructure design and deployment for the retailer's India technology centre — network, data centre and unified communications across sites. Now Catalyst Brands India.
2015 — 2018
Lead Architect, Voice · Capita IT Enterprise Services
Lead UC architect on Cisco Collaboration engagements — architecture, statements of work and delivery for global clients across India and UK centres.
2011 — 2015
AVP, Voice Engineering · JPMorgan Chase
Carrier-grade voice architecture for global trading floors — HLD/LLD, capacity planning, SLA and monitoring design across cloud and on-premise.
2010 — 2011
Sr. Technology Analyst · Goldman Sachs
Unified communications infrastructure for the firm — Cisco IPCC, CUCM, CUC and CUCCX platforms.
2009 — 2010
Project Lead · Target
Project planning, systems design and deployment, cutover and operations — plus service improvement and team performance management.
2004 — 2008
Sr. Voice Consultant · Accenture
End-to-end voice infrastructure design, implementation and maintenance for contact centre operations.
2003 — 2005
Sr. Executive Engineer · Siemens
Installation and maintenance of HiPath EPABX, contact centre, voicemail and video conferencing systems. Where it started.
process
How I work
The systems behind the output. The case studies show what got built — this is how.
The shape of it
I don't build products as a series of features. I build them as loops — systems that pick up a problem, run it through a defined process, check their own output, and leave me with a decision instead of a draft. Every product on this site follows the same five pieces, arranged differently: problem identification, validation, build, measure, iterate.
The rule that makes it work: I don't put my own angle on a problem until I've listened to at least 20 users. The opinion is mine, but the insight comes from the market first.
Written standards, not repeated prompts
Everything I know how to do well gets written down as a skill, a playbook or a principle. Every feature spec, user interview script and metric dashboard follows a standard, and that standard doesn't drift.
When output gets rejected, the fix goes into the system
The highest-leverage pattern I've found: separate the builder from the reviewer. Same-context self-review misses what fresh-context review catches, every time. I apply it to code reviews, product decisions and my own writing.
One spine, many limbs
Notion is shared state — content calendar, ideas inbox, activity logs, specs. Linear holds the roadmap. Every week I snapshot live state to dated files nobody overwrites, which is what makes real week-over-week trends possible.
The loop closes in public
LinkedIn for reach, this site for depth. Every product that performs gets written up here in full — the honest numbers, the failures, the pivots. The loop only closes when the learning is shared.
What I look for in problems
High frequency of pain — daily beats monthly
Existing spend — people already paying for something worse
A structural tailwind — ONDC, AI adoption, digital India
A defensible data flywheel — every user makes it better for the next
Clear unit economics — a visible path to profitability
Stack & tools
Next.js, React, TypeScript on the front end
Supabase and PostgreSQL for data
Claude and OpenAI for AI features
Vercel for deployment
Linear for roadmap, Notion for docs, Figma for design
advisory
Where I can help
Building is easier with someone who has already hit the wall you're walking towards. I advise founders and product teams building AI products for India.
AI product development
Prototype to production. What to build versus buy, where a model genuinely beats a rule, and how to ship an AI feature people use on day thirty rather than day one. I've taken five products through this, so I know which parts are hard and which only look hard.
Fintech product strategy
Credit, lending and investment products under Indian regulation. What DPDP compliance actually costs to build, how to price honestly when every competitor is paid to rank, and where fintech trust is won — usually in the boring parts nobody demos.
Distribution: WhatsApp, ONDC, vernacular
The channels most founders treat as an afterthought and then bolt on badly. What worked scaling Tipplr on ONDC from 300 to 2,000 daily orders, what building AskGogo taught me about WhatsApp as a product surface, and why vernacular is a distribution decision rather than a localisation task.
Operating AI-native
Running a portfolio of products with AI doing most of the building. The systems that make it work, the failure modes that cost me weeks, and the places a human still has to sit in the loop. Honest about what breaks, not just what ships.
Practical notes on AI-native building, fintech product strategy, and what shipping actually teaches you.
about
A bit more
I started as a technology analyst. Then I found product. Then I found entrepreneurship. The arc isn't linear, but the through-line is: I like making things that move outcomes — and AI is the most leveraged way to do that right now.
For the last five years I've been co-founder and CEO of Tipplr, building one of India's leading ONDC-powered food commerce platforms. Before that I led voice architecture at Capita IT, was AVP of Voice Engineering at JPMorgan Chase, a Senior Technology Analyst at Goldman Sachs, and a Project Lead at Target. Twenty-two years across enterprise and startup, technology and product, execution and strategy.
Now I run my ventures the way I'd want to work — small surface area, high leverage, AI-first — and build things on the side I'd want to use myself. FolioKey, AskGogo, CreditIQ, Rasoi Capital, AURA. Each one solves a problem I personally hit. Each one is built to the same standard: real math, honest value, and an experience that respects your time.
I'm looking for founders, investors, operators and builders who care about the same things. If that's you, say hello.
contact
Say hello
Hiring, advising, investing, or just comparing notes on building with AI — all welcome.
Opens your mail app with the message ready to send.
AI-native builder with 22+ years shipping products end to end. I don't hand off specs — I close the gap between idea and shipped product. I've gone from technology analyst to production code, owned growth funnels, and taken 0→1 features to market. Since 2021 I build my own products full-time.
Claude and Cursor are my default environment. I find the problem, scope the solution, build it, and drive adoption.
Live work
AskGogo
askgogo.in — AI assistant inside WhatsApp, 10+ Indian languages, voice notes
CreditIQ
creditiq.app — Honest credit card intelligence, real math not marketing
FolioKey
foliokey.app — Mutual fund analytics with tax harvesting and rebalancing
