Founder's Office, 10on10 Foods / Gurgaon and Bengaluru

Krishna Mistry

One city to sixteen in six weeks. I built the plumbing that made it hold.

One city to sixteen in six weeks. Most of that plumbing was code.

I work in the founder's office at 10on10 Foods, a stone milled flour brand in Bengaluru. I set up the order, transport, ERP and inventory systems behind the expansion, then took the North region supply chain and ran it across eight markets. Before this: Cityfurnish, Coop AI, and a company of my own.

I work in the founder's office at 10on10 Foods, a stone milled flour brand in Bengaluru. Engineer by training, so when a process breaks I usually end up writing the thing that fixes it. Python, SQL, ERP APIs, LLM and RAG workflows. Before this: Coop AI, an open source RAGOps framework, and a company of my own.

Write to me See the work

16 Cities live
from one, in six weeks

₹3L → ₹1.5Cr Monthly revenue
over the same stretch

8 Markets
North region, mine to run

40% Faster client decisions
Coop AI, automation layer

17× Compute scaled
GURU, NVIDIA H100 cluster

6 Systems in one stack
OMS, TMS, ERP, store, automation

Open to roles

Krishna Gaurishankar Mistry Gurgaon, IN

Work5 roles
2024 to now

Five places, one job description

Find the thing that is quietly breaking, fix it properly, then make sure nobody has to fix it again.

Apr 2026 → nowBengaluru
Full time

Founder's Office

10on10 Foods

D2C stone milled flour brand. Fresh to order, sold through quick commerce, marketplaces and our own store.

When I joined we sold in one city. The plan was sixteen. Nothing about the way orders, stock and money moved was going to survive that, so the first job was building something that would.

Stood up the stack behind the expansion: omnichannel OMS, TMS for transport, Odoo ERP for procurement and billing, Shopify, plus marketing and inventory automation on top.
Opened order capture in every new city across quick commerce, marketplaces and D2C, so a city could start selling the day it went live.
Took the North region supply chain. Onboarded the first vendor base and negotiated their rates, then owned raw material sourcing, purchase orders, inbound transport and dispatch across eight markets.
Sat in on partnership conversations with Country Delight and Blinkit Gourmet alongside the founder, and fed what came out of them back into sourcing calls.
Automated the Shopify catalogue work, the marketing workflows and the SEO, so listings and campaigns stopped eating a person's week.
Currently wiring Odoo to the omni commerce layer over API, so inventory, orders and accounting read from one place instead of three.

The stack behind sixteen citiesBuilt Apr to Jun 2026

Order
sources

Quick commerceBlinkit, Zepto, Instamart

MarketplacesThird party listings

D2CShopify, own store

Capture

Omnichannel OMSOne order queue for every city and every channel

Systems
of record

Odoo ERPProcurement, purchase orders, billing

Inventory automationStock position across the network

Movement

TMSInbound transport and dispatch

Marketing automationCatalogue, campaigns, SEO

In progress Odoo is being wired to the omni commerce layer over API, so inventory, orders and accounting stop being three separate versions of the truth.

Footprint 00 / 16

Origin Bengaluru, one city, one channel.
Week six sixteen cities capturing orders across every channel.

1 → 16Cities, six weeks

₹3L → ₹1.5CrMonthly revenue

8Markets on my desk

Aug → Sep 2025Remote
Internship

Founder's Office

Coop AI

AI legal workflow platform serving SMB and enterprise clients.

An AI platform selling into legal teams, with the operation still being put together by hand around every client. I set up how it ran, then took the manual parts out.

Built out operations for the platform. Client decision turnaround came down by 40%.
Built the automation layer on n8n, Relevance AI and AWS SageMaker, which turned deployments into something repeatable instead of bespoke every time.

40%Faster decisions

3Tools, one pipeline

Sep 2024 → Apr 2025Open source
Project lead

Project Lead

GURU

Enterprise grade open source RAGOps framework, built for low latency chatbot deployments.

An open source project that needed serious compute it did not have. Someone had to run the operational side of it and go get the hardware.

Directed the operational workflows for the framework, which was built for enterprise use and low latency chatbot deployments.
Pitched at an international AI forum and came away with NVIDIA H100 GPUs and enterprise infrastructure. Compute capacity went up 17×.
RAGOps in the real sense: retrieval, serving and the operational scaffolding around a framework other teams were going to run in production.

17×Compute scaled

H100Hardware secured

Oct 2025Gurgaon
Short engagement

Founder's Office

Cityfurnish

Rental first marketplace for furniture and appliances.

One month, one brief: go through the whole operation and come back with what is actually wrong, not what people assume is wrong.

Found that roughly 30% of KYC verification was still being done by hand, which is exactly where customers were dropping off. Proposed a three step flow to close the gap.
Traced the delivery delays back to procurement buffers rather than logistics, and brought in forecast driven inventory planning.

30%Of KYC still manual

2Root causes named

Nov 2024 → Mar 2025Pune
0 to 1

Founder

MyTribe

Event sponsorship marketplace. My own company.

The one where the buck stopped with me. Product, sales, vendors, staffing, and the logistics of getting large events to actually happen on the day.

Took it from nothing to a working platform. Go to market through partnerships, affiliate networks and outbound sales.
Ran sprint planning, and handled vendors, staffing and logistics for six plus large events. The biggest was a Holi festival with over 80,000 people through the gate.

0 → 1Platform built

80,000+Largest event

MethodHow I
actually work

Four things I keep coming back to

These are not principles I read somewhere. Each one cost me something to learn.

Go and look

Operating problems are rarely what they look like from a dashboard. The delivery delays at Cityfurnish read like a logistics problem for months. They were a procurement problem. You only find that by walking the process end to end and talking to whoever touches it.

Ship the ugly version first

A spreadsheet that works this week beats an ERP module that works next quarter. Half of what I built at 10on10 started as something crude that kept a city selling, and got rebuilt properly once we knew it survived contact with reality.

Twice, write it down. Three times, automate it

That rule is most of what the automation work at 10on10 and Coop AI really was. Nothing clever. Just refusing to let the same task get done by hand a fourth time.

Own the number, not the task

The North region was never a list of tasks. It was eight markets that had to have stock on the shelf. Framing it that way changes what you decide to do on a Tuesday, and it changes who you call when something slips.

ToolkitWhat I reach
for first

The operating side

Supply chain, commerce and the business fundamentals underneath both.

The building side

Engineering degree in AI and data science, still in daily use.

Supply chainSourcing to
doorstep

Vendor negotiationProcurementPurchase orders Demand planningInventory managementSKU and category management 3PL and fulfilmentDispatchSOP development

GrowthWhere the
orders come from

ShopifyBlinkitZeptoInstamart MarketplacesSEOPerformance marketing GA4CACROASAOVLTV

BusinessThe part that
reaches the founder

0 to 1 executionGo to marketUnit economics and P&L Market sizingBusiness reviews (OKR, MIS)Program management Cross functional stakeholder managementOdoo ERPAdvanced ExcelPower BI

LanguagesData and ML

PythonSQLPandasNumPy Scikit learnTensorFlowPyTorchKeras Time series forecastingStatistical analysis

AILLM and
automation

Large language modelsRetrieval augmented generationLangChain HuggingFaceVector databasesNLP n8nRelevance AI

InfraPipelines and
deployment

Apache AirflowETL pipelinesFastAPIDocker CI/CDAWS SageMakerGoogle Cloud PlatformREST APIs MLflowDVC

Business systemsWhere the two
sides meet

Odoo ERPShopifyOMSTMS Power BIAdvanced Excel

Weather Data ETL Pipeline

Airflow · Docker · PostgreSQL

Tesla Stock Forecasting

ARIMA · SARIMA · LSTM · Value at Risk

Political Sentiment Analysis

Transformer NLP · 81% accuracy

Medical Insurance Cost Prediction

Regression models · 86.5% accuracy

BackgroundWhere it
came from

Business school on top of an engineering degree

One taught me to build the system. The other taught me to argue for it in a room full of people who own the budget.

Education

Aug 2025 → Aug 2026Gurgaon

PGP Rise (MBA), General Management

Master's Union

A build first business school. The programme runs on live company problems rather than cases written ten years ago, which is how I ended up in a founder's office instead of a graduate scheme.

MBA

Dec 2021 → May 2025Pune

B.E. Artificial Intelligence & Data Science

Dr. D. Y. Patil Institute of Technology, Savitribai Phule Pune University

Four years of machine learning, NLP and data engineering. Outside the coursework I was Student Coordinator at the Entrepreneurship Development and Startup Innovation Cell, running community relations and bringing industry people in for events, and Marketing Executive at TEDxDYPIT (550 plus attendees). GURU started here.

B.E.

Credentials 12 certifications

BusinessStrategy and
finance

McKinsey.org Forward Program McKinsey & Company · 2025

Stock Trading Professional Certification New York Institute of Finance · 2025

Essential Career Skills for Investment Banking and Finance New York Institute of Finance · 2025

Money Markets, Foreign Exchange and Time Value of Money New York Institute of Finance · 2025

Marketing Fundamentals: Who Is Your Customer? Babson F.W. Olin Graduate School of Business, edX · 2025

GrowthDemand and
channels

Fundamentals of Digital Marketing Google Digital Academy · 2023

Google Project Management Google · In progress

AI and dataThe technical
base

Machine Learning Specialization DeepLearning.AI · 2024 Supervised Learning: Regression and Classification
Advanced Learning Algorithms
Unsupervised Learning, Recommenders, Reinforcement Learning

Intro to ChatGPT and Generative AI 365 Data Science · 2023

Introduction to Data and Data Science 365 Data Science · 2022

Leadership and awards

Leadership

Student Coordinator, Entrepreneurship Development and Startup Innovation Cell

Ran startup community relations at DYPIT: bringing industry people in, and putting events and collaborations together.

Pune

Leadership

Marketing Executive, TEDxDYPIT

550 plus attendees.

Pune

Awards

Mathematics Olympiad, Gold Medalist

The reason numbers are the first place I look when something feels off.

Gold

Also

Machine Learning Engineer, Healthsutra

Three month internship building NLP and data science work, alongside the final year of the degree.

2025

ContactGurgaon, India
Replies fast

I am most useful early, before the systems exist.

Consumer brands and early stage startups especially, seed through Series B, where the founder still needs someone to take an entire problem off their desk and come back with it solved. If that is the seat you are trying to fill, write to me.

Email krishnamistry.co.in@gmail.com Phone +91 81280 34874 LinkedIn krishna-mistry-677587229 GitHub Anonymous143w