A Chrome extension request. An 18-month technical co-founder engagement.

How a data intelligence company went from no technical infrastructure to a complete prospecting platform, a 3-million-record search engine, and a full engineering team, starting from a single small task.

$200,000

total engagement value

18 months

as acting technical lead

1 task

starting point: a Chrome extension request

About A Data Intelligence Company

A Data Intelligence Company is a data and trade intelligence company. Their business: providing trade data and business intelligence to companies looking to expand into new markets. They wanted to build a LinkedIn prospecting platform, their own internal version of a tool like Apollo.io, as a core product.

The problem

A clear product vision. No technical foundation.

A Data Intelligence Company had the business model and the market knowledge. They understood the problem they were solving and had a clear vision for the product. What they did not have was any technical infrastructure to execute it. No engineering team. No architecture. No foundation.

They needed someone who could not only build what they imagined but make the architectural decisions that would determine whether the product could scale, design the system from the ground up, and own the technical direction end to end.

A relative of the owner found Harsumeet and made the introduction. The owner's trust in that recommendation is what made the engagement possible.

The brief

The initial request was a Chrome extension. Small, scoped, minimal commitment. An entry point that let both sides build trust before the larger engagement was defined.

The discovery process revealed the full scope. The Chrome extension was one component of a complete product that needed to be designed and built from scratch.

The build

Seven components. One complete product.

Chrome extension

The original brief. A browser extension allowing users to extract and enrich prospect data from LinkedIn profiles. The first piece of the platform.

Full web application

The core product. A web-based prospecting platform where users could search, filter, and manage prospect lists. Designed for the way their users actually worked.

Admin panel

Internal tooling for the A Data Intelligence Company team to manage users, data sources, access levels, and platform settings.

Programmatic SEO infrastructure

A content architecture designed to generate organic search traffic at scale. Pages built programmatically from the data, targeting the search terms their prospective users were already using.

ElasticSearch implementation

The search infrastructure for the platform, implemented at 3 million records. Fast, relevant, scalable. The kind of search experience that makes a data product feel professional.

Engineering team recruitment and assessment

As the product matured, A Data Intelligence Company needed to build a technical team. Harsumeet ran the recruitment process, assessed candidates against the technical standards the product required, and helped onboard the team into the existing codebase and architecture.

Technical operations leadership

For over a year, Harsumeet ran the technical operations of the company end to end. Decisions about architecture, technology choices, team direction, and product development all ran through this engagement.

How we worked

This was not a project with a defined end date. It was a partnership that grew as the product grew. Each phase of the build created the foundation for the next. The trust built through consistent delivery over 18 months is what made the depth of the engagement possible. The engagement is not currently visible on Upwork as it moved off-platform as it scaled.

What changed

A data company with no technical foundation launched a complete prospecting platform

The platform scaled to 3 million searchable records with fast, reliable search

A technical team was hired, assessed, and operational

Technical ownership was clear and consistent throughout

The product that started as a Chrome extension became the company's core commercial asset

What this shows

Data companies do not fail because of bad ideas. They fail because the architectural decisions made in the first 90 days are wrong, and fixing them later costs more than getting them right at the start.

The reason this engagement lasted 18 months and produced a complete product is that the foundation was right. Every component built on what came before. The Chrome extension data model informed the web app schema. The web app schema informed the ElasticSearch implementation. Getting the architecture right at the start is not optional. It is the whole game.

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