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The bottleneck was never writing the pipeline.

For a data team, the hard part was the profiling before anyone could start, the review before anything shipped, and the sign-off before personal data could go anywhere new.

01Why we built it

So the backlog grew, and for years it was ours.

Our team owned the data platform, architecture and engineering for billion-dollar Fortune 500 businesses in retail and healthcare, where a wrong number costs trust as well as money. Every new request waited behind the last one.

Nectorq hands that queue to agents. They do the work, and a person approves every pull request before anything ships.

Data requests · openoldest first
  1. Clinic no-show rate33 dOperations ·waiting on data sign-off
  2. Daily stock cover by store19 dRetail ops ·waiting on profiling
  3. Weekly margin by region12 dFinance ·waiting on review
  4. Returns by reason code4 dMerchandising ·waiting on an engineer
Board KPI refreshjust in · fifth in line
An illustration of the queue we used to own.
02How we build it

Four rules we hold ourselves to.

They come from the seat we used to sit in: the one that signs off a pipeline and answers for its numbers.

A person approves
Agents do the work and a person approves it.Every pipeline and every change arrives as a pull request in your repository. Deploying is a separate click, never automatic.
Masked first
The model sees what it needs, with personal data masked.To build, agents work from the shape of your data and summary statistics, with values from personal-data columns withheld. To answer a question, the model gets the schema, the question and a capped slice of the result, with personal data masked first.
Yours to keep
You keep the code, in your repo and your cloud.Ordinary code in your repository, running in your cloud. It keeps running if we are unreachable.
Said plainly
We say plainly what isn’t built yet.Every product page marks what is live, in early access or coming soon.
03Who we are

We built it from the inside, for the seat that answers for it.

Getting a system past security, past compliance and past a CFO is work we have done ourselves, from inside the business.

The founding team

where we come from
Fortune 500 data platforms

Owned the data platform, architecture and engineering inside billion-dollar retail and healthcare businesses.

Early AI adopters

Built and shipped agentic systems inside those walls before “agentic” was a category.

Built from the inside

We owned the pipelines and answered for the numbers, so we build for the people who still do.

A small team that would rather earn one data team’s trust than win a thousand sign-ups.

If that backlog looks familiar, point it at one real source.

A Proof of Value is sixty days on your own data, with your first pipelines built and running. Your cloud, your code.