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Agentic data engineering

Pipelines, without the wait. Agents build them. Your team approves them.

From our inventory database: daily stock cover by store, fresh by 7 a.m.

Build it

Connect a database, say what you need in your own words, pick the KPIs. Then scroll: agents build it in front of you.

Who does the work
Agents
Profile your real data14 columns
Write the data pipeline7 files
Test it safelyall checks
Fix what breaks1 fixed
Send it for your review#128
Your team
Described it
nothing for you to do
Review and approve

Reading the shape of your data, on your real tables.

An example build. How long a build takes depends on what you ask for, and you see its size before anything is built.

Building inventory_dailyProfiling…
Profiled
Rows1.24M
Columns14
Nulls · on_hand_qty0.3%
Joins tostores · products
Testsqueued
pipeline runs
no missing stock values
re-run · no duplicates
personal data masked
Your turn

Nothing ships until a person approves it. Today, that’s you.

The pull request is in your own repository, as plain code your team can read. Read it and approve it. Deploying is a separate click, never automatic.

harborline / data-platformYour repository

#128 Add inventory_daily pipeline

14 files · +1,284 −0 · opened by Nectorq
✓ All checks passedReview required
ModelsHow your data is shapedread it, change it
TestsTests and docsfor every model
LoaderMoves your data inruns on your schedule
DeployDeploy workflowdeploys to your cloud
You are the reviewer.
● Livein your cloud · watched on every run
Ask

Ask your data, in plain words.

3 stores are under three days of cover.

StoreManagerDays of cover
Seattle FlagshipAva Thompson1.8
Tacoma MallDaniel Ortiz2.4
Portland PearlMarcus Webb2.9

from your inventory database · read-only · data through today 06:41

Answered from your own database, read-only.

Converse finds the right tables, writes one read-only query, checks it, and shows its work: the query, the tables and the definitions it used. Flip the lens to see exactly what the model received.

  • Senttable names · the question · a capped slice
  • Maskedpersonal data, and anything untraced
  • Runread-only, inside your database
It’s yours

It’s yours. Every line of it.

Ordinary code, in your repository, running in your cloud, on your data. The platform keeps building, watching and answering. You keep everything it builds.

Yours · your cloud · your repository
Your datain your warehouse
Your codeharborline/data-platform
Your pipelineson your cloud account
harborline / data-platformmain
Transformationsread them, change them
Tests and docsfor every model
Loadermoves your data in
Deployto your cloud
You own
  • Your data, where it already lives
  • The code, in your repository
  • The pipelines, running in your cloud
  • Every change, reviewed in your Git history
Nectorq brings
  • Agents that build the next one
  • A watch on every run
  • Answers in plain words
  • Changes, whenever you ask

No lock-in, by design. We would rather earn your next pipeline than hold on to your last one.

How you pay

You don’t pay per seat. You pay per pipeline.

A platform subscription, plus one for each pipeline on your plan. Drafts and unfinished builds never count. If one fails because of Nectorq, it stops counting until it’s fixed. And if you outgrow your plan, what’s running keeps running.

How you pay

Seatsnever
People asking questionsnever per person
Drafts and unfinished buildsnever
A pipeline failing because of Nectorqstops counting until it’s fixed
Pipelines on your planwhat you pay for

You briefed it, approved it, and kept every line. Now do it on your data.

Bring one database. Leave with a pipeline: sixty days, your cloud, your code.