Capabilities · 04 · Data

Data engineering

Data moved on time from where it is made to where it is used, cleaned and checked on the way.

On this page
Live cleaner, live
Fixed-price start
Data Dashboard in 7 Days · ₹40,000 or $1,200

Draft price These prices are drafts, not final. Nothing is charged without a written quote that you accept first. Prices in dollars are for clients outside India.

01What it is

In plain words.

Data engineering is the plumbing under every dashboard and every AI agent. Data is made in many places and in many shapes: dates written three ways, the same customer twice, amounts with and without the rupee sign.

We build pipelines that bring it in on time, clean it the same way on every run, check it, and keep a history of what changed. Rows that fail a check go to a person instead of being guessed.

You need it when

  1. Reports break whenever a column moves.
  2. The same customer appears under three spellings.
  3. You want AI to answer questions about your data, but the data is a mess.
  4. Nobody is sure which file is the real one.
02Try it

Messy rows in. Clean rows out. Nothing guessed.

Nine customer rows the way they arrive from three different systems. Switch the cleaning steps on one by one, or run them all, and watch every cell that changes. Rows that fail a check go to a person.

Live demo · Live cleanerExample dataRuns in your browser · nothing is sent

Cleaning steps

Customers · from 3 systems

Rows in
9
Clean rows out
9
Cells changed
0
Duplicates
0
For a person
0
#NamePhoneCityDateAmountNote
1 rahul MEHTA 98100 12345delhi12/03/2026₹1,200
2Anita Rao+91-98765-43210Bengaluru2026-03-121200.00
3Rahul Mehta9810012345Delhi 12 Mar 20261,200
4S. Iyer044 2345 6789chennai13/03/2026₹ 850
5Farah Khan98765-11111Mumbai2026/03/142,450.5
6VIKRAM SINGH9988776655Jaipur14-03-2026TBD
7anita rao9876543210Bangalore12.03.2026₹1200
8meera nair98470 11223Kochi31/02/2026600
9Arjun Das9433 012 345kolkata15 Mar 20263,075

For a person · 0

Rows that fail a check land here with the reason. Nothing is guessed.

Turn on "Show what changed" to see the old value next to the new one. All rows are example data.

03What we build

What you get.

  1. Ingestion from your sources

    APIs, exports, shared folders and email attachments, brought in on a schedule.

  2. Cleaning rules, written down

    Each rule is a named, tested step: one date format, amounts as numbers, one spelling per city.

  3. Checks that stop bad rows

    A row that fails a check is set aside for a person, with the reason, instead of being silently fixed or dropped.

  4. A database built to be queried

    Postgres tables designed for the questions you ask, ready for a dashboard or an agent.

  5. A history of changes

    What changed, when, and by which rule, so any number can be traced back to the row it came from.

clean_customers.pyExample
# Each rule is a named step; each change is logged.
STEPS = [trim_and_case, one_date_format, amounts_as_numbers,
         phones_as_plus91, one_city_name, drop_duplicates]

for row in batch:
    for step in STEPS:
        row = step(row, log=history)
    if problems := checks(row):
        quarantine(row, reasons=problems)  # a person decides
    else:
        load(row)
Named, tested cleaning steps; a row that fails a check goes to a person. An illustration of the pattern, not code from a client system.

What it runs on

Scheduled pipelines from your sources into Postgres tables designed for your questions, with a written history of every change.

Who owns it at handover

Who owns what (the code, the data and the accounts) is written into the scope before we build anything, so you know before you pay. At handover you get a walkthrough of how it works and what to do when it stops.

04How we work

Agents draft, people approve, receipts prove it.

The same rule runs through everything we build, and through how we build it.

  1. Draft The system

    The pipeline cleans each batch and drafts the load.

  2. Approve A person

    Rows that fail a check wait for a person; nothing is guessed.

  3. Receipt The record

    Each run records what changed, which rule changed it and when.

How a project runs

  1. A call, or an AI Checkup if you are not sure where to start.
  2. The job written down: what we build, the price and the date, fixed before we start.
  3. We build in rounds, and you approve each one before it reaches your team or your customers.
  4. Handover, with a walkthrough of how it works and what to do when it stops.

Fixed-price ways to start

Data Dashboard in 7 Days

₹40,000 or $1,200 · 7 working days

Owners who run the business from spreadsheets and can't see the numbers.

Every price

Tell us the job.

A person reads every request and replies by email.
Or start with the Data Dashboard in 7 Days: ₹40,000 or $1,200