Solutions

The same four agents, pointed at different problems. Start from the job you need done, or from the seat you sit in.

By use case

What people actually bring us

Five jobs the suite is built to finish, and which agent leads on each.

Modernizer leads

Legacy migration

An Oracle estate nobody fully documented has to move to Delta Lake, and the scoping alone is measured in months of manual reading.

Reads the real schema — every table and column from the DDL you have, not a sample.
Writes the code — Delta DDL, PySpark and Terraform, generated and ready to review.
Names the ambiguous columns — so nothing is silently mistranslated into a report that breaks later.
See Modernizer →
Guardian leads

Governance & compliance

Data leaves the building constantly — exports, extracts, partner feeds — and nobody can check every file by hand before it goes.

Finds exposure before it ships — PII, secrets and schema violations, with the rows that prove it.
Frames it as the regulation reads — GDPR and HIPAA groupings, so the fix list matches the obligation.
Produces a signed report — ready to file, and on Enterprise exportable to your SIEM.
See Guardian →
Engineer leads

Pipeline reliability

Loads break on upstream changes at 3am, and the choice is between waking someone up or letting a tool guess quietly and get it wrong.

Repairs what is safe to repair — and writes down the reason so you can check the call.
Stops on what isn’t — flagged for sign-off rather than guessed at silently.
Hands changes back as a PR — reviewed by your process, never applied behind your back.
See Engineer →
Analyst leads

Self-serve analytics

Every question about the business queues behind the data team, and by the time the answer lands the decision has been made without it.

Anyone can ask — in plain English, with no SQL and nothing to configure first.
The query is shown first — so the answer can be checked rather than trusted blindly.
Answers arrive Excel-ready — as tables your team can open, sort and forward.
See Analyst →
All four together

Cloud migration & reconciliation

The move itself is only half of it. Afterwards someone has to prove the new numbers match the old ones, and keep them matching.

Modernizer moves the schema, with a runbook and validation checks written before cutover.
Analyst reconciles the numbers — ask the same question of both sides and compare the answers.
Engineer keeps it running, and Guardian checks nothing sensitive moved that shouldn’t have.
How the four connect →
By role

Where you’d start

Everyone gets all four agents. This is which one earns its keep first, depending on the seat you sit in.

Analysts, ops & founders

You have the questions and none of the SQL. Start with Analyst — ask in plain English, get an Excel-ready answer, and see the query it ran.

Start with Analyst
Compliance & security

You are accountable for what leaves. Start with Guardian — scan before it ships, and get a signed report rather than a spreadsheet of maybes.

Start with Guardian
Data platform & on-call

You carry the pager. Start with Engineer — overnight loads that repair what they safely can and stop on what they can’t.

Start with Engineer
Platform & migration

You inherited the estate. Start with Modernizer — it reads the schema you actually have and writes the migration you have to review anyway.

Start with Modernizer
Data leadership

You are signing for it. Start with the business case — what changes before and after, in the terms a budget conversation actually uses.

See the business case
Governance at scale

You need it inside your own network, with every action scored and logged and audit retained to your policy. That’s the Enterprise tier.

See Enterprise
By sector

Where this work happens

The sectors the suite is built around, and the pressure specific to each.

Financial services

Reporting that has to reconcile, and exposure that has to be found before an audit finds it.

Healthcare

HIPAA obligations on data that still has to move between systems and reach the people who need it.

Aviation

Operational data across routes, crew and cost, where a stale number is an expensive decision.

Manufacturing

Supply chain and production data spread across systems that were never designed to agree.

Retail & e-commerce

Customer and order data at volume, where the question changes faster than the pipeline can.

Technology & SaaS

Cloud-native stacks that grew fast, and now need governance that didn’t grow with them.

How it works

Plug in, pick agents, run

Point it at a source. Choose what runs. Collect the answers.

Industries

Proven impact across industries

Raw data transformed into strategic intelligence — powering measurable outcomes across six major sectors.

Financial services

Risk analyticsCompliance dashboardsForecasting

Healthcare

Data pipelinesKPI dashboardsCompliance reporting

Aviation

Passenger insightsRoute planningCost efficiency

Manufacturing

Supply chain analyticsInventory intelligenceProduction planning

Retail & e-commerce

Customer analyticsPersonalizationRevenue growth

Technology & SaaS

Cloud-native BIAI/ML integrationScalable warehouses
Core capabilities

Everything you need to lead with data

From engineering to AI integration — our practice areas cover the full modernization lifecycle.

Data platforms & engineering

SnowflakeAzureAWSDatabricks

Intelligence & insights

Power BITableauSalesforce Analytics

Analytics & AI integration

Predictive modelingMachine learningDecision support

Process efficiency & automation

Self-service BIAutomated pipelinesUnattended overnight loads

Compliance & security by design

GDPRHIPAAISO-aligned

Agile & collaborative delivery

Agile/ScrumStakeholder collaboration
The full circle

From the first question to the bottom line

The same sequence the live demo walks through.

  1. Day 1 Connected and answering Usable in minutes
  2. Day 2 You know your exposure Risk caught pre-ship
  3. Day 3–5 Loads stop paging you 0 nights interrupted
  4. Onwards Migration has a plan 34 of 43 columns mapped
Before & after

The business, before and after

Four agents, but one story — what changes when the whole business runs on one shared understanding of its data.

Analyst
Waits on the data team’s queue
Answered as you ask
42,013 orders, no SQL
Guardian
Risk found at audit
Caught before it leaves
622 IDs flagged
Engineer
Pages someone at 3am
Repairs itself overnight
0 people woken
Modernizer
Months of guesswork
Mapped up front
34/43 automatic
Columns still to map by hand
Before
All 43
After
9 left
The business case

What each agent is worth

Measured inside the product, not projected.

42,013
orders answered in one question
$2.1M surfaced in the same query
No day lost waiting for an answer
622
national IDs found in plain text
2 critical findings, 1 file
Exposure caught before it ships
2.4M
rows kept flowing overnight, unattended
1 fixed automatically, 1 flagged
Nobody woken at 3am
34/43
columns mapped without a human
9 tables read from a live schema
The plan starts from what is really there

Counted, not estimated. Every figure above comes from a run that ships inside the app — the files, the questions and the findings are all in there.

Start it yourself →

Not sure which one you need?

Tell us what’s slowing you down and we’ll tell you which agent to start with.

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