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Data infrastructure for $10M–$100M operating companies

Your AI is only as good as the data underneath it

Every company your size is deploying AI. But if your systems can't agree on last month's revenue, no model can help. That's where we start.

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Our consultants built data systems at
Morgan Stanley Deloitte LexisNexis Legg Mason Catalent

01

Every one of these tools knows something about your business. You've never seen it all at once.

Salesforce QuickBooks HubSpot Stripe Shopify Xero Zendesk Slack Jira SAP Oracle Airtable Google Sheets Mailchimp Square Asana Dropbox
Sage Google Ads Intercom Twilio Gusto ADP Expensify Brex PayPal Notion Trello WooCommerce Magento BigCommerce Odoo Tableau Zoom

02

Sooner or later, someone outside the building goes through your numbers line by line

A buyer. A lender. A board that stops taking the monthly pack at face value. When that happens, every system that disagrees with another becomes a problem with a dollar sign on it.

03What we find

The same three patterns, at almost every company

01

The CRM says one thing, finance says another

We connect both to the same warehouse and reconcile the definitions at the source. The board meeting opens with one slide, not two.

02

The board pack is assembled by hand, every month

We pipe the data straight from the warehouse into the pack. It assembles itself. Your team stops exporting and starts analyzing.

03

Nobody's quite sure how the systems connect

We map every integration, document what's actually flowing where, and rebuild what needs it on infrastructure your team can see. No more guessing.

04The approach

One workflow, end to end. Then the next.

We don't start with an eighteen-month transformation. We pick the workflow that's costing you the most: the month-end report, the meeting follow-ups, the numbers your team assembles by hand. We take that one slice all the way. The data underneath it, the reporting on top, the automation around it. The slice tells us what to build next, because the work that keeps showing up is the roadmap.

Three levers move enterprise value: margin, earnings quality, and the growth story. Most companies this size can't move any of them, because the data underneath all three is scattered. And most firms will sell you exactly one layer of the fix, quietly rebuild the same data plumbing to deliver it, and bill you for the privilege: three vendors, three half-built foundations, three versions of the truth. We build the foundation once, and everything runs on it. And if someone else started and didn't finish, we pick up where they left off.

Three stacked planes: a data foundation, reporting, and an AI agent on top
Data · Reporting · AI

05AI agents

We build AI agents. Here's what one looks like when it's real.

Meet AIDA, an AI data analyst you can call from Slack. Ask it a question in plain language; it investigates the warehouse the way an analyst would, running queries, checking what it finds, trying again, and returns the answer, the SQL that produced it, and the caveats, in one message. Then ask the follow-up, the way you would with an analyst, and it keeps digging. It shows its math.

It ran through our client's busiest season in production, the season that had buried their data team the year before. This time routine pulls stopped swallowing the team, and the analysts spent the crunch on work that actually needed them. A data request that used to take an analyst one to two hours comes back in about sixty seconds.

#finance-questions AIDAApp
SR

Sana Rahim

@aida why did gross margin dip in March?

AIDAApp

Gross margin fell 2.1 points in March. Nearly all of the move is freight surcharges in the West region; margin excluding freight was flat. Caveat: March had one fewer selling day than February. 

SELECT region, month,
       SUM(gross_margin_usd) AS margin,
       SUM(freight_surcharge_usd) AS freight
FROM   finance.margin_monthly
WHERE  month BETWEEN '2026-02' AND '2026-03'
GROUP  BY region, month
ORDER  BY region, month;

6 rows · 0.8s

SR

Sana Rahim

is it one customer or all of them?

AIDAApp

Two accounts. Nordwest and Halvorsen moved to expedited freight in February and account for 1.6 of the 1.9 points. The rest of the West region is flat. Caveat: both renew in June.

Finance & data

AIDA

AI Data Analyst

01

Ask it a question in plain language, then keep asking. It holds the thread and digs — from the number, to the region, to the two accounts behind it — in Slack or inside the dashboard.

Readsthe warehouse: finance, sales and ops tables in its scope
Returnsthe answer, the SQL, the chart — and the next answer when you push

Operations

KAT

AI Operations Agent

02

Sits in your standup and writes what it hears to the board: the blocker raised out loud, the estimate that changed, the ticket nobody updated after. Every write leaves a trail a person can override.

Readsthe standup transcript, and the board beside it — Jira, Linear or Asana
Writesticket updates, estimates and the blockers nobody filed — logged, attributed, reversible

Forecasting

NOVA

AI Forecasting Agent

03

The same warehouse, pointed forward. It projects what's coming, keeps the dashboard current, and raises a flag when a number is heading somewhere you'd want to know about early.

Readsthe warehouse's history, the same numbers your reports run on
Writesthe projection and what's driving it, dashboard updates, threshold alerts

One scaffold, built once, so every agent after the first is a fraction of the effort. Which one your company needs first is exactly what the audit figures out.

06Proof

Eight systems became one. Revenue doubled.

At Human Development Fund, eight disconnected systems became one. Revenue grew from $17M to $33M with retention held above benchmark throughout.

Our deepest work has been for humanitarian organizations, including one whose platform processed $664M+ in donations. The companies change, but the data problem is the same. We've been solving exactly this, at organizations that answer publicly for every dollar.

Read the case studies

07The people

Who you'd actually be working with

SH

Samad Husain

CEO

Told his first boss: “You don't need an analyst. You need an engineer.” Built LaunchGood's data function from zero and re-architected departments' data infrastructure at a Fortune-50 tech company.

FA

Fahad Ahmed

CTO

Builds the integrations, infrastructure and guardrails behind every Datstra deployment. He wrote the rules those agents live inside.

HC

Hamza Chaudhry

COO

Runs every engagement from kickoff onward. The reason the audit lands in two weeks, not six.

More about the team →

08Getting started

From first call to first result, one workflow at a time

01

Find out if there's anything here

30 minutes · free

We ask how long your monthly close takes, how many separate systems hold a number you report on, who assembles the board pack and how. Then we tell you honestly whether there's something worth doing.

02

Get the diagnosis

Two weeks · paid

Priced and scoped up front. We map your systems, test what their APIs can actually do, and hand you a written diagnosis with a costed roadmap. Yours to keep and act on, with us or with anyone else. That diagnosis tells us which workflow to take end-to-end first.

03

See the first workflow live

The first 90 days

Three to five source systems connected, the first workflow live, your numbers reconciled and signed off. If your systems are simple, faster.

04

Keep the numbers right

Ongoing

Most support contracts cover uptime, not truth. Whether the numbers are right is usually nobody's job. With us it's the whole job. Everything runs in your accounts, in your repositories, from day one.

What we deliver: numbers you can trust, in front of the people who need them, on time.

Can you prove it when they ask?

If it takes your team a spreadsheet, a week, and an argument to answer that question, thirty minutes with us will tell you what it would take to answer in one glance.

01

One call to find out if there's a problem worth solving

02

A written diagnosis you keep regardless of what comes next

03

Numbers the board can trust, on time, every month

Book a Discovery Call See Our Results

No deck, no pitch · hello@datstraanalytics.com · For $10M–$100M operating companies