Your board deck, every month.
A managed analytics team for companies with 50+ accounts and no data team. A senior operator runs your analytics on our own AI infrastructure: the numbers your board asks for, the metrics your team acts on, the model that says which customer to call next. Everything built in your cloud stays yours. One flat monthly fee.
Who do we call today? Is the quarter on track? What do we tell the board? The questions are not the problem. Getting them answered, every week, is.
Months to recruit a data lead, months to ramp. The first dashboard ships after the question that needed it has changed, and the knowledge leaves with the first resignation.
A fractional team or an agency bills by the hour, so the incentive is to spend hours. Every engagement starts from a blank repo, and the lineage lives in someone's head.
CRM reports, spreadsheets and notebooks each tell a different story about the same customer. “Is this number right?” has no owner, so the decision goes back to gut feel.
Today most of this is rebuilt by hand: exports pasted into spreadsheets, a report refreshed on Sunday night, a deck patched the day before the board. With ZAIOHM, the CSM opens the morning with a list, the weekly review opens with what moved, and the board pack is ready before anyone asks for it. It runs on its own, in the rhythm of the company; a person only steps in to approve.
No more pulling the list from three exports every morning. Signals fire under thresholds your reviewer set; nothing acts without a rule you approved.
No spreadsheet refreshed by hand the night before. One generated page: the numbers that moved, why they moved, who owns the next step.
No deck rebuilt by hand the week of the board. Generated from the same source as the weekly review, agreed with finance before it reaches a slide.
Software with a Service means two infrastructures with two owners. NeurohmTM is the software we run. Your data infrastructure is what you keep.
NeurohmTM is internal software, developed and operated by ZAIOHM. It brings three things to every account: automated agents that do the engineering work, the ZAIOHM standards for data pipelines (layers, owners, lineage, naming, tests) applied to every task, and self-healing pipelines that monitor their own runs and recover from common failures, such as a schema change or a failed load, before the morning review. What they cannot fix, the QA agent diagnoses and routes to a person. It is why the first release takes days, not a quarter.
The lakehouse, the models, the metric definitions, the dashboards, the reports and the CRM signals: built inside your cloud, documented and versioned, on standard tooling any data engineer can maintain. Any ZAIOHM component deployed inside it carries a perpetual, royalty-free license. If we ever part ways, it all keeps running without us.
AI made the work faster. Hourly invoices never got smaller. On a flat fee, every hour we automate is our margin and your lighter month. That is the whole incentive, and it is what you can hold us to.
Six years across every part of data. Leonardo started at Cargo Sapiens in sales ops and commercial intelligence, then moved into web development and optimization inside data science; along the way he built the VC deck and owned the unit economics. From there he joined ArcelorMittal (NYSE: MT), where he designed the procurement data platform for ArcelorMittal Brasil and was brought onto the Digital Board Room project at ArcelorMittal Europe.
The usual first step is a small team: a product manager, a junior engineer, a junior analyst. It is a reasonable start, and it comes with trade-offs. Here is how that compares with a senior squad on one flat fee.
Before benefits, recruiting fees, tooling and cloud. Add two quarters to hire and ramp.
The trade-offs that usually come with itSalary sources: Payscale, US base salary, 2026 (junior data analyst); Kore1 Data Engineer Salary Guide 2026, citing Glassdoor, ZipRecruiter and Payscale (junior data engineer, range midpoint); LaunchNotes (entry-level data product manager, range midpoint). Benefits, equity and recruiting fees not included.
Every plan is the same product: AI squads on Neurohm™, run by a named operator, for one flat fee. What you choose is the size: how many squads, how many meetings a week feed them with demand, how many governed contexts.
You run on gut feel and a spreadsheet nobody fully trusts. You need the first numbers a board can be shown, and someone accountable for them.
The process exists, but the numbers do not keep up with it. You need to know what scales before you hire for it, and a deck every month without a weekend lost to it.
Several products, teams or regions, each with its own version of the truth. You need more squads working in parallel, and each context governed on its own.
Business units with their own rules, security reviews and model providers. You need the same product, sized and governed the way the group requires.
Checkpoints are the squad's weekly reviews with your reviewer; product brainstorms are where new demand enters the backlog. Move up a size as the company grows; the infrastructure and the license come with you. Contract term and notice: [TERMS].
Agile by design: a backlog prioritized with you, short cycles, a demo at every checkpoint.
Remote, with the people who decide. Where revenue leaks, where the bottlenecks are, which question comes first.
Evidence, risks, the releases in order, cloud costs and the date of the first one. Short enough for leadership to read.
Your data infrastructure goes live in your cloud, with Neurohm™ connected to run it. First release against a test you countersign.
Checkpoints with your reviewer: demo, backlog, retro. Product brainstorms start the same week; the monthly cadence runs from there.
Anything not covered here is a good opening question for the diagnostic.
A free 30 to 45 minute diagnostic, remote, with no commitment. Bring the people who decide.