What if all your data spoke over the same rails?
And understood every aspect of your business. The ledger, the pipeline, the campaigns, the warehouse, the tickets, the roster, the contracts: each lives in a system that speaks its own language. We connect them on one business brain, put an AI workforce on those rails, and train the whole company to run it, so every decision in the building is made on the data. Every function trained and deployed, so the people are ready the day the system is.
Every enterprise build is custom, so pricing comes from a conversation. The Readiness Score is free: two hours with your leadership team, a one-page score.
Connecting the systems that speak their language.
Two rails in the center: the business brain, which holds everything the company knows, once; and connected data, every system of record read in one language and written to only through its own controls. Eight functions around them, each with the systems it already runs on. Open any one for the training and deployment we bring to it.
- FinanceSAP · Oracle NetSuite · Microsoft Dynamics 365
- Sales and RevOpsSalesforce · HubSpot · Microsoft Dynamics 365
- MarketingHubSpot · Adobe Marketo · Mailchimp
- Customer Support and SuccessZendesk · Intercom · ServiceNow
- Operations and Supply ChainSAP S/4HANA · Oracle SCM · Microsoft Dynamics 365
- PeopleWorkday · ADP · BambooHR
- IT and SecurityOkta · Microsoft Entra ID · ServiceNow
- Legal and ComplianceDocuSign · Ironclad · Vanta
The answers no single system can give.
Every one of these needs data from three or four functions at once. Today that is a meeting, a spreadsheet and a week. On the rails it is a question, answered from the systems of record, with the sources attached.
Cash, actually daily
Receivables from the ERP, expected collections from the CRM's deal stages, payables from the AP tool, payroll from the HRIS, into one cash view every morning, with the three things that moved it.
Finance, trained and deployed →The whole account in one answer
A rep asks before a call and gets the deal, the last three calls summarized, open tickets, invoice status, product usage and what marketing sent, in one page, from six systems.
Sales and RevOps, trained and deployed →Attribution to the collected dollar
Ad spend, registrations, opportunities, invoices and payments joined across the ad platforms, the CRM and the ERP, so marketing reports cash collected per campaign instead of leads per campaign.
Marketing, trained and deployed →Demand from the pipeline to purchasing
Open deals, campaign performance and seasonality read into the purchasing plan, so the buy happens before the stock-out instead of after the complaint.
Operations and Supply Chain, trained and deployed →Churn seen ninety days early
Usage, ticket sentiment, invoice disputes and renewal dates into one health score, with the play assigned to success and the account owner told.
Customer Support and Success, trained and deployed →Onboarding that runs itself
The signed offer creates the accounts, the devices, the calendar, the training path and the manager's checklist across IT, the HRIS and the LMS, and reports what is done each day.
People, trained and deployed →The contract as obligations
Every executed agreement read into its obligations, dates and terms, and each one handed to the function that owns it: the renewal to sales, the payment term to finance, the data clause to IT.
Legal and Compliance, trained and deployed →An identity for every co-worker
Each agent is a principal in the identity provider with scoped access, a service account, an owner and an audit log, reviewed like any other account. This is the layer that makes the rest of the company's AI possible.
IT and Security, trained and deployed →Decide from the systems of record, every time.
The point of the rails is the decision at the end of them. Today a leadership decision runs on a deck someone assembled last week from numbers that were already stale, with the assumptions invisible. On the rails the question is asked of the systems themselves, the answer arrives with its sources attached, the decision is recorded beside the evidence, and the outcome is measured against it a quarter later. Judgment stays with the people. The evidence arrives settled.
One version of the numbers
Finance, sales, marketing and operations read the same figures from the same systems, so the meeting starts at the decision instead of at whose spreadsheet is right.
Every answer with its sources
A figure in a decision carries the records it came from. Anyone in the room can open them. The assumption that used to hide inside a deck is visible.
Plain questions, answered in minutes
“What did the last three launches cost us in stock-outs?” answered across the ad platforms, the CRM, the warehouse and the ledger, with no ticket to the data team.
A decision log that closes the loop
Each decision is recorded next to its evidence and the result it expected. The quarterly re-score reads the actual against it, so the company learns from its own calls.
Decisions that run on the rails
Each one used to take a week of assembly. On the rails it is a question, and the functions it draws on are the pages on this map.
Buy ahead of demand?
Open deals, campaign performance and supplier lead times read into the purchasing plan.
Renew the vendor?
Usage, cost, incidents and the contract's terms, read from the systems that hold them.
Leadership, its AI Chief of Staff and the numbers in one place. The weekly review runs from the rails: what moved, why, what the systems say to do next, and what was decided last time and how it turned out. The training makes every leader fluent in asking, and every operator fluent in what the answer is built from.
Finance is where every other function’s data finally has to agree.
The ledger only knows what was posted, so finance is the function that feels the disconnect first: the close waits on everyone, cash is a weekly guess, and every exception arrives without its reason. Connect finance to the rails and the rest of the company is connected to the numbers.
We train the people and deploy the infrastructure.
Ninety-three percent of the stall is people. So the training runs alongside the install, and the people are ready the day the engine is. Neither leg works alone; together they are the transformation.
Train
Every employee to White Belt: AI literacy, how to hand work to an agent and check it. Operators in each migrated function to Ninja: run, tune and extend the engine. Two or three per company to Sensei: train the next cohort and own the standard after we leave. The same dojo path, run inside your company.
The path we teach →Deploy
The infrastructure the company runs on, installed one engine at a time with a completion test written in your own operational language. The rails first, then the co-workers that take over whole functions: finance, sales, marketing, operations, support, people, IT, legal. You own the agents. They run on your accounts.
The functions we deploy →Analyze everything. Migrate in order. Train everyone.
The order carries the whole argument. We analyze before we optimize, because the companies that lose are the ones running twenty-five disconnected projects. We migrate one engine at a time, because a ninety-day cutover with a completion test is a thing a CFO can fund and a board can see. We train alongside the install, because the people are the stall.
Readiness Score
Free. Two hours with your leadership team, scored on four dimensions: removal test, data, governance, people. A one-page score and the three findings that matter most.
Workflow Audit
Function by function, every workflow mapped: trigger, steps, systems, people and hours, exceptions, decisions, data, controls. Each one scored for automation fit and dollar value. The deliverable is the Operations Map.
Migration Plan
The ranked backlog becomes a cutover sequence: which engine first, which workflows inside it, what data to fix before day one, the completion test for each module. Fixed fee, credited against the first engine.
Engine Migration
One engine per quarter, ninety days each, back office first. Every module ships with a completion test in your own operational language. Fixed price per engine, agreed before we start.
Staff Training
The dojo runs alongside the install: White Belt for everyone, Ninja for the operators, Sensei for the two or three who will own the standard.
Operate
Autonomous operations, watched. A quarterly re-score, then the next engine.
Teams of every size, trained to run it.
A ten-person team and a thousand-person company get the same ladder, sized to the room. Every cohort runs on the dojo’s path: the front door, the foundation, the engines, and the black belt for the ones who will lead.
AI literacy, the gates in plain language, how to hand work to an agent and check it.
Run, tune and extend the engine in their function. The same path as the dojo, inside the company.
Train the next cohort and own the standard internally. The reason the migration holds after we leave.
Sovereign, fixed, and tested.
You own the agents
They run on your accounts and your subscriptions. When we leave, everything stays.
No meter
No per-conversation charge, no per-action charge. A fixed price per engine with a completion test.
Proof over promise
The studio behind this dojo has shipped 65 products, systems and client solutions with the same architecture. The Readiness Score shows you yours before anyone commits.
The Readiness Score. Free, and the whole first step.
Two hours with your leadership team. You leave with a one-page score across four dimensions and the three findings that matter most. Every enterprise build is custom, so pricing comes from this conversation; if the plan follows, the score is where it starts, and if it does not, you keep the findings.