Profitability you can prove, not guess.
An operating model of your business that shows which customers, products, and activities make your profit, and which ones cost you. Our engine computes every figure, your finance team runs it, and the AI you already use can now drive it.
Watch a worked exampleMore revenue isn't more profit.Your accounts tell you the company made money. They don't tell you which work made it, or which work quietly cost it.
Most operationally complex businesses run on a P&L that aggregates everything above the gross margin line, then aggregates everything below it. It tells you whether last quarter was good or bad. It doesn't tell you which customers were subsidising others, which products earned their place on the shelf, or which operational activities consumed margin you can't see. Attributing cost properly answers all of it, and it is the work most teams skip, because it has always been too slow and too expensive to do well.
The people who feel this most acutely are the ones closest to the numbers. Finance leaders who close the books cleanly every month, then get asked by a CEO or a board which customer segments to double down on, and want to answer with evidence, not instinct.
Curious what your profit shape looks like?
Answer five quick questions and see the likely shape of your profit: where it concentrates, how many customers may be losing you money, and the margin probably at risk. An illustrative benchmark for businesses like yours.
How it works
Map your operations.
A guided process turns your business into a structured operating model: revenue streams, activities, cost pools, products, customers. Days of work, not months.
Connect your data.
Pull in financials from your accounting system and operational data from wherever it lives. ERP, CRM, spreadsheets, warehouse systems. We work with the data you already have.
Let the engine do the work, and the AI do the analysis.
CostCtrl's allocation engine attributes every cost to the activities that consumed it, and every activity to the customers and products that triggered it. Tens of thousands of consistent, explainable allocations. The AI reads the result and tells you what to do with it: which customers to renegotiate, which products lose money, where margin is leaking, and what a change to price or mix would do. The analysis a team would take weeks to assemble, ready the moment the model runs.
Act on what you find.
Profitability by customer, product, region, channel, and activity, with scenario modelling for pricing, mix, and operations. Numbers your finance team can defend line by line, and a clear list of where to win margin back.
Then close the loop.
The model above is deterministic and auditable. The MCP server adds a port to it, so the AI you already use can drive it: set a target and constraints and let it search for the plan. Goal seek, for the whole business. Every candidate computed by the engine, not guessed.
- EngineCostCtrl
The deterministic operating model. Cost pools, drivers, attribution, every rule auditable.
- The portMCP server
A standard socket. Scenarios, inputs, calculations and results, exposed as tools any AI can call.
- Your AIThe AI you already use
Claude, ChatGPT, Copilot or your own. It reads, proposes, changes inputs and asks the engine what happens.
The agent never types a number into the P&L. It changes inputs. The engine computes the consequences, and every figure carries the rule that produced it.
Get net margin to 7% in the FY2027 plan. Lose no more than 3% of revenue. No headcount reductions. No plant or hub closures. Find the plan.
What the engine computed- Revenue down 1.6%, inside the 3% limit
- Headcount unchanged at 526
- 10 scenarios computed, 2 rejected by constraints
Illustrative. The demo manufacturer's figures, computed by the CostCtrl engine.
What you can see, the day after you finish modelling.
Every usual option gives you a snapshot. The hard part is staying correct.
Spreadsheets.
An analyst builds a model. It works for a quarter. Then someone leaves, the data shape changes, or a formula breaks. You're back to instinct.
Enterprise platforms.
Powerful, capable, and built for companies that can afford a six-figure implementation, an in-house consultant team, and a year before anything ships.
Consulting projects.
A team of smart people produce a profitability deck. The deck is brilliant. By the time you've acted on it, the underlying business has moved on.
A general-purpose AI on its own.
It answers any what-if fluently and instantly. With no engine to compute against, the figure is invented.
CostCtrl stays correct.
It keeps the enterprise method and drops the enterprise invoice. Your finance team runs it every month, so it is still right next year, and your AI has an engine to compute against.
See what CostCtrl finds in your business.
Book a 30-minute call and bring one real question about your numbers. We'll show you how CostCtrl would answer it.
Book a 30-minute call →How Snell turned a hidden cost-to-serve problem into a multi-year margin turnaround.
CostCtrl gave us a view of our business we'd never had: which customers and products were actually contributing, once you accounted for everything it took to serve them. That visibility changed how we price, what we focus on, and how we work with customers. It's become part of how we run the business.
negative contribution cut from $1.335M to $665K
from 830 down to 295, most near break-even
a model Snell owns and runs, refined as the business changes
Driving EBITDA across a portfolio?
Built for operating partners running profitability programmes across portfolio companies. One repeatable methodology, deployed in weeks and transferable across operationally complex industries.
Common questions.
How does it go from start to live?
A one-off setup fee to build your model on your own data, then a monthly platform fee. Cancel at any time in the first three months. After that, the plan runs on an annual commitment. We build the model with you, engineer-led, typically in 3 to 6 weeks. The setup ends with quantified improvement opportunities, each with a financial target, presented to the person who owns the budget inside those three months, so you decide with the result in hand. From there your finance team runs it day to day, with as much or as little support from us as you want.
Do we need to connect our ERP?
No. We pull from the systems you have, in the formats they produce. Most engagements start with monthly data exports and add automated connections later if useful.
Where does our data live?
In a secure, logically isolated environment on AWS in the EU. CostCtrl never uses customer data to train AI models. The specifics are on our security page.
How is this different from our BI tool?
A BI tool reports on the data you already have. CostCtrl enriches it first: our engine attributes every cost down to the customer, product, and activity that drove it, so you see profit at a granularity your source systems never captured. A dashboard shows you what happened. CostCtrl tells you what it cost, and what to do about it.
How is the AI used, and is it reliable?
Every number comes from our allocation engine, which applies the same deterministic rules to every customer, product, and activity. The AI reads those results and explains them in plain language, and through the MCP port it can also drive the model toward a target. It never supplies a figure. Each attribution carries the rule that produced it, so any number can be traced and checked.
Can we plug our own AI into it?
Yes. CostCtrl can expose your model through an MCP server, a standard port that Claude, ChatGPT, Copilot or your own AI can connect to. The agent can read results, create scenarios, change inputs and run the calculation. The engine computes every consequence; the agent never types a number into the P&L. Opening the port and choosing the provider is your decision, made under your own agreement with that provider. Our security page sets out how that works.
What does it cost?
Most customers pay between $1,500 and $3,000 per month (USD) for the platform, plus a one-off setup fee to build the model. A distributor carrying around 3,000 products on $30M in revenue typically sits mid-range. Where you land depends on the complexity of your operating model and the compute it requires. For scale: Snell's first model found $1.335M of negative contribution. We'll price your setup and platform once we understand your business.
What if we already use a different cost platform?
Some customers run CostCtrl alongside an existing platform; others switch over. We'll talk you through the trade-offs.
See what's hiding in your operations.
Book a 30-minute call with Sam or Miguel. We'll walk through how CostCtrl would map onto your business, with one of your real questions in mind.