Everything you need to know about Cooper, how it works, who it's for, and where it fits alongside the tools you already have.
Cooper is a PE-native decision intelligence platform. It connects to a portfolio company's existing systems and surfaces prioritized, EBITDA-tied decisions, each with an owner and a date attached.
Cooper is a decision intelligence platform built for private equity value creation. It connects to a portfolio company's existing ERP, CRM, billing and operations systems, then returns prioritized decisions, ranked by EBITDA impact, with an owner and a deadline on each one. No dashboards. We deploy in about five days and deliver the first ranked opportunities within two weeks.
Decision intelligence sits between having data and using it. Most portfolio companies already have the data, and the dashboards too. What they are missing is the answer to a simple question: which move do we make first, and who owns it? Decision intelligence takes raw transaction data and turns it into ranked actions, each tied to EBITDA, with a name and a deadline on it.
Cooper is for the people who own a value creation plan: private equity operating partners, deal teams, and the executives running the portfolio company. Ask your question in plain English and you get a decision back. You will not need SQL, a BI tool, or a data scientist to use it.
We work across a range of industries. Consumer and beauty brands, education and classroom supplies, aviation, healthcare, and multi-site services are all on the platform today. The questions we field most often cover revenue and margin, customer and channel performance, inventory and demand planning, and procurement spend.
Both. Most clients start with a single portfolio company, run as a 30-day proof of concept on one business. From there it scales across the fund. Every portfolio company you add makes the benchmarking and pattern recognition sharper. Data stays isolated per company. The fund sees roll-ups; the detail stays with the company.
Cooper is based in Los Angeles, California and was founded in 2023. The company is led byAPPEND: leadership names.
Decisions. Cooper reads the business data you already have and hands back a ranked list of moves, each one carrying a dollar figure, an owner, and a date. You skip the part where you stare at a dashboard and try to work out what to do next.
Three engines, one for each place the money gets stuck. Revenue Finder goes after pricing, discounting, churn, and sales coverage. Cost Finder works procurement, product mix, contracts, and overhead. Cash Finder frees working capital out of receivables, inventory, and payables. On a full rollout, all three run.
Something you can act on the same day. Real example: Cooper found three products priced below where they should have been, worth $362,485 of gross margin over a year. It read twelve months of sales data, ran price sensitivity on each product, checked what retailers were charging, and ranked the three. It also caught two retailers selling one of them under MSRP, so it flagged a pricing check before anyone moved.
Whatever you would ask a good analyst. Why is margin slipping in the Northeast? Which customers look like they might leave? Where are we overpaying for parts? You type it in plain English. No SQL, and nobody has to pull a report for you.
Every number runs through a fixed recipe instead of being improvised on the spot. There are more than 800 of them, covering client metrics and business rules. A routing layer sends each job to whichever model handles it best (we run Claude, ChatGPT, Gemini, and Grok), and outputs get checked before they reach you.
Your BI tool already shows you what happened last quarter. What it will not do is tell you which of the forty things on that dashboard is worth acting on this week. That is the gap Cooper fills. It reads the same data, then ranks the moves by the dollars they are worth and puts a name against each one.
Most consultancies work the same way: ninety days, a 200-page deck, then the team leaves and the findings start to age. You pay north of $500K for that, and again every time you want a new answer. Cooper runs the same discovery and stays on it, for a fraction of one study.
Ask ChatGPT where your margin is leaking and you will get a reasonable list of ideas. Ask Cooper and you get the three products actually priced wrong, and the margin sitting on each one. The difference comes down to what the model is pointed at.
Some firms do. It is a nine-month build at minimum, and that assumes you already have the people. Connectors alone run 8 to 12 weeks; the layer that turns raw tables into agreed metrics takes another 12 to 16. Then it needs looking after forever (model upgrades, data changes, the occasional schema break). We did that work already, and we keep doing it.
Plenty of decision platforms exist. They were built for supply chains and for fraud teams, and they are priced for large enterprises: $5M and up, with a year or more before the first output. Cooper was built for private equity from day one. The playbooks and the metrics are already the ones an operating partner asks for, and the first ranked decisions land inside two weeks.
See Cooper on your own portfolio data. First ranked decisions inside two weeks.