About Cooper

Software discovery is changing faster than the systems used to measure it. Buyers increasingly ask ChatGPT, Gemini, Claude, and Perplexity which products deserve consideration before they visit a vendor website, review platform, or traditional comparison page.

Cooper turns that changing layer into a dated public record. We measure repeated recommendations across defined software categories, preserve weekly movement, identify cited evidence, and show where assistants agree or diverge.

The goal is not to declare one universal winner. It is to make AI recommendation behavior legible within the market and context where a buyer is actually making a decision.

Companies cannot buy placement, approve a score, or remove an unfavorable weekly result. Cooper measures what assistants return and applies the same versioned scoring rules to claimed and unclaimed products.

Claimed profiles can add verified product information. Advertising and paid tools can provide visibility or deeper analysis. Neither changes collection, entity validation, assistant or regional weights, tie-breaking, rankings, citations, or archive history.

We measure recommendations. We don’t sell them.

Cooper uses automation and AI to collect repeated observations, process evidence, and operate at a scale that would be impractical through manual research alone. Automation provides consistency and reach; it does not decide what result Cooper should publish.

No reviewer can manually promote a product or rewrite a weekly score. Human intervention protects data quality and governance, while derived rankings remain tied to the observed answers and published methodology.

Built by Sweetspot° Partners

Cooper is built and operated by Sweetspot° Partners, a partner-led team of senior operators who use AI to deliver at a scale a small team otherwise could not. Sweetspot Partners works across growth, product, and operations, building what growing businesses are missing and organizing delivery around measurable outcomes rather than hours.

That operating model shapes Cooper: experienced people define the problem and remain accountable for the outcome, while AI provides the execution layer required to collect, structure, and maintain a living software recommendation index.

Cooper remains governed by its published independence rules, methodology versions, and correction history. Sweetspot Partners builds the system; no client or commercial relationship determines what the index reports.