Performix provides measurement science tools for performance leadership, helping organizations identify the single condition limiting their team's performance and track whether fixes work. The platform operates as a cooperative where members jointly own the tools, corpus, and community, with options for enterprise, practitioner, worker, or rental access. The environment runs on each organization's own data and can be called by their AI assistants.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations struggle to improve team performance because they rely on generic best practices rather than understanding the specific conditions driving their unique situation. Each organization's tool stack, data, and decisions are different, yet the same measurement and decision tools are needed across organizations, making it inefficient for each to build them independently.
Solution
Performix provides a measurement science platform that identifies the one binding condition holding a team back and tracks whether interventions actually work. The platform adapts to each organization's specific situation, measuring conditions rather than mining data or blaming individuals. It operates as a cooperative where members jointly own the tools, corpus, magazine, and community, running on a platform licensed from Bicycle LLC. The environment runs on each organization's own data, can be called by their AI assistants, and is built collaboratively with the people who will use it rather than sold by a vendor.
Target Audience
Primary customers are organizations seeking to improve team performance through data-driven measurement, as well as individual practitioners in performance leadership roles who want access to the toolbox, corpus, and community.
Features
- Measurement science approach that names the single binding condition limiting team performance
- Situation-adaptive walk that adjusts based on where the organization is in its performance journey
- Tenant backplane architecture allowing the environment to run on each organization's own data
- AI-assistant callable interfaces for integrating performance measurement into existing workflows
- Cooperative ownership model with member equity accounts, board seats, and patronage shares
- Data commons with anonymous aggregates shared only when enough organizations participate
- Co-development process where practitioners shape what gets built next