Companies are spending heavily on AI, but leaders still struggle to answer the basic question: what work is it actually doing for us? AI work is spread across copilots, chats, agents, workflows, clouds, and vendors. Cost dashboards show spending. Tool dashboards show activity. Joan gives the company one operating layer for the work, value, memory, execution, and risk.
Frontier models provide intelligence. Enterprise systems hold data. Joan gives the customer the middle layer where AI work is measured, remembered, governed, and executed under their control.
How It Works
Observe the work
Bring together AI tool usage, cloud spend, identity, teams, agents, decisions, work events, and business systems.
Measure value and cost
Track AI-assisted work, decisions, artifacts, handoffs, accepted recommendations, outcomes, and cost per useful work event by team.
Remember what works
Turn good AI-assisted work into customer-owned memory, playbooks, coaching, and reusable decisions.
Govern and execute
Know what to scale, coach, automate, restrict, or retire, and run governed digital workers where the company wants to own the work layer.
Joan can start with basic usage and cost data. The deeper value comes when companies choose to capture the actual work signal and run governed digital work under their own rules.
What You Get First
What work AI helped produce
See AI-assisted decisions, completed work, created artifacts, accepted recommendations, and cost per useful work event by team and role.
Reusable company memory
Capture the decisions, examples, and patterns worth reusing so good AI work does not disappear into chat history.
Risk and ownership gaps
See where AI work has no owner, no policy, weak evidence, low confidence, or missing data before it becomes a bigger problem.
Governed execution
Run digital workers with the customer’s chosen models, systems, memory, approvals, audit trail, and cost controls.