Adoption & usage tracking
Track adoption, everywhere
Teams, repos, workflows, individuals. See which assistants and agents are in use, how adoption is spreading, and where it's stalling across your organization.
Adoption across teams and agents
Usage trends over time
Tool and agent comparison
Efficiency metrics
Cost per unit of work, measured
Tokens per delivery point, cost per team, cost per agent. Connect AI and agent spend to delivered output as adoption scales.
Tokens per point
Cost per unit of work
Efficiency benchmarking
Productivity impact
Separate signal from noise
Connect AI and agent usage to delivered output, weighted by magnitude and complexity. See where they actually move the needle, not just where they're active.
Delivery before and after AI
Productivity improvement analysis
Human, AI-assisted and agent contribution
Quality analysis
Faster doesn't mean fragile
Compare human, AI-assisted and agent-written code across defects, maintainability and rework traced back to whatever produced it. Prove that speed isn't costing you quality.
Agent vs AI-assisted vs human quality
Defect and rework attribution
Quality trends over time
"I can see the impact that AI is having on productivity… how much it influences the code that we're producing."
Jordi Miro
CTO, Zynap
"I'll pay for every AI tool you want. What I ask in return is: show me how you're going faster."
Andrew Eye
CEO & Founder, ClosedLoop
Does Pensero measure AI impact or just AI usage?
How is this different from per-tool AI adoption dashboards?
How does Pensero separate AI's contribution from normal team improvement?
How quickly can we start seeing useful data?
