Token spend without velocity is wasted spend
Most organizations track token usage. Few understand its impact on delivery.
Seats does not equal usage. Usage does not equal productivity.
Understand which AI coding tools teams use, how deeply they are adopted, and productivity impact.
Developer token consumption is rising. Most of those tokens never ship code to production.
Identify wasted and optimizable spend, and measure cost per developer, agent, or feature.
AI ships code faster. It also ships bugs, security vulnerabilities, and tech debt faster too.
Connect AI activity to production outcomes, clearer engineering ROI, and stronger security posture.
Measure AI adoption and token consumption
Track tokens consumed by developer, team, agent, and model.
Measure AI-authored code at the commit level.
See AI-assisted PRs, acceptance rates, and code contribution.
Identify power users and ghost seats.
See whether increased token spend produces more shipped code.
Stop tokenmaxxing and reduce wasted spend
Find tokens spent on code that's abandoned, rewritten, or never shipped.
Spot expensive model choices, bloated prompts, and missed cache hits.
Compare API and token costs by developer, team, agent, or repository.
Track cost per feature, bug fix, or engineering initiative.
Separate the workflows that ship code from the ones that just burn tokens.
Track AI-generated code from prompt to production
Connect AI adoption to PR velocity, deployments, and throughput.
Track features delivered, backlog reduction, and production outcomes.
Measure quality regressions, security risk, and engineering rework.
Monitor DORA metrics, sprint health, and business alignment.
Compare delivery efficiency and output across teams.
Query, visualize, and act on engineering data
Explore adoption, spend, delivery, and engineering health using natural language.
Generate dashboards instantly without manually configuring reports or filters.
Query engineering data in real time with MCP-powered workflows and agents.
Surface bottlenecks, regressions, and optimization opportunities automatically.
One platform to measure AI spend & development impact
Track every token from prompt to production. Know which agents, teams, and workflows turn AI spend into shipped features.
Role-based access control
Control visibility and permissions across teams, business units, and engineering leadership.
Organization hierarchies
Model teams, reporting structures, and business units with metrics that roll up automatically.
Harness native integrations
Connect CI/CD, feature flags, cloud cost, security, incident, and delivery data across the Harness platform.
Out-of-the-box insights
Prebuilt dashboards for AI adoption, engineering efficiency, productivity, security, and business alignment.
Software delivery knowledge graph
A unified, real-time data layer connecting AI activity, SDLC workflows, and engineering outcomes across the Harness platform.
Custom insights with Studio
Build custom dashboards, reports, and engineering views tailored to your organization.
Insights for every role
Know if your AI bet is paying off.
See AI adoption, token spend, shipped code, and delivery performance in one view. Understand whether the engineering organization is getting faster or just more expensive.
Insights you can trust start with data you can trust
Connect your AI coding agents, source control, and delivery tools to track every prompt to every deployment.
Get started with Harness AI DLC Insights
Try Harness AI DLC free. No credit card. Full access to AI spend analytics, adoption tracking, and engineering performance insights.