Agent Performance Analytics & ROI Dashboard
Agent Performance Analytics & ROI Dashboard
The ROI Dashboard gives you a business-level view of what your SaaS Factory agent fleet is delivering. Where the technical observability panels show system health, this dashboard answers the question: is autonomous development paying off?
Overview
SaaS Factory already tracks agent job token usage and credit consumption at the infrastructure level. The ROI Dashboard surfaces that raw data as executive-ready value metrics — the same kind of numbers that companies like Nubank (20× cost savings), Cursor (80% adoption among top YC builders), and EY (5,000-engineer deployment) use to justify AI development investments.
Dashboard Metrics
Features Shipped per Week
A rolling time-series showing the number of features completed and merged through the full pipeline each week. Useful for tracking development velocity over time and identifying periods of high or low throughput.
Hours Saved vs. Manual Development
An estimated displacement metric calculated from token usage, task complexity, and pipeline execution time. Provides a human-hours equivalent for the work performed by the agent fleet.
Value Delivered per Credit Spent
A cost-efficiency ratio that divides measurable output (features shipped, PRs merged, tests passed) by the total credits consumed. Helps operators identify which pipelines and agent configurations deliver the best return.
Pipeline Success Rate Trends
Historical charts of pass/fail rates across CI jobs, PR merges, and deployment workflows. Breaks down success rates by pipeline stage so you can pinpoint where failures cluster.
Agent Job Token Usage
Per-agent and per-pipeline token consumption over time. Useful for capacity planning and for identifying runaway jobs that consume disproportionate resources.
Credit Consumption Breakdown
A granular view of credit spend across the agent fleet — segmented by agent type, pipeline, and time period. Helps allocate costs back to specific products or workstreams.
Relationship to Technical Observability
The ROI Dashboard is a separate layer on top of the existing technical observability components (observability-stat-card and fleet-observability). Those panels remain unchanged and continue to provide low-level system health data (queue depth, error rates, job status). The ROI Dashboard is additive — it reads the same underlying data and presents it through a business-value lens.
| View | Focus | Audience |
|---|---|---|
| Fleet Observability | System health, job status, error rates | Platform engineers |
| ROI Dashboard | Business value, cost efficiency, velocity | Engineering leaders, finance, enterprise buyers |
Data Sources
No additional instrumentation is required. The dashboard consumes data already captured by the platform:
- Agent job logs (token counts, duration, outcome)
- Credit ledger (consumption per job and per agent)
- Pipeline event history (CI results, PR merge events, deployment records)
Use Cases
Internal reporting Share weekly feature velocity and hours-saved figures with engineering leadership or a board.
Enterprise procurement Provide cost-per-feature and ROI ratio data to procurement teams evaluating or renewing a SaaS Factory contract.
Pipeline optimization Use the value-per-credit and success-rate trends to identify underperforming pipelines and tune agent configuration.
Budget planning Use credit consumption breakdowns to forecast spend as the agent fleet scales.