Navigara provides a performance layer for AI-native engineering teams. It measures pre- and post-AI throughput and the mix of feature, maintenance, and fix work from commits, then relates model and token spend to unit output cost. It also maps work to Jira objectives and roadmaps, runs nightly process checks, and generates reports to distinguish code volume from product progress.
Features
- Pre- and post-AI throughput comparison
- Work mix and unit cost
- Jira roadmap alignment
- Nightly checks and reports
Use Cases
- Evaluate coding-AI ROI
- Optimize model spend
- Check roadmap alignment
- Report engineering progress
FAQ
Navigara provides a performance layer for AI-native engineering teams. It measures pre- and post-AI throughput and the mix of feature, maintenance, and fix work from commits, then relates model and token spend to unit output cost. It also maps work to Jira objectives and roadmaps, runs nightly process checks, and generates reports to distinguish code volume from product progress. Core capabilities include: Pre- and post-AI throughput comparison, Work mix and unit cost, Jira roadmap alignment.
Common scenarios include: Evaluate coding-AI ROI, Optimize model spend, Check roadmap alignment.
