Turn Your AI Spend into Faster Delivery
We trace every AI dollar to the work it shipped, find where your agents stall, and fix what slows delivery most.
Ask what your AI spend bought.
Every answer traced to your commits, tickets and AI invoices. No surveys, nothing to instrument.
Trusted by engineering teams
Five things we do every day.
Prove your AI ROI.
Measure engineering before and after AI from commit history, not surveys, and read the gain as capacity you did not have to hire.
Explore AI ROI60 engineers on payroll. $124,880 bought 56 more.
Level up AI adoption.
Every developer and team is at a different point with AI. Each gets personal guidance on what to do next, drawn from their real work.
Explore AI Adoption- Agent fluency6142614
- Delegation depth825189
- Roadmap alignment1326156
- Context leverage1023207
- Agentic autonomy2421123
Keep delivery flowing.
Coding got faster, so the bottleneck moved: to review, then process, then context. Every night an agent finds where it sits now.
Explore Agent Speed- Coding−7.0%
- Review−7.8%
- Automation−8.8%
- RoadmapFix first−13.4%
- AI cost−10.7%
Match budget to delivery.
Budget moves to the teams shipping the most per dollar, inside a total you fix. Requests are answered in seconds, by rules you set.
Explore Adaptive Token Limits- Checkout team+$4,290$84
- Search team+$1,560$93
- Growth team+$1,470$96
- Payments teamheld$121
- Platform team−$2,640$233
- Mobile team−$4,680$459
Lower your token spend.
Chameleon routes each task to the cheapest model that holds the quality bar. Work that must stay on your frontier model stays there.
Explore Token Spend Intelligence- Scaffold CRUD endpointsHaiku 4.5−94%
- Refactor auth middlewareSonnet 5−61%
- Payments architecture spikeOpus 5Held
- Incident root cause, checkoutOpus 5Held
Your history,
reconstructed.
Connect your repos and tracker. Navigara reads back through your history and sets your pre-AI baseline, so the first report compares against where you actually started.
Three numbers to know if AI tools are performing
How much more can my team ship?
Engineers of capacity the output is worth, on top of the people actually employed.
What does that capacity cost?
What one engineer’s worth of added capacity costs a month in AI spend. Lower is better.
Is that capacity on the roadmap?
How much of the output it bought lands on roadmap priorities, not just volume.
As featured in
Your code can stay exactly where it is.
Three deployment models, from fully managed cloud to air-gapped on-premises. Full security detail →
Grounded in research.500.navigara.com runs the same measurement engine, and powers the OSS Performance white paper, a study of repositories across multiple AI-forward organizations.
AI ROI · in 5 days
Prove your AI ROI in five days.
Give us read-only access. Five days later you see what AI added in capacity, what it cost, and whether the work landed on your roadmap.