#1 AI Transformation Platform for Engineering
We trace every AI dollar to what your engineering team ships, find where your agents stall, and fix what slows delivery most.
Ask about your AI spend.
Trusted by engineering teams
AI transformation never stops.
Your engineers ship faster with AI, but costs are climbing, and the board demands proof of AI ROI. Navigara ties AI coding costs to AI engineering productivity, so you can show whether your AI coding costs moved your business goals.
Prove your AI ROI.
Turn AI engineering productivity into a number finance reads: the capacity AI added, what your AI coding costs paid for it, and the AI ROI per added engineer.
Explore AI ROI350 engineers on payroll. $226,900 bought 326 more.
Cut AI coding costs.
Chameleon sends each coding task to the cheapest model that clears your quality bar. Token budgets move to the teams shipping the most per AI dollar, inside a total you fix. Compare AI coding costs by team, then decide which work stays on the frontier model.
Explore Token Spend IntelligenceExplore Adaptive Token Limits- Scaffold CRUD endpointsHaiku 4.5−94%
- Refactor auth middlewareSonnet 5−61%
- Payments architecture spikeOpus 5Held
- Incident root cause, checkoutOpus 5Held
Drive AI adoption.
Measure how each developer uses AI through commits and tickets. Each person gets one next step, so AI engineering productivity can grow team by team.
Explore AI Adoption- Agent fluency358215182
- Delegation depth4714610552
- Roadmap alignment761528735
- Context leverage5813411741
- Agentic autonomy1401237017
Keep delivery flowing.
Every night an agent finds where your bottleneck sits now: review, process, or context. Then it names the one fix that does the most for AI engineering productivity.
Explore Agent Speed- Coding−7.0%
- Review−7.8%
- Automation−8.8%
- RoadmapFix first−13.4%
- AI cost−10.7%
As featured in
Your pre-AI baseline,
rebuilt from Git.
Connect your repositories and Navigara reads back through years of commits. You get the pre-AI baseline every AI ROI calculation starts from, plus your AI engineering productivity since.
Your code can stay exactly where it is.
Three ways to deploy, from managed cloud to air-gapped. 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 coding costs, AI ROI, and AI engineering productivity questions.
What do AI coding costs tell us about delivery?
On their own, very little. AI coding costs show what the tools charged. Set them beside the work they funded (features, maintenance, fixes, roadmap objectives), and you see where your AI ROI comes from.
How do we calculate AI ROI for engineering?
Start from your pre-AI baseline. Navigara measures the change in AI engineering productivity since then and divides your AI coding costs by the capacity gained. Treat the result as evidence for a budget conversation; booked profit and headcount are separate questions.
Can we review AI coding costs before changing models?
Yes. Navigara measures AI engineering productivity from repository history and tracker context, and reads your provider bills, without touching the request path. Chameleon routing is a separate opt-in to test later against your own quality rules.
How does AI adoption affect AI engineering productivity?
Navigara scores how each developer works with agents, then checks whether AI engineering productivity moved for the same people. When costs rise and throughput stays flat, the read-out shows which skill or process is holding your AI ROI down.
What should we check before raising an AI budget?
Check the team’s AI engineering productivity, work mix, and priorities over the same period as its AI coding costs, then set the budget rule. Adaptive limits start in review mode, so a person approves every change until you trust the rules.
Where do we start measuring AI engineering productivity?
Pick one reporting period, the repositories and teams it covers, and the provider bills for the same months. Navigara rebuilds your baseline from Git history and shows your AI ROI within five days. Explore AI coding costs by team.
AI ROI · in 5 days
Prove your AI ROI in five days.
Give us read-only access. In five days, you’ll see how AI engineering productivity changed, your AI coding costs by team, and where the work landed on your roadmap.