Navigara connects AI coding performance directly to your engineering roadmap. Analyzing code like a senior engineer to prove real capacity gains, Navigara tracks exact costs per roadmap item, isolates off-roadmap waste, and identifies maintenance burn. Cut spend further by automatically routing routine CRUD tasks to low-cost models without sacrificing quality. Connects in minutes via Git history, JIRA/Linear, and any AI coding license for spend.
I spent years as a CTO trusting the velocity charts, cycle times, right up until I realized they were telling me a story I couldn't back up. Then a CFO asked whether Claude was producing real value for almost $150k a month or just producing invoices, and the honest answer was "we think so." Try saying that out loud while asking for a bigger token budget.
So we built Navigara. It reads your commit history, uses an LLM to understand the repo and explain what each change did, then scores how complex the merged work was. Not lines, not commits. Refactor 400 lines down to 40 and you score higher than shipping 400 more. Full methodology behind Engineering Throughput Value: https://500.navigara.com/methodology. ETV splits into Features, Maintenance, and Documentation. We measure against your team's own pre-AI baseline.
We pointed it at open source first and created a white paper about this. The result? Across the public commit history of Microsoft, Google, Cloudflare, OpenAI, Meta, and Vercel, ETV per engineer rose 116% between Q1 2025 and Q1 2026, measured across 676 contributors.
Then we noticed that a lot of the performance and code created inside companies was not aligned with the company roadmap. So the spend was high and a lot of PRs were generated, but the roadmap did not move that much faster. So we connected token spend to the roadmap (initiatives, epics, and tickets) to see what work is aligned with your roadmap, what just has a ticket without an initiative, and what is unaligned with your roadmap and put number in $ next to it.
Here’s the part I care about most: Lead engineering with data. My engineering team's ETV per engineer is up 4x against our own pre-AI baseline. We are realizing that process issues between epics, tickets, AI spend, and code are the source of teams slowing down as they grow in headcount. If you care about this too, check out “Process Checks.” It is like Sentry, but for engineering processes.
You can start a 14-day trial, or just poke around at navigara.com first. If you think we're measuring engineering wrong → That's the feedback I really want.
The great thing about building products with, you know, actual makers is that even if you can't code, startups need a decent non-agentic storyteller. Proud to be building something so important alongside such brilliant founders.
Cost per roadmap item is the number finance keeps asking for and nobody has, so this lands. One thing I'd push on: off-roadmap work isn't always waste, half the refactors that save a codebase never had a ticket. How does Navigara tell exploration apart from actual burn?
A CFO asked whether the spend was producing value and your honest answer was we think so. So you built the thing that answers it. Congrats on a strong launch day.
Tying AI infrastructure costs directly to feature roadmaps is super practical for engineering leaders tracking ROI. Great launch!
Love that Navigara reframes AI spend around actual roadmap value shipped instead of raw token usage, that is the metric engineering leaders have been missing.
Here is a detailed view of how the token spend looks when it is connected to the roadmap.
Don’t forget to check out our public data. We are updating 500.navigara.com daily.
How Top Engineering Teams Actually Perform today?
A live index of the industry's leading engineering orgs. Every commit is weighted by the work it represents, not the lines it touched, and reported as ETV per engineer.
how do you account for engineers who spend significant time mentoring, designing systems or unblocking teammates?
About Navigara on Product Hunt
“Connect Your AI Spend Directly to Your Roadmap”
Navigara launched on Product Hunt on August 24th, 2026 and earned 227 upvotes and 24 comments, earning #3 Product of the Day. Navigara connects AI coding performance directly to your engineering roadmap. Analyzing code like a senior engineer to prove real capacity gains, Navigara tracks exact costs per roadmap item, isolates off-roadmap waste, and identifies maintenance burn. Cut spend further by automatically routing routine CRUD tasks to low-cost models without sacrificing quality. Connects in minutes via Git history, JIRA/Linear, and any AI coding license for spend.
Navigara was featured in Analytics (173.4k followers), Developer Tools (518k followers) and Artificial Intelligence (476.7k followers) on Product Hunt. Together, these topics include over 212.8k products, making this a competitive space to launch in.
Who hunted Navigara?
Navigara was hunted by Ben Lang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Navigara stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ben Lang
Hey, Product Hunt ✋,
I'm Jirka, co-founder of Navigara.
I spent years as a CTO trusting the velocity charts, cycle times, right up until I realized they were telling me a story I couldn't back up. Then a CFO asked whether Claude was producing real value for almost $150k a month or just producing invoices, and the honest answer was "we think so." Try saying that out loud while asking for a bigger token budget.
So we built Navigara. It reads your commit history, uses an LLM to understand the repo and explain what each change did, then scores how complex the merged work was. Not lines, not commits. Refactor 400 lines down to 40 and you score higher than shipping 400 more. Full methodology behind Engineering Throughput Value: https://500.navigara.com/methodology. ETV splits into Features, Maintenance, and Documentation. We measure against your team's own pre-AI baseline.
We pointed it at open source first and created a white paper about this. The result? Across the public commit history of Microsoft, Google, Cloudflare, OpenAI, Meta, and Vercel, ETV per engineer rose 116% between Q1 2025 and Q1 2026, measured across 676 contributors.
Then we noticed that a lot of the performance and code created inside companies was not aligned with the company roadmap. So the spend was high and a lot of PRs were generated, but the roadmap did not move that much faster. So we connected token spend to the roadmap (initiatives, epics, and tickets) to see what work is aligned with your roadmap, what just has a ticket without an initiative, and what is unaligned with your roadmap and put number in $ next to it.
Here’s the part I care about most: Lead engineering with data. My engineering team's ETV per engineer is up 4x against our own pre-AI baseline. We are realizing that process issues between epics, tickets, AI spend, and code are the source of teams slowing down as they grow in headcount. If you care about this too, check out “Process Checks.” It is like Sentry, but for engineering processes.
You can start a 14-day trial, or just poke around at navigara.com first. If you think we're measuring engineering wrong → That's the feedback I really want.
Jirka