Akon Labs
Databricks for Enterprise Codebases
About Akon Labs
Databricks for Enterprise Codebases
Public traction evidence
Each signal links to the public source used for attribution.
- LinkedIn
Engineering teams at 184 𝗼𝗳 𝘁𝗵𝗲 𝗙𝗼𝗿𝘁𝘂𝗻𝗲 500 now uses GitNexus OSS in some capacity. We ran the numbers on who's actually using GitNexus. The reach surprised even us. We didn't chase these logos. Engineers found GitNexus, indexed their repos, and kept coming back. When we opened up the usage data, it showed just how far it had spread on its own. A few of the names in there: 𝗡𝗩𝗜𝗗𝗜𝗔 · 𝗧𝗲𝘀𝗹𝗮 · 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 · 𝗔𝗺𝗮𝘇𝗼𝗻 · 𝗜𝗕𝗠 · 𝗢𝗿𝗮𝗰𝗹𝗲 · 𝗔𝗱𝗼𝗯𝗲 · 𝗧𝗵𝗲𝗿𝗺𝗼 𝗙𝗶𝘀𝗵𝗲𝗿 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 · 𝗚𝗼𝗼𝗱𝘆𝗲𝗮𝗿 · 𝗞𝗼𝗵𝗹'𝘀 …and 174 more. The pattern is the same everywhere: the moment a codebase gets too big for any one person to hold in their head, code intelligence stops being a nice-to-have. A knowledge graph of every symbol, caller, and cross-repo dependency turns "what does this change break?" from a half-day investigation into a single query.
Engineering teams at 184 𝗼𝗳 𝘁𝗵𝗲 𝗙𝗼𝗿𝘁𝘂𝗻𝗲 500 now uses GitNexus OSS in some capacity. We ran the numbers on who's actually using GitNexus. The reach surprised even us. We didn't chase these logos. Engineers found GitNexus, indexed their repos, and kept coming back....
- LinkedIn
𝗧𝗼𝗱𝗮𝘆 𝘄𝗲 𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗲𝗱 𝗔𝗸𝗼𝗻 𝗟𝗮𝗯𝘀 𝗮𝘁 𝗬 𝗖𝗼𝗺𝗯𝗶𝗻𝗮𝘁𝗼𝗿 𝗗𝗲𝗺𝗼 𝗗𝗮𝘆. We build self-hosted knowledge graphs for enterprise codebases — think Databricks, but for code. Because our graph is deterministic, agents query logic by logic instead of file by file across thousands of repos. Massively fewer tokens, massively better performance. Open-source models start behaving like frontier models inside your own infrastructure. 1 of every 3 Fortune 500 companies already uses our open source. In 4 weeks since launch, we've converted those users into self-hosted enterprise contracts. Subham Kundu Abhigyan Patwari Zander Raycraft Abhinav Pandey …more
𝗧𝗼𝗱𝗮𝘆 𝘄𝗲 𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗲𝗱 𝗔𝗸𝗼𝗻 𝗟𝗮𝗯𝘀 𝗮𝘁 𝗬 𝗖𝗼𝗺𝗯𝗶𝗻𝗮𝘁𝗼𝗿 𝗗𝗲𝗺𝗼 𝗗𝗮𝘆. We build self-hosted knowledge graphs for enterprise codebases — think Databricks, but for code. Because our graph is deterministic, agents query logic by logic instead of file by...
- LinkedIn
AI now writes thousands of lines of code every day. Your reviewer still reads them one line at a time. That gap is the real problem. Coding agents open PRs faster than any human can absorb, and most review bots just bolt an LLM on top of the diff. Run the same PR twice and you get two different reviews, half of them noise. They see one file, one repo, one moment, and then they guess. We built GitNexus Check to be native to this new volume. It runs on the GitNexus knowledge graph, so it reviews the way your code actually connects, not the way a model happened to sample this run. That makes it deterministic: the same PR earns the same review every time, so you can put it straight in the merge path. And it is cross repo by default. Change one repo and it maps the full blast radius, showing you exactly what breaks in the others. On the Martian benchmark it ranks 3rd of 23, ahead of CodeRabbi
AI now writes thousands of lines of code every day. Your reviewer still reads them one line at a time. That gap is the real problem. Coding agents open PRs faster than any human can absorb, and most review bots just bolt an LLM on top of the diff. Run the same PR twice and you...
- YouTube
Akon Labs (YC S26) - Launch Video
Akon Labs (YC S26) - Launch Video