AI agents are generic.
Your codebase isn't.

Tanagram turns your team's tribal knowledge into automatic guardrailsso your AI agents code like they've actually worked here for years.

Tanagram finds patterns in your codebase that can lead to bugs, and makes sure they don't get repeated. It's built for tech leads and teams who

really really care.

Trusted by teams that ship quality at scale

across fintech, crypto, infra, and generative AI with hundreds of millions in revenue.

“Tanagram is annoying in, like, the best possible way! Every comment is a bug caught or an incident avoided, and that's massive time savings. I would say 10+ hours a week”

“Tanagram is annoying in, like, the best possible way! Every comment is a bug caught or an incident avoided, and that's massive time savings. I would say 10+ hours a week”

“Tanagram is annoying in, like, the best possible way! Every comment is a bug caught or an incident avoided, and that's massive time savings. I would say 10+ hours a week”

Staff Engineer, Series-D Gen AI firm (can't name yet)

“If Tanagram was gone tomorrow, I would be desperately sad… we would have to figure out what are we gonna do now”

CTO, Series-A Security startup

Deputy Head of Security,

Infrastructure

“If Tanagram was gone tomorrow, the work I did today would probably spill into tomorrow or even Wednesday. It’s saving me from having to go in and be like, no, no, no!”

Tech Lead, Series-A Fintech startup

Robust Foundations for Serious Engineers

Structural understanding.

Tanagram builds several different graphs of your codebase - lexical, referential, dependency, and more - and keeps them updated.

No hallucinations.

Build policies around deterministic queries, ensuring robustness and reliability.

AI in the right place.

Agentically generate queries from plain-English descriptions of what you're looking for.

Self-healing.

coming soon

Policies update themselves when your code changes.

A Letter from the Team

Why we're building Tanagram

In 2019, as a new engineer at Stripe, I built a feature for our team’s top user. We added tests, rolled it out successfully, and our user was happy.


I also set myself up for disaster.


Two years later, some other team discovered a data anomaly, and it blew up into a huge incident involving multiple state regulators and took six months to clean up. 


As it happened, I’d updated our main system, one that powered the API and user-visible aspects of this feature. Another team, millions of lines of code away, owned a different system that handled reporting. We had no idea we needed to update it too…

Read More

In 2019, as a new engineer at Stripe, I built a feature for our team’s top user. We added tests, rolled it out successfully, and our user was happy.


I also set myself up for disaster…

Read More

In 2019, as a new engineer at Stripe, I built a feature for our team’s top user. We added tests, rolled it out successfully, and our user was happy.


I also set myself up for disaster.


Two years later, some other team discovered a data anomaly, and it blew up into a huge incident involving multiple state regulators and took six months to clean up. 


As it happened, I’d updated our main system, one that powered the API and user-visible aspects of this feature. Another team, millions of lines of code away, owned a different system that handled reporting. We had no idea we needed to update it too…

Read More