Storia AI YC Application

Summer 2024Active

Storia AI went through Y Combinator in the Summer 2024 batch as a B2B company. Below: what the company does, who founded it, and its application to YC, reconstructed question by question in the real YC form.

YC batch: Summer 2024
Industry: B2BEngineering, Product and Design
Team size: 2
Status: Active
Launched: 2024

Founders

Julia TurcFounder

What Storia AI does

With AI increasingly automating away code generation, software engineers will spend more time reading, judging, and architecting code rather than writing it. Storia is building an open-source copilot that knows a company's codebase and its context. We are starting with Sage, a Perplexity-like agent for helping developers understand, judge, and generate software. Given an existing codebase, developers can ask Sage questions such as: 1) Given my project’s SLA and latency constraints, what is the appropriate underlying vector database to use? How would I incorporate it into my existing codebase? 2) Why should I pick Redis over Milvus as my underlying vector store? 3) Does this codebase in our organization still work and what steps are required for a complex integration with another library? Sage’s answers are directly supported by documentation and external references like GitHub, Stack Overflow, technical design documents, and project management software, preventing hallucinations. Today, Sage has up-to-date knowledge about open-source repositories (indexed daily). Tomorrow it will have a deep understanding of every line of code on the Internet. For teams, Sage will know about your private codebase too. No group has yet solved how to build an AI system that comprehends a codebase and its context and can empower every developer to architect better code, faster. This requires new research advances because vanilla RAG and out-of-the-box LLMs aren’t going to cut it. We have 20+ years of software engineering and AI research experience. Julia worked on precursors of Gemini using contextual neural techniques before they were called “RAG” (and applied it to products like Google Keyboard and Pixel phones). Mihail built the earliest LLMs at Amazon Alexa and launched the first contextual deep learning conversational AI system in production at Alexa.

Storia AI's YC application, reconstructed

Y Combinator application

Storia AI, Summer 2024 batch. The real form questions, answered from public data.

Founders2
Company7
Progress7
Idea4
Equity3
Curious2
Batch Preference1

Company

Company name

Storia AI

Describe what your company does in 50 characters or less.

Open source AI copilot that knows your company's code

What is your company going to make? Please describe your product and what it does or will do.

We are building Sage, an open-source AI copilot designed to help developers understand, judge, and generate software by deeply knowing their company's existing codebase and its context. Sage answers complex engineering questions by referencing documentation, GitHub, Stack Overflow, design documents, and project management tools to avoid hallucination, starting with public open-source repos and expanding to private codebases. It's made for software engineers who spend more time reading and architecting code than writing it as AI automates generation.

Where do you live now, and where would the company be based after YC?

We live in San Francisco, CA, and the company will be based here after YC.

Explain your decision regarding location.

San Francisco is where we both live and it's the center of software engineering and AI innovation, making it the natural place to build a developer-focused AI product with engineering talent and early adopter customers nearby.

21 more answers in the full application

Founders, Progress, Idea, Equity, Curious, Batch Preference are in the full version. Create a free account to open it in YC Insights, next to every other YC batch.

See full application

Frequently Asked Questions

Is this the real Storia AI YC application?

No. Y Combinator keeps submitted applications private. This is a reconstruction: the real YC form questions, answered from Storia AI's public data (launch notes, founder backgrounds, product description). It shows how a company like Storia AI would present itself to YC, not the text they submitted.