Storia AI
Active · Open source AI copilot that knows your company's code and its context
Why it ranks
How the rank works- went through YCProgram · this site+4
- 2 programsMore than one program · this site+3
- team of 2Team size · YC's directory+2.5
A sum of public facts, not a judgement and not investment advice.
Competitors
| Company | Category | Status | Program |
|---|---|---|---|
| AI, Devtools | Not stated | Plug and Play | |
| AI | Not stated | Antler2023 | |
| AI, Data, Devtools | Inactive | YCW24 | |
| AI, Data, Devtools | Active | YCW22 | |
| AI, Data, Devtools | Active | YCX25 |
Adjacent
| Company | Category | Status | Program |
|---|---|---|---|
| Data, Devtools | Not stated | Seedcamp2020 | |
| Data, Devtools | Acquired | YCS15 | |
| AI, Devtools | Acquired | YCW20 | |
| AI, Data, Devtools | Active | YCS23 | |
| Devtools | Inactive | YCS12 |
Also from S24 in AI
All of S24Founders
- Julia TurcFounder/CTO
Programs
| Program | Cohort | Source |
|---|---|---|
| S24 · Summer 2024 | YC Page | |
| Inaugural cohort | AWS GenAI Page |
About Storia AI
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.
- YC batch
- S24 · Summer 2024
- Status, per YC
- Active
- Category
- AI, Developer tools
- Team size
- 2
- Location
- San Francisco, CA, USA
- Founded
- 2023
- Checked
- 7h ago
YC tags: Developer Tools, Machine Learning, SaaS, AI
Changes seen
Newly tagged AI; no longer tagged Artificial Intelligence.
Storia AI: questions
Which YC batch was Storia AI in?
Storia AI was in Y Combinator's Summer 2024 batch (S24).
Which accelerators did Storia AI go through?
Storia AI is listed by Y Combinator (S24), AWS Generative AI Accelerator (GenAI Inaugural cohort).
Is Storia AI still active?
Y Combinator lists Storia AI as active.
Who founded Storia AI?
Storia AI's founders, as listed on its YC page: Julia Turc (Founder/CTO).
Where is Storia AI based?
Storia AI lists San Francisco, CA, USA as its location on YC's directory.