"Building the future of coding."
TL;DR: Storia helps engineering teams understand, analyze, and generate software with their codebases.
Founded by Mihail Eric & Julia Turc
They 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.
👎 The Problem: <5% of software teams use AI code understanding and generation systems
Despite all the hype around AI coding following the release of GitHub Copilot, a disappointingly small percentage of engineering teams have actually adopted AI assistants into their developer workflows. Why?
What developers don’t like about systems today:
- Code search is not accurate enough, slowing dev velocity.
- Code assistants are not grounded in their team’s codebase, so they lack the necessary context to produce useful and high-quality answers.
- Code outputs can be incorrect due to hallucination which strains dev patience and trust
🚀 The Solution: A contextual AI pair programmer built for any team’s codebase
They’re building Sage, a Perplexity-like agent for helping developers understand, analyze, and generate software. Given an existing codebase, developers can ask Sage questions such as:
- For 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?
- Why should I pick Redis over Milvus as my underlying vector store?
- Does this codebase in our organization still work, and what steps are required for an integration with another library?
A few of the features Sage supports:
- They index repos daily, providing users with the most up-to-date info about how to use a library (no stale, deprecated API definitions),
- They have a Perplexity-like focus on citing the source of every generated line of code, enhancing developer trust.
- They've developed algorithms grounded in research for syntactic and semantic understanding of a codebase so that they can provide more relevant context and use it effectively given a user query.
They are now actively working with seed to series C partner companies to help them integrate Sage into their developer workflows.
🌅 The Opportunity: Making every engineer on a software team a 10x developer
There are ~28M developers worldwide. Github Copilot is the frontrunner in AI assistant tooling and reached $100M ARR in 2 years, which is only a small percentage of the $913B spent on software development in 2023.
Learn More
🌐 Visit storia.ai to learn more.
🌱 They’re still onboarding a closed group of beta partners to integrate with Sage. Intros to engineering leaders (VP of engineering, Head of Engineering, CTO) at Seed-Series C companies would be appreciated!
