Potpie AI has raised $2.2 million in pre-seed funding to develop a foundational context layer that allows AI agents to reason and act across large, interconnected codebases with the depth and reliability of experienced engineers. The round was led by Emergent Ventures, with participation from All In Capital, DeVC, and Point One Capital. The capital will support early enterprise deployments, team expansion, and continued development of Potpie’s core context and agent infrastructure.
Modern codebases have grown far beyond what traditional tools or even senior engineers can easily comprehend. Context is fragmented across repositories, issue trackers, logs, documentation, and institutional knowledge, making safe and reliable AI agent operation nearly impossible. Potpie solves this by automatically building and maintaining a dynamic, ontology-first model of the entire engineering ecosystem—linking code behavior, architectural intent, historical changes, and operational signals into a single, agent-accessible foundation.
Aditi Kothari, CEO and co-founder of Potpie said, “As AI makes code generation easier, the real challenge shifts to reasoning across massive, interconnected systems. Potpie is our answer to that shift, an ontology-first layer that helps enterprises truly understand and manage their software.”
Anupam Rastogi, Managing Partner at Emergent Ventures said, “In large enterprises, the real challenge is not generating code, it is understanding the system deeply enough to change it safely. Potpie’s ontology-first architecture, combined with rigorous context curation and spec-driven development, creates a structured model of the entire engineering ecosystem. This allows AI agents to reason across services, dependencies, tickets, and production signals with the clarity of a senior engineer. That is what makes Potpie uniquely capable of solving complex RCA, impact analysis, and high-risk feature work even in codebases exceeding 50 million lines.”
Potpie shifts AI from surface-level code completion to system-level reasoning. Agents use the platform’s structured artifacts to plan features holistically, anticipate downstream impacts, and generate production-ready code with built-in safeguards. The system continuously updates context as code evolves—auto-generating documentation from pull requests, inferring designs from tickets, and maintaining behavioral definitions for agents—ensuring consistency and reducing drift over time.
Early deployments demonstrate significant impact. One customer with a 40-million-line codebase reduced production issue root cause analysis from nearly a week to about 30 minutes, shifting engineers from investigators to reviewers. Another team maintaining decades-old systems used Potpie to automate test updates in the background, compressing multi-sprint efforts into much shorter cycles.
Founded in October 2023 by Aditi Kothari and Dhiren Mathur, Potpie launched publicly in January 2025 after nearly two years of building its core knowledge graph infrastructure. The company now works with Fortune 500 and publicly listed enterprises in regulated sectors, where safe, explainable AI operation is non-negotiable.
About Potpie
Potpie is a foundational context layer that allows AI agents to operate across complex, large-scale codebases the way experienced engineers do. Potpie pulls in information from source code, tickets, logs, documentation, and reviews, links it together, and makes it usable by agents. In doing so, Potpie is unifying context across the entire engineering stack and enabling spec driven development.
TechIntelPro empowers B2B technology decision-makers with the latest industry trends, deep insights, leadership perspectives and actionable intelligence to drive both organizational and professional milestones—and thrive on the tech pulse.