Potpie AI Secures $2.2M for Engineering Agents

Potpie AI has secured $2.2 million in pre-seed funding, aiming to bridge the gap between AI agents and complex, real-world engineering systems. The San Francisco-based startup is building a foundational context layer designed to enable AI agents to operate across vast, intricate codebases with the same understanding as experienced human engineers.

Modern software development, while accelerating, wasn't designed for AI agents. Codebases often span millions of lines, critical context is scattered across numerous tools, and vital knowledge remains siloed within senior engineering teams. Potpie seeks to unify this fragmented landscape, making AI agents genuinely useful in these challenging environments.

This round will support early enterprise deployments and expand the engineering team.

Unifying Context for Intelligent Agents

Most current generative AI tools for code focus on surface-level generation, largely ignoring the deeper challenge of context. Without access to system-level understanding, tooling history, and architectural intent, large language models struggle in production. Potpie addresses this by pulling and linking information from source code, tickets, logs, documentation, and reviews across the entire engineering stack.

With Potpie, the specification becomes the source of truth, not merely existing code. Agents first plan features end-to-end, converting requirements into clear implementation plans, mapping dependencies, and aligning tests before writing any code. The platform’s effectiveness hinges on the information agents can access and the tools they can utilize. Potpie optimizes both.

Potpie’s foundational context layer unifies data from across the engineering stack, enabling AI agents to operate with system-level understanding.

"As AI makes code generation easier, the real challenge shifts to reasoning across massive, interconnected systems," said Aditi Kothari, CEO and co-founder of Potpie. "Potpie is our answer to that shift, an ontology-first layer that helps enterprises truly understand and manage their software."

Enterprise-Grade Automation

Potpie enables high-impact automation across the software development lifecycle, including debugging cross-service failures, maintaining end-to-end tests, blast radius detection, and system design. Designed for enterprise companies with codebases exceeding one million lines, it builds a graphical representation of software systems, infers patterns, and creates structured artifacts for consistent, safe agent operation.

The platform actively creates context as systems evolve. It can automatically update documentation and tickets from pull requests, generate system designs from new tickets, and produce release notes upon shipment. Potpie generates Agent.md files to define agent behavior and builds a searchable index across APIs, services, and databases, enhancing reliability.

Founders Aditi Kothari and Dhiren Mathur began tackling this problem in October 2023. They recognized that developers faced a fundamentally different challenge than knowledge workers: code is non-linear, deeply interconnected, and spread across large systems. They spent nearly two years building the core knowledge graph before Potpie's public launch in January 2025.

Early deployments demonstrate Potpie’s impact. One customer with over 40 million lines of code reduced root cause analysis for production issues from nearly a week to approximately 30 minutes. Engineers shifted from investigators to reviewers. Another client, managing decades-old hardware-integrated systems, used Potpie to update and generate tests, compressing multiple sprints of work into a shorter cycle.

Anupam Rastogi, Managing Partner at Emergent Ventures, highlighted the core value: "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."

Potpie currently partners with Fortune 500 and publicly listed companies in regulated industries like healthcare and insurtech. Its open-source projects have garnered over 5,000 stars on GitHub, attracting significant enterprise interest.

"AI readiness is not about picking the right model," Kothari added. "It’s about building systems that can support intelligence over time. Our goal is to make Potpie the foundational layer engineering teams rely on to build, operate, and evolve complex software with AI built in from the start."