Devplan raises $2.5M to build an intelligence coordination layer for product development

Devplan Inc., a company building an intelligence layer for product development, today emerged from stealth with $2.5 million in seed funding led by AI2 Incubator.

Acequia Capital, Mighty Capital, Grand Ventures and eLab Ventures also participated in the funding round.

Devplan focuses on providing companies with a way to handle the dramatically increased speed provided by artificial intelligence-assisted software development in product development. The integration of AI into product streams has provided a paradigm shift for accelerating software creation. But the company argues it has not given way to an equivalent shift in coordination.

Product and engineering companies currently spend hours gathering context, tracking progress, aligning teamwork and communication, making decisions and trying to handle increasingly fragmented tools. Devplan cited the Atlassian State of Teams 2026 report to show that Fortune 500 companies spend $161 billion annually reconciling this fragmentation.

“After two decades leading product and engineering teams, I watched talented people lose half their week to coordination work that never resulted in a customer-facing update,” said co-founder and Chief Executive Chris Bee.

Founded in 2025, Devplan tackles this problem with what the company calls an “intelligence layer” for AI-native product development.

Its product intelligence engine, Weaver, connects to all the tools that developers and product engineers use, including GitHub, Jira, Linear, Slack, Notion, Google Workspace, meeting notes and customer feedback, creating a shared knowledge graph.

Knowledge graphs are a well-known industry tool used by intelligence layers to produce relationship representations of entities to enable both humans and machines to understand, reason and extract insights from complex, interconnected data. Unlike traditional flat and relational databases, which can struggle with highly connected datasets, knowledge graphs are becoming a best practice for querying networks of diverse information.

Devplan said in a survey of early users and product managers, it received a report that they saved eight hours per week on coordination work. Additionally, internal benchmarking against a standard Claude configuration connected via Model Context Protocol showed that moderately complex queries took only about six minutes and cost $1.75. With its platform, the cost was reduced to two minutes and 56 seconds and a cost of 54 cents. Almost two times faster and more than three times cheaper.

The competitive landscape for coordination, especially in the wake of AI agents, which act like additional people, has been filling up. Big players include Atlassian Corp. Plc. itself and its AI agent Rovo, which coordinates between a multitude of contexts – using the company’s own report to speak to product is certainly a clever move; Snowflake Inc. and CoWork with enterprise data and GitHub Copilot that focuses on code.

The category exists, but Devplan doesn’t fit neatly into any one part. The company’s vision is to provide product management with coordination, visibility and productivity – something that the coding side is already receiving from AI.

The company said Axiad IDS Inc., an identity security company and dozens of other companies that focus on engineering, product and customer feedback.

With this new funding, the company intends to expand its own engineering and go-to-market efforts, while actively seeking to partner with leaders seeking to embed AI into their core business operations.

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