Devplan
Devplan is an AI-native product management platform that connects to a company's existing tools—including GitHub, Slack, Jira, Linear, and Zendesk—to automatically build a shared, evidence-based product context. It generates role-specific daily digests, auto-updating project statuses, and grounded PRDs and specs, while providing MCP integration so AI coding agents like Claude Code and Cursor access the same context. The platform ranks customer requests by demand and impact, helping teams ship what customers actually pay for.
- Artificial Intelligence
- Enterprise Software
- AI Agents
- Software Only
- Data & Analytics
- Developer Tools
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
AI has accelerated execution but not coordination, leaving teams drowning in status reports, sync meetings, stale project docs, and endless Slack threads. This "work about work" consumes significant team time and creates a gap between what actually happens in the codebase and what stakeholders believe is happening, leading to misaligned priorities and delayed risk detection. Customer signals get lost across calls, tickets, Slack, and docs, so decisions stall and features ship late.
Solution
Devplan connects to an organization's existing stack—including GitHub, Slack, Linear, Zendesk, and other tools—and automatically transforms every signal into shared understanding for humans and agents. The platform's core technology, Weaver, builds and maintains a persistent context graph that maps the complete product catalog, continuously indexes all connected sources, and generates evidence-based insights. Each morning, Devplan delivers role-specific Daily Digests to Slack or email, surfacing action items, risks, changes, and decisions tailored to PMs, engineering managers, and executives. The system also generates automated project status updates directly from commits, meeting notes, and ticket movements, with no manual input required. Every claim in the system is backed by explicit evidence references, ensuring no hallucinations and maintaining trust across the organization. Devplan also ranks customer requests by demand and impact, writes PRDs and specs grounded in code and customer evidence, and provides MCP integration so AI coding agents (Claude, Codex, Cursor) access the same product context.
Target Audience
Primary users are product managers, engineering managers, and executives at software development organizations who need accurate, up-to-date product intelligence without manual status reporting. The platform also serves sales, customer success, support, and marketing teams, as well as AI agent developers and automation workflows that require structured, evidence-based product context.
Features
- Daily Digest: Role-specific morning briefings delivered to Slack or email, highlighting changes, risks, decisions, and action items relevant to each user's role
- Automated Project Status: Self-updating project reports generated from commits, meeting notes, and ticket movements, with requirements automatically checked off when satisfied
- Ask Devplan: Natural language query interface for both humans and AI agents, providing traceable answers with evidence chips linking back to source items; up to 6x faster and 4.5x lower model cost than MCP queries with Claude
- Weaver Context Graph: Persistent knowledge graph that maintains a complete, continuously updated map of the product, connecting cross-repository functionality and enforcing evidence-based claims
- Multi-agent extraction flows: Programmatic guarantee that every signal from connected sources is processed and captured, mitigating AI's probabilistic nature
- Security and access control: Agents run under independent agentic identities with granular permissions, ensuring users only see information they are authorized to access
- Evidence enforcement: Every fact in the graph must point to specific source items (PRs, tickets, meeting notes), with assumptions and suggestions clearly labeled separately from facts
- MCP integration: Supports AI agents querying product context via Model Context Protocol for automated workflows, working with Claude Code, Cursor, and Codex
- Integrations: Slack, Microsoft Teams, Jira, Linear, Zendesk, Intercom, HubSpot, Salesforce, GitHub, Bitbucket, Zoom, Granola, Notion, Confluence, Google Drive