Cleo AI: The Best Product Ops Agent for AI-native & B2B Teams
One thing we kept noticing while building AI products: coding agents can generate features extremely fast, but they still don’t understand what users actually need unless someone manually translates feedback, support issues, analytics, and product discussions into actionable specs.
So we built Cleo AI at Axcelner to solve that operational gap for small AI-native B2B teams.
Cleo acts as a Product Ops agent that connects customer signals, product usage, support conversations, and team workflows into a single execution layer. Instead of manually triaging feedback across Slack, Jira, GitHub, analytics tools, and support tickets, the system continuously organizes and converts them into structured product actions.
A few things we focused on while building it:
* Converting support tickets + usage patterns into structured specs
* Automatically generating actionable Jira/GitHub tasks
* Giving coding agents richer product context before implementation
* Reducing PM overhead for fast-moving startup teams
* Keeping the loop between users, product decisions, and engineering tighter
Current integrations include GitHub, Jira, Slack, and MCP-compatible workflows.
We launched today on Product Hunt and would genuinely love feedback from founders, PMs, engineers, or anyone working on AI-native products especially around how teams are handling product operations as development becomes increasingly agent-driven.
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