The graph that connectsyour customers to your code.
Every customer signal, every product spec, every line of your codebase in one queryable graph. Plus the agents and automations that act on it.
Your Product Data Is Fragmented
Every product agent needs the same context - your codebase, docs, customer history, feedback. But each rebuilds its own fragmented view from 10+ scattered tools.
Knowledge Graph
One graph. Every agent connected.
10+ tools. No shared context.
How It Works
From scattered data to a traversable knowledge graph in three steps
Connect Sources
Slack, Intercom, Gong, GitHub, email - connect the tools where product signals already live.
Build the Graph
Hissuno comes with prebuilt agentic workflows that build your connected knowledge graph and enrich data intelligently.
Expose to Agents
CLI, API - your AI agents traverse the graph and query product intelligence natively.
The runtime
Skills that run when your graph changes.
Hissuno isn't a passive store. Drop a SKILL.md in your project and it runs on a trigger - new feedback, a scheduled cadence, a webhook from any connected tool - with full graph access and a sandboxed environment.
Trigger on anything
Manual, scheduled, or event-driven. New feedback tagged "bug". A Linear status change. A nightly digest. Declared in frontmatter.
Sandboxed by default
Each skill runs in an isolated environment with scoped credentials. Per-plugin tokens are injected at runtime, never in code.
Built on the graph
Skills traverse the same knowledge graph your agents use. Feedback, issues, contacts, codebase, scopes - one query away.
---
name: triage-bug-reports
description: Triage new bug feedback into Linear with codebase context
trigger:
on: feedback.tagged
filter:
tags: [bug]
capabilities:
sandbox: true
webSearch: false
---
When new bug feedback arrives:
1. Pull the feedback and linked contact.
2. Search the codebase for related modules.
3. Score impact using ARR-weighted customer data.
4. Open a Linear issue with the spec and code refs.
5. Post a summary to #product-triage in Slack.One file. Drops into your repo. Runs in production on the trigger you define.
Built-In Agents, Powered by the Graph
Production-ready agents that show what's possible when AI can traverse your entire product graph.
Your Agent, Our Data
Connect any AI agent to the graph via CLI or API. Build workflows on shared context.
Product Intelligence on Autopilot
Auto-triages feedback, creates issues, generates briefs by traversing the knowledge graph.
AI Support, Grounded in Your Product
Resolves questions using product knowledge, codebase context, and customer history.
Agent-Native Interfaces
Your agents don't need a browser. They traverse the graph directly.
$ hissuno search "checkout issues" $ hissuno list feedback --tag bug $ hissuno get knowledge KB-12
The Cost of Scattered Context
When every agent builds its own fragmented view, everyone loses.
“Our support agent couldn't answer basic product questions because the knowledge was split across 6 different tools.”
VP of Product
Series B Startup
“We built an AI copilot but it hallucinated constantly. Turns out it had no access to real customer context or product data.”
Head of Engineering
SaaS Company
“Every agent we tried needed its own data pipeline, its own context, its own integrations. We were building infrastructure instead of product.”
Engineering Lead
B2B Platform
“Our PM spent 10 hours a week copy-pasting between Slack, Linear, and spreadsheets just to understand what customers were asking for.”
Founder
Early-stage Startup
“We had customer feedback in Intercom, product specs in Notion, issues in Linear, and insights in nobody's head. Nothing was connected.”
Director of Product
Enterprise Software
“Our AI agent gave a customer completely wrong information because it couldn't access the latest product changes. We lost the deal.”
Account Executive
Growth Company
“Three teams built three different 'customer intelligence' dashboards. None of them talked to each other.”
Product Manager
Dev Tools Company
“We wanted to give Claude access to our product knowledge. It took 3 engineers 2 months to build the data layer. That's the problem.”
CTO
Fintech Startup
“Our support agent couldn't answer basic product questions because the knowledge was split across 6 different tools.”
VP of Product
Series B Startup
“We built an AI copilot but it hallucinated constantly. Turns out it had no access to real customer context or product data.”
Head of Engineering
SaaS Company
“Every agent we tried needed its own data pipeline, its own context, its own integrations. We were building infrastructure instead of product.”
Engineering Lead
B2B Platform
“Our PM spent 10 hours a week copy-pasting between Slack, Linear, and spreadsheets just to understand what customers were asking for.”
Founder
Early-stage Startup
“We had customer feedback in Intercom, product specs in Notion, issues in Linear, and insights in nobody's head. Nothing was connected.”
Director of Product
Enterprise Software
“Our AI agent gave a customer completely wrong information because it couldn't access the latest product changes. We lost the deal.”
Account Executive
Growth Company
“Three teams built three different 'customer intelligence' dashboards. None of them talked to each other.”
Product Manager
Dev Tools Company
“We wanted to give Claude access to our product knowledge. It took 3 engineers 2 months to build the data layer. That's the problem.”
CTO
Fintech Startup
“We wanted to give Claude access to our product knowledge. It took 3 engineers 2 months to build the data layer. That's the problem.”
CTO
Fintech Startup
“Three teams built three different 'customer intelligence' dashboards. None of them talked to each other.”
Product Manager
Dev Tools Company
“Our AI agent gave a customer completely wrong information because it couldn't access the latest product changes. We lost the deal.”
Account Executive
Growth Company
“We had customer feedback in Intercom, product specs in Notion, issues in Linear, and insights in nobody's head. Nothing was connected.”
Director of Product
Enterprise Software
“Our PM spent 10 hours a week copy-pasting between Slack, Linear, and spreadsheets just to understand what customers were asking for.”
Founder
Early-stage Startup
“Every agent we tried needed its own data pipeline, its own context, its own integrations. We were building infrastructure instead of product.”
Engineering Lead
B2B Platform
“We built an AI copilot but it hallucinated constantly. Turns out it had no access to real customer context or product data.”
Head of Engineering
SaaS Company
“Our support agent couldn't answer basic product questions because the knowledge was split across 6 different tools.”
VP of Product
Series B Startup
“We wanted to give Claude access to our product knowledge. It took 3 engineers 2 months to build the data layer. That's the problem.”
CTO
Fintech Startup
“Three teams built three different 'customer intelligence' dashboards. None of them talked to each other.”
Product Manager
Dev Tools Company
“Our AI agent gave a customer completely wrong information because it couldn't access the latest product changes. We lost the deal.”
Account Executive
Growth Company
“We had customer feedback in Intercom, product specs in Notion, issues in Linear, and insights in nobody's head. Nothing was connected.”
Director of Product
Enterprise Software
“Our PM spent 10 hours a week copy-pasting between Slack, Linear, and spreadsheets just to understand what customers were asking for.”
Founder
Early-stage Startup
“Every agent we tried needed its own data pipeline, its own context, its own integrations. We were building infrastructure instead of product.”
Engineering Lead
B2B Platform
“We built an AI copilot but it hallucinated constantly. Turns out it had no access to real customer context or product data.”
Head of Engineering
SaaS Company
“Our support agent couldn't answer basic product questions because the knowledge was split across 6 different tools.”
VP of Product
Series B Startup
Stop wiring context for every agent. Start shipping the loop.
Open source. One graph. One runtime. Your customers, your code, connected.