Hissuno is built on four foundational systems that work together to turn raw customer feedback into structured, actionable product intelligence. Each system handles a different part of the pipeline - from organizing data to discovering connections automatically.

Knowledge Graph

Every entity in Hissuno - sessions, contacts, issues, scopes, knowledge sources, and companies - is a node in an interconnected knowledge graph. Agents traverse these relationships to build real understanding, assembling full context from multiple entity types in a single query.

Scopes

Scopes define what your product is. They come in two types - areas (permanent product domains) and initiatives (time-bound efforts) - and each can have specific goals. Scopes give agents a structured product understanding beyond raw data.

Embeddings

Every session, issue, contact, and knowledge chunk gets a vector embedding that captures its semantic meaning. These embeddings power deduplication, semantic search, and relationship discovery across the entire graph.

Graph Evaluation

An AI pipeline that automatically discovers relationships between entities whenever new data enters the system. It extracts topics, runs six parallel discovery strategies, and classifies entities against scope goals - connecting feedback to the right product areas without manual triage.

Built-In Intelligence

Hissuno ships with agents and automation flows that deliver value on top of the knowledge graph.

Support Agent

A customer-facing AI that answers questions using your knowledge graph. It retrieves relevant knowledge packages, past conversations, and product context to generate grounded responses. Deploy it via the embeddable widget or Slack.

See Support Agent for configuration details.

Product Co-Pilot

A team-facing AI assistant for PMs, founders, and engineers. Available in-app (sidebar), via Slack, or through MCP (Claude Desktop, Cursor). It has full access to project data and can query issues, search feedback, and explore the knowledge graph conversationally.

See PM Copilot for capabilities and usage.

Automation Flows

Feedback Triage - When a customer session closes, the review workflow automatically classifies the conversation, links it to contacts and scopes via graph evaluation, searches for duplicate issues, and decides whether to create a new issue, upvote an existing one, or archive.

Issue Analysis - When an issue is created or upvoted, the analysis workflow gathers all linked sessions and customer context, analyzes technical impact and effort against the codebase, computes priority scores, and generates a product spec when configurable thresholds are met.

Both flows run automatically. The graph evaluation pipeline connects each piece of feedback to the right scope, related entities, and existing issues - closing the loop from customer signal to product action.

Core Concepts