Kasava
Kasava is an AI-native workspace that unifies code repositories, customer call transcripts, and product documentation into a single queryable product graph. Product managers and engineers can chat with the graph to get cited answers, generate PRDs from call transcripts, and push plans directly to Linear, Jira, or GitHub. The platform uses code-trained embeddings and traces every model call for credit-based billing.
- Artificial Intelligence
- AI Agents
- Developer Tools
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Engineering and product teams struggle to stay aligned across fragmented tooling: code lives in GitHub, customer feedback in Gong calls, and planning in Linear or Jira. Finding what shipped, why it shipped, and what customers actually asked for requires manual context-switching across multiple platforms, leading to stale documentation, duplicated effort, and a slow path from customer signal to shipped feature.
Solution
Kasava provides an AI-native workspace that ingests repositories, customer call transcripts, and product docs into a single parsed product graph. Users can chat with the graph to get cited answers, ask for weekly narrative summaries of shipped work, and generate PRDs from call transcripts or code context. Drafted plans push directly to Linear, Jira, or GitHub, and specs can be handed off to coding agents like Claude Code. Every claim is grounded in a file, commit, or quote, so output doesn't hallucinate function names or PR numbers.
Target Audience
Product managers, engineering leads, and technical founders at software companies who need to translate customer feedback and code activity into product decisions and shipped features. The platform is built for teams already using GitHub, Linear, Jira, and Gong in their daily workflow.
Features
- Product Graph: one index that parses repos, Gong calls, Notion docs, and Linear issues, with auto-discovery of components and call patterns without YAML configuration
- Interactive Chat: @mention a file, Linear issue, or Gong call and receive answers that quote the exact source with file paths and line numbers
- Narrative weekly summaries: groups PRs by actual feature area and writes plain-English summaries instead of commit lists
- Plan Generation: draft PRDs with problem statements, impacted segments, and evidence quotes, then push epics and tickets to Linear, Jira, or GitHub
- Research clustering: groups recurring customer asks and bugs from Gong transcripts by meaning, and scores feature ideas on impact and effort
- Competitor monitoring: scheduled re-scans of competitor URLs that cross-references changes against customer call mentions
- @kasava mentions: cited replies directly inside GitHub, Linear, Jira, and Notion threads without context-switching
- Architecture map: self-updating diagram of how components connect, regenerated on every PR
- Three-axis classification: slices the same codebase by architecture, feature area, team ownership, and customer impact
- Code health and drift detection: surfaces which components are actively shipped versus accruing tech debt