hiFred is an AI‑powered copilot for product managers that ingests discovery data, Jira tickets, and design files to automatically generate and continuously update a Live Spec with acceptance criteria, edge cases, and open questions.
Funding
Funding not disclosed
Founders
Product
Problem
Product managers often spend excessive time aggregating disparate discovery data, drafting specifications, and coordinating handoffs, leading to outdated documents, missed gaps, and bottlenecks across engineering, support, and marketing teams.
Solution
hiFred is an AI‑powered copilot that reads existing product artifacts—such as interview notes, support tickets, NPS surveys, Jira tickets, and Figma designs—to surface key insights and automatically generate a “Live Spec.” The Live Spec continuously evolves as new information is added, providing up‑to‑date acceptance criteria, edge cases, and open questions. Engineers can query the spec directly within their ticketing system and receive instant answers, while the platform also creates tailored deliverables for support knowledge bases, QA test scenarios, marketing briefs, and release notes. By layering on top of tools like Jira, Confluence, Linear, Notion, Slack, and GitHub, hiFred requires no migration and keeps the team’s workflow intact.
Target Audience
hiFred is designed for product managers who lead discovery and spec creation, as well as engineers, QA, support, marketing, and sales teams that rely on accurate, up‑to‑date product documentation.
Features
- AI‑driven discovery analysis that clusters themes, ranks impact, and drafts opportunity briefs from raw user data
- Automatic generation of acceptance criteria, edge cases, and open questions by ingesting Jira tickets and linked Figma screens
- Live Spec that stays synchronized with ongoing decisions and is accessible inside the ticket workflow and Cursor editor
- Real‑time Q&A for engineers within tickets, reducing ambiguity and catching gaps before development starts
- One‑click creation of team‑specific artifacts: support KB articles, QA test scenarios, GTM briefs, release notes, and executive summaries
- Seamless integration with existing product stacks (Jira, Confluence, Linear, Notion, Slack, GitHub) without requiring data migration
- Option for private VPC deployment, ensuring data isolation for security‑focused organizations