FragmentFeedback: Contextual AI Interviews for AI Product Positioning

Trace [https://gettrace.vercel.app/](https://gettrace.vercel.app/) We’re building a system for conversational product feedback. Instead of static forms, Trace runs adaptive interviews that ask follow-up questions in real-time, then extracts recurring themes, friction points, and recommendations across conversations. One thing we noticed while building this: people often give shallow “everything was fine” answers in forms, but reveal much more actionable detail once follow-up questions start happening naturally. Technologies Used: Next.js, AI/LLM workflows, vercel aisdk Feedback Requested: Would mainly love feedback on the positioning and onboarding flow. Big question we’ve been struggling with: Does this currently feel more like: * a survey/form tool * a research tool * or a product decision system? We’ve realized those are very different categories and are trying to make the value clearer. Also curious whether the conversational examples on the landing page make the product “click” fast enough. Seeking Beta-Testers: Yes Additional Comments: Still early and actively iterating. Happy to trade feedback with other founders in this thread too.

**Company name:** Appish **URL:** [https://appi.sh](https://appi.sh) **Purpose:** One `docker push` turns your AI-made prototype into a live demo URL - no repo, no YAML, no CI, no dashboard to learn. Built for PoCs, demos, and quick concept validation. **Technologies used:** .NET, Docker Swarm, Tailwind, Supabase, Cloudflare. **Feedback Requested:** - **Landing page** ([appi.sh](https://appi.sh)) - does the value prop land in 5 seconds or do you bounce? - **Onboarding flow** - sign up, try to push something, tell me where it gets confusing or breaks. - **Positioning** - does "AI-made prototype" resonate, or am I describing the wrong audience? **Seeking Beta-Testers:** Yes - actively looking for 10-20 users who'd actually push an image and report back. **Additional Comments:** First testers from this thread get **1 year free on paid tier + founding-user credit** in exchange for honest feedback. Happy to return the favor - drop your link below and I'll give your product specific written feedback within 24h.

**Company name**: Fragment **URL**:https://app.fragment.fit/signup **Purpose of Startup and Product**: Fragment helps product builders figure out what to build, from early idea to validated feautres. It analyzes your customer data and company context so you can validate ideas against real feedback and analytics, brainstorm solutions with our agents, and turn business goals into specs ready to prototype. AI doesn't know your customers. Fragment does. **Technologies Used**: Next.js, Multi-agent systems, MCP **Feedback Requested**: 1. **Onboarding** \- Sign up and tell me where you got stuck or confused and what worked well. 2. **Overall experience** \- Spend some time with your own data. What worked, what didn't, what surprised you? 3. **Real use** \- Would you use this at work today? For what, exactly? 4. **In your words** \- After using it, how would you describe Fragment to a colleague or your boss? **Seeking Beta-Testers**: Yes. If you're a Product builder in B2B SaaS/ AI with active customers, DM me and I'll comp Pro for a month for up to 5 seats. I want real honest feedback. **Additional Comments**: Happy to return the favor 😄 Drop your link in the replies and I'll give you the same kind of honest feedback I'm looking for. Appreciate your time and help!

Company Name: AetherX URL: https://aetherx.ai Purpose of Startup and Product: Professional memory infrastructure. Passively captures everything you work on across email, calendar, meetings, and documents, connects it over time, and deploys agents that act on your context with your approval. Everything you’ve ever worked on, always with you. Technologies Used: Knowledge graph, hybrid retrieval, local-first architecture, MCP server, desktop, iOS app, Chrome extension. Feedback Requested: Onboarding experience, product UI, retrieval quality, and whether proactive context surfacing feels genuinely useful in practice. Seeking Beta-Testers: 20 more alpha spots open. Looking for AI-native professionals who have felt the context re-explaining problem and have tried Obsidian, Notion, a second brain system, or interested in AI chief of staff.