
Flummio
AI-powered reading for families
What it does
FramerThe app identifies characters in a book and highlights their dialogue lines in customizable colors, turning reading into a shared interactive experience for families, children, and friends. Future features include: • synchronized reading across devices • AI voices for characters • collaborative reading sessions • immersive role-based storytelling
Does the same job
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- RRReadwise Reader, an all-in-one reading app2022 · readwise.io · ▲326
Hey HN, cofounder of Readwise here. We've been working on this cross-platform reader app for about 2 years, excited to finally share it in public beta. Probably the most notable thing that makes Reader unique is that it supports almost any content type you could want to save/read/highlight: * web pages * emails/newsletters * PDFs * ePubs * twitter threads * youtube videos (with transcripts) * RSS feeds With all of your knowledge content in one place, we built powerful reading and highlighting, as well as a bunch of novel triage/organization features, so you can actually…

- AOAn open-source e-book reader for conversational reading with an LLM2025 · github.com · ▲86
Hi HN! I've been working on BookWith, an open-source e-book reader that integrates AI as your reading companion. The problem: Traditional e-readers are passive. When you encounter something unclear, you have to context-switch to search for it. Your highlights and notes remain isolated, and you can't easily connect ideas across different books. My solution: BookWith embeds an AI that maintains full context of what you're reading. It features: - Context-aware AI chat: Ask questions about the current page/chapter and get instant answers - AI podcast generation: Automatically converts book…
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Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai


- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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