klipflow
The affordable AI clipper for long-form content
What it does
KlipFlow is an AI video clipping tool for long-form content (podcasts, streams, interviews). It detects highlights, generates animated subtitles, and creates short-form clips using an FFmpeg pipeline. Unlike subscription tools, it uses credit-based pricing with no expiry and discounts for longer videos. It also includes a free AI highlight detector and supports manual editing for full creator control.
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- IBI built Magiclip – an all-in-one AI studioNov 2025 · magiclip.io · ▲41
Hi HN I’ve been working on a tool I personally needed as someone who edits a lot of video content. The problem is simple: Modern video editing requires 8+ different tools, all slow, all noisy, all repetitive. Subtitles here. Audio cleanup there. Silence removal elsewhere. Upscaling in another tool. AI voice in a different one. A clip extractor somewhere else… So I built Magiclip.io — a single interface that automates the most boring parts of editing. What it does today Auto-subtitles (fast & accurate) Silence removal AI voice-over Audio enhancement Image upscaling Clip extraction from long…
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, May 2026
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Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
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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…
Life & fun · May 2026 · github.com
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Dev tools · May 2026 · github.com