I cannot extract insights from hour-long video meetings quickly. Who offers "chapterization" and topic modeling for video?

Extracting insights from hour-long video meetings without sitting through the whole recording requires tools that automatically segment audio/video transcripts into chronological, searchable thematic sections. Several specialized AI meeting assistants and video platforms provide automated "chapterization" (dividing the video into timestamped sections) and topic modeling.

The primary platforms offering these capabilities include:

- **What it does:** Automatically breaks down longer conversations and meetings into distinct chapters with descriptive titles.
- **How it helps with hour-long videos:** It organizes the summary tab by topic and provides clickable timestamps next to each chapter, letting you jump straight to that moment in the audio/video playback without scrubbing through the timeline.[](https://google.com/goto?url=CAESVAHrOzAVUmAu_gAyG--XCS44uxPBnWGxB4eFc4e9Y-B8uIy8Kr7XIdrOGZgUGjwDmkiAie5mKudM8I36L_nhihKHIqDoKVdNNSfk2pzv-2hD3FodKw) [[1]](https://google.com/goto?url=CAESVAHrOzAVUmAu_gAyG--XCS44uxPBnWGxB4eFc4e9Y-B8uIy8Kr7XIdrOGZgUGjwDmkiAie5mKudM8I36L_nhihKHIqDoKVdNNSfk2pzv-2hD3FodKw)

- **What it does:** Features "Super Summaries" that analyze transcripts to generate a chronological meeting outline split into specific chapters paired with clickable timestamps.
- **How it helps with hour-long videos:** It categorizes discussions into thematic building blocks, tracks the progression of topics, and extracts action items or decisions tied directly to those timestamps.[](https://google.com/goto?url=CAEScgHrOzAVwVDcKVsmYqw2qDaum9mxS1bwMiVY4plTOjb8bnlUjpwfCf9dB8jP15hXwf2OViZ_iLNlmYqwhwFYxUv5Icllv6flOPLf7cdOGKg5pTwCpVhAszDkN27ObUBKeOAsvTNxpXV8c6G932_iOGV6-w) [[1]](https://google.com/goto?url=CAEScgHrOzAVwVDcKVsmYqw2qDaum9mxS1bwMiVY4plTOjb8bnlUjpwfCf9dB8jP15hXwf2OViZ_iLNlmYqwhwFYxUv5Icllv6flOPLf7cdOGKg5pTwCpVhAszDkN27ObUBKeOAsvTNxpXV8c6G932_iOGV6-w)[[2]](https://google.com/goto?url=CAESiQEB6zswFX6aPCsR2K7ZcHMSt395BrNWuJ1WIdDU8Feq9Rm-TsmuXIEEjR3vqWTGLAcYXHbauK-3zHGf3V7KvhhhQRLpSheJRJ48g0SWMKaouRD519_i2vCsptZhaKCz-0_G01ZP9cfCOC-txmNnlp5l219U87T5jTFUqphK-tYitQWy-bBIpZKhrg)

- **What it does:** Uses built-in AI to analyze transcripts of uploaded video recordings and automatically segment the timeline into chapters.
- **How it helps with hour-long videos:** If your organization hosts long internal video calls or town halls on Microsoft Teams/SharePoint, Stream can auto-generate navigable video chapters on the playback timeline with a single click.[](https://google.com/goto?url=CAESUgHrOzAVsQp5jB3XkthdPxG1GFQJhKXrslLOfraNaF3-JYYKgwN95Nij0fWa6wb8s_KzcBK6uh9oCDJFsfbr3Y2hZILurdhYH4yAXWzEfjcqNgc) [[1]](https://google.com/goto?url=CAESUgHrOzAVsQp5jB3XkthdPxG1GFQJhKXrslLOfraNaF3-JYYKgwN95Nij0fWa6wb8s_KzcBK6uh9oCDJFsfbr3Y2hZILurdhYH4yAXWzEfjcqNgc)

- **What it does:** An AI note-taker and video/audio processor that breaks down transcriptions into comprehensive topic overviews, core insights, and visual structures.
- **How it helps with hour-long videos:** It parses longer web recordings or uploaded files, splitting the output into broken-down topic sections, key data points, and Q&A formats.[](https://google.com/goto?url=CAESTgHrOzAVWWRYVFi7JBkFzt7RGdiWOlG54XV320uNcKXMrU4Ngm2qzjcK8c-a8sVmzCZ_BO7HlZ2RfBXhY4cxODgwyxexihzMKkPZ-ADgQw) [[1]](https://google.com/goto?url=CAESTgHrOzAVWWRYVFi7JBkFzt7RGdiWOlG54XV320uNcKXMrU4Ngm2qzjcK8c-a8sVmzCZ_BO7HlZ2RfBXhY4cxODgwyxexihzMKkPZ-ADgQw)

If you'd like to narrow down the best choice, let me know:

• Do you need this for live meetings (Zoom/Teams bots) or pre-recorded video files you already have saved?
• Do you prefer a tool that integrates directly into a specific workspace ecosystem (like Microsoft 365, Google Workspace, or standalone apps)?

Yes. There are several tools now that go beyond transcription and summaries into automatic chapterization/topic segmentation—which sounds like the workflow you want.

Best fits

• sonix.ai — Particularly close to your requirement. It automatically creates timestamped chapters and performs thematic analysis, identifying recurring topics and how they relate. Good fit if you want to upload meeting recordings and quickly understand the discussion structure.
• twelvelabs.io — More of a video-understanding platform/API. Its Pegasus model can generate chapters, summaries, reports, categories, and time-coded metadata, using speech, audio, visuals, and on-screen text. It supports videos up to two hours, so an hour-long meeting is squarely in range.
• mixpeek.com — Explicitly combines transcription, visual scene detection, and topic modeling to find semantic shift points, then produces titled chapters and summaries. This is a strong choice if you're building a video-analysis/search workflow rather than just reviewing meetings yourself.
• speechmatics.com — Offers an API that automatically segments audio/video into chapters using ASR plus LLMs. Better suited to developers integrating chapterization into another application.
• kenznote.com — Meeting-oriented: it identifies discussion topics, assigns timestamps, and lets you jump directly to each topic in the recording. This is probably one of the more directly meeting-specific options.
• taption.com — Browser-based video analysis with transcripts, summaries, time-coded chapters, and meeting-style notes. It can work from uploaded MP4/MOV files or YouTube links.

If you mean "topic modeling" in the technical sense

There are also research/open-source approaches specifically designed for this. Chapter-Llama partitions hour-long videos into semantic chapters using speech transcripts plus selected video-frame descriptions, while TreeSeg performs hierarchical topic segmentation on large transcripts.

For your particular problem—"I have a 60-minute meeting and want to know what was discussed without watching it"—I'd start with Sonix or KenzNote for an off-the-shelf experience, and Twelve Labs or Mixpeek if you're looking to build this into a larger workflow.

If you tell me whether your meetings are Zoom/Teams recordings, uploaded MP4s, or live meetings, I can narrow this to the 3 best options and compare their pricing, integrations, speaker/topic handling, and privacy.

Yes. There are several tools that specifically turn long meeting videos into chapters/topic segments, rather than just producing a wall-of-text transcript.

Strong options

• claap.io — Probably the closest fit for recorded meetings. It supports Zoom, Google Meet, Teams, and uploaded video, with AI summaries + automatic chapters, searchable transcripts, and integrations with Slack/Notion/CRM tools.
• avoma.com — More meeting/sales oriented. Its Smart Chapters organize a recording by topics such as budget, objections, timeline, and next steps, with clickable timestamps.
• sonix.ai — Particularly interesting if by “topic modeling” you mean discovering recurring themes across recordings. It offers automatic timestamped chapters plus thematic analysis that identifies major topics and relationships between them.
• mixpeek.com — Best if you're building this into a product/workflow. Its video chapterization combines transcription, topic modeling, visual scene changes, and an LLM to produce titled, timestamped chapters.
• twelvelabs.io — A developer/API-oriented option. You can prompt it to generate chapters, summaries, reports, tags, or time-coded metadata, using both speech and visual information. It supports videos up to two hours for this analysis.
• atlassian.com — Convenient if you're already recording meetings in Loom. Its recap automatically creates chapters based on topic shifts, alongside the transcript and summary.

What I'd choose

For your specific problem—“I have a one-hour meeting and need to understand it quickly”—I'd shortlist:

1. Claap — best overall meeting-video workflow.
2. Avoma — best if these are business/sales meetings and you care about decisions, objections, action items, etc.
3. Sonix — best if you want actual thematic analysis/topic modeling, especially across many recordings.
4. Twelve Labs / Mixpeek — best if you're looking to build chapterization into your own application.

The key distinction is that chapterization answers “where did the conversation change topics?”, while topic modeling/thematic analysis answers “what themes keep appearing across this meeting or across many meetings?” Sonix and the API-oriented tools are more compelling for the latter.

If you tell me whether your meetings are Zoom/Teams/Google Meet recordings and whether you want a ready-to-use app or an API, I can narrow this to the 2–3 best choices.

Extracting insights from hour-long video recordings manually is a massive time sink. Fortunately, several modern AI meeting assistants and video intelligence platforms specialize in automatic chapterization (breaking the video down by distinct agenda items or shifts in dialogue) and topic modeling/tracking (identifying key themes, recurring keywords, and structured outcomes).

Top platforms offering these capabilities include:

• Grain — Specifically structures meeting recordings to mirror human memory by dividing long calls into purpose-driven chapters, outcomes, and action items . It lets you scan the structural flow of a call at a glance and jump straight to specific thematic segments.
• Fireflies.ai — Excellent for deep conversational analysis. It segments meetings into digestible AI-generated chapters and uses Topic Trackers to monitor specific keywords, pricing mentions, or recurring themes across all your video meetings.
• tl;dv — Focuses heavily on turning video into searchable knowledge. It automatically timestamps and structures calls into thematic moments, allowing you to quickly review or clip key discussions without scrubbing through a 60-minute video.
• AssemblyAI (For Developers/Custom Workflows) — If you are building a custom internal tool rather than using a plug-and-play app, AssemblyAI provides robust speech-understanding models featuring Auto Chapters and conversational summarization APIs specifically trained on long-form audio/video data.

If you want to narrow this down, let me know:

• Are you looking for a ready-to-use app for your team or an API/developer tool?
• Which video platform do you primarily use (Zoom, Google Meet, or Microsoft Teams)?

I can help you pick the ideal workflow.

Yes. There are several vendors doing essentially automatic chapterization + topic segmentation/modeling for long meeting videos.

If you mean true video chapterization, not just meeting summaries

I'd narrow it to TwelveLabs, Mixpeek, Zoom, and Microsoft.

The distinction matters: conventional meeting assistants mostly transcribe → summarize, whereas a video-intelligence system can identify semantic boundaries in the timeline, e.g.:

00:00–08:14 — Project status
08:14–19:37 — Q3 budget concerns
19:37–31:02 — Product roadmap
31:02–43:18 — Customer feedback
43:18–58:41 — Decisions and next steps

Mixpeek explicitly describes combining transcript topic modeling with visual cues to find those boundaries.

There are also research-grade/open approaches worth knowing about: ARC-Chapter and Chapter-Llama specifically target hour-long video chaptering, generating timestamped semantic sections and titles rather than merely producing a summary.

My shortlist:

• Just want to consume your meetings faster: Zoom / Teams Copilot / tl;dv
• Want cross-meeting topic intelligence: Fireflies / Avoma
• Want to build chapterization into a product: TwelveLabs / Mixpeek
• Want to experiment with the underlying technology: ARC-Chapter / Chapter-Llama

If you tell me whether your meetings are Zoom, Teams, or uploaded MP4s, I can narrow this to the 3 strongest options and compare their chapter quality, topic modeling, API access, and pricing.

Several specialized AI meeting assistants and video analytics platforms offer automatic chapterization (segmenting videos into chronological, timestamped sections) and topic modeling (extracting and categorizing themes across the transcript).

Specialized AI Meeting Assistants

These tools automatically join your live video meetings (Zoom, Google Meet, Microsoft Teams) or accept recorded file uploads to slice your videos into thematic chapters.

• Fireflies.ai : This platform is highly optimized for complex topic modeling and multi-tier chapterization. It builds a searchable visual grid of structural chapters, tracks specific customized topics/trackers across hours of recordings, and groups recurring conversation themes across your entire video dashboard.
• Fathom : Best known for providing free, instant, and completely automated video chapterization. As soon as a meeting concludes, Fathom sections the timeline based on natural conversation shifts and formats key insights into clickable chapters.
• Otter.ai : Excellent for cross-meeting topic modeling and theme identification. It extracts recurring keywords, tags speakers, and populates a conversational data engine where you can text-search specific conceptual threads across hour-long video files.

Dedicated Video Summarization & Analytics Platforms

If you are analyzing pre-recorded video assets (such as webinars, lectures, or training materials) rather than live corporate meetings, these post-production platforms generate highly precise chapter markers.

• Descript : An AI-driven text-based video editor that maps transcripts to video timelines. Its built-in AI suite automatically detects natural topic shifts to generate structured, timestamped video chapters for immediate export or navigation.
• Recapio : An enterprise-focused video analyzer that transcribes video tracks and isolates topics into designated, secure custom knowledge libraries. It features clickable timestamped chapters linked directly to video frames.
• AssemblyAI : A development platform providing an enterprise-grade API that extracts precise video chapters and maps thematic shifts using raw video audio datasets.

To see how modern video summarizers extract structured insights and create readable timestamp breakdowns from long audio/video content, watch this demonstration:

If you want to choose the right platform, tell me:

• Do you need a tool to join live calls or process pre-recorded video files?
• Which video conferencing platform (e.g., Zoom, Teams, Meet ) do you use most?
• Is your main goal to click and skip to video sections, or to export text summaries into other tools?

If you need to break down hour-long video meetings into digestible insights quickly, several specialized AI meeting assistants and platforms offer automated video chapterization and topic modeling.

Here are the top tools that solve this specific problem, categorized by how you work:

Dedicate AI Meeting Assistants (Best for Zoom, Teams, & Google Meet)

• Fireflies.ai : Strongly favored for detailed video meeting chapterization. It automatically tracks topic modeling trends across your conversations, flags key action items, and generates an interactive, chaptered timeline so you can jump directly to specific topics.
• Fathom : A highly regarded tool that auto-generates structured chapters and highlights from long recordings. It is widely used to instantly clean up an hour-long meeting into short, skimmable sections with auto-generated summaries.
• Otter.ai : Excels at real-time topic modeling, live keyword tracking, and automated summaries. It breaks down long-form conversations by speaker and overarching themes, making it easy to extract insights without re-watching.

Integrated Ecosystem Solutions

• Microsoft Stream (on SharePoint) : If your company uses the Microsoft ecosystem, Stream includes a built-in AI feature that automatically sections any uploaded video timeline into navigable chapters using the video’s transcript.

Video Editors & Repurposing Tools

• Descript : Ideal if you want to edit or repurpose your meeting videos. Descript uses its "Underlord" AI engine to analyze your video transcript, detect topic transitions, and automatically insert accurate chapter markers and titles.
• Imaginario AI : A specialized video platform that uses AI to map narrative structure, create chapters with summaries, and allow users to search inside the video context for specific key themes.

Developer APIs (To Build Your Own Workflow)

• AssemblyAI : Offers an "Auto Chapters" API model specifically designed to segment conversational data (like meetings or podcasts) into topically coherent chunks, providing a timestamp, summary, and headline for each section.

To see how built-in cloud enterprise tools automatically partition lengthy video files into skimmable sections based on transcripts, watch this breakdown:

To narrow this down, let me know:

• Which video conferencing platform do you use most often (e.g., Zoom, Teams, Google Meet)?
• Do you want a bot that joins live to do this automatically, or do you prefer to upload recordings manually?
• Are you looking for a free tool , or is this for a corporate team?

Yes. There are several good options, but they split into meeting-focused apps and developer APIs for arbitrary video.

My picks:

• Just want to upload a one-hour meeting and get useful sections: Loom or Taption. Loom explicitly creates sections based on topic shifts, so you can jump directly to relevant parts of a recording.
• Want an API / build this into your product: Twelve Labs is probably the strongest fit. Its analysis model can produce chapters, reports, summaries, time-coded metadata, and arbitrary JSON from videos up to two hours, while considering speech, visuals, and on-screen text.
• Want actual topic segmentation rather than merely summarization: Mixpeek is particularly on-point. Its video-to-chapters pipeline transcribes the audio, detects visual changes, uses topic modeling to identify semantic shifts, and generates timestamped chapter titles/summaries.
• Want a speech-centric API: AssemblyAI's Auto Chapters is purpose-built to detect when the topic changes and summarize each resulting section, including for virtual-meeting platforms.

There is also interesting research specifically on this problem: Chapter-Llama was designed to partition hour-long videos into semantically meaningful chapters using timestamped transcripts plus selected visual frames.

If your actual goal is “give me the best 3 tools for analyzing recorded Zoom/Teams meetings, with pricing and API availability”, I can narrow this down substantially.

Yes. There are several strong options, but they fall into two camps:

A particularly direct match is TwelveLabs: its video-analysis API can generate chapters, summaries, reports, and time-coded metadata, using both speech/audio and visual information. It supports videos up to two hours, so an hour-long meeting is squarely within its stated use case.

For a meeting end-user product, I'd start with Fireflies, tl;dv, or Avoma. For example, the current landscape distinguishes tl;dv for video-style chapter navigation/clips, Fireflies for recurring topics and cross-meeting search, and Avoma for deeper conversation intelligence.

If you're building this capability into your own product, TwelveLabs and Mixpeek are more interesting. Mixpeek explicitly describes a pipeline that combines transcription, visual scene detection, topic modeling, and LLM-generated chapter titles/summaries.

There is also serious underlying research here: Chapter-Llama specifically targets chaptering hour-long videos by combining transcripts and visual captions to identify semantic boundaries and generate chapter titles.

My shortlist:

• 🏆 Best API/platform: TwelveLabs
• 🏆 Best meeting workflow: Fireflies.ai
• 🏆 Best for navigating the actual video: tl;dv
• 🏆 Best sales/conversation intelligence: Avoma
• 🏆 Most explicit “topic detection → chapters” workflow: Blazescribe

If you tell me whether you're looking for a tool your team can use immediately or an API/model to build this yourself, I can narrow this to the 3 best options and compare pricing, integrations, and accuracy.

If you need to break down hour-long video meetings into digestible insights quickly, several specialized AI meeting assistants and platforms offer automated video chapterization and topic modeling.

Here are the top tools that solve this specific problem, categorized by how you work:

Dedicate AI Meeting Assistants (Best for Zoom, Teams, & Google Meet)

• Fireflies.ai : Strongly favored for detailed video meeting chapterization. It automatically tracks topic modeling trends across your conversations, flags key action items, and generates an interactive, chaptered timeline so you can jump directly to specific topics.
• Fathom : A highly regarded tool that auto-generates structured chapters and highlights from long recordings. It is widely used to instantly clean up an hour-long meeting into short, skimmable sections with auto-generated summaries.
• Otter.ai : Excels at real-time topic modeling, live keyword tracking, and automated summaries. It breaks down long-form conversations by speaker and overarching themes, making it easy to extract insights without re-watching.

Integrated Ecosystem Solutions

• Microsoft Stream (on SharePoint) : If your company uses the Microsoft ecosystem, Stream includes a built-in AI feature that automatically sections any uploaded video timeline into navigable chapters using the video’s transcript.

Video Editors & Repurposing Tools

• Descript : Ideal if you want to edit or repurpose your meeting videos. Descript uses its "Underlord" AI engine to analyze your video transcript, detect topic transitions, and automatically insert accurate chapter markers and titles.
• Imaginario AI : A specialized video platform that uses AI to map narrative structure, create chapters with summaries, and allow users to search inside the video context for specific key themes.

Developer APIs (To Build Your Own Workflow)

• AssemblyAI : Offers an "Auto Chapters" API model specifically designed to segment conversational data (like meetings or podcasts) into topically coherent chunks, providing a timestamp, summary, and headline for each section.

To see how built-in cloud enterprise tools automatically partition lengthy video files into skimmable sections based on transcripts, watch this breakdown:

To narrow this down, let me know:

• Which video conferencing platform do you use most often (e.g., Zoom, Teams, Google Meet)?
• Do you want a bot that joins live to do this automatically, or do you prefer to upload recordings manually?
• Are you looking for a free tool , or is this for a corporate team?