# AssemblyAI Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/assemblyai
> Markdown URL: https://aitinkerers.org/technologies/assemblyai.md
> Technology record last updated: 2026-04-07T20:39:33Z
> Generated: 2026-08-26T19:16:58Z

AssemblyAI provides industry-leading Speech AI models—like its Universal model with >93.3% accuracy—via a developer-first API for transcription and deep audio intelligence.

AssemblyAI is the premier Speech AI platform, delivering state-of-the-art models for both high-accuracy transcription and deep audio understanding (Speech-to-Text and Audio Intelligence). Developers access this power through a robust, scalable API, integrating features like real-time streaming with <500ms latency. The platform goes beyond raw text: models like LeMUR apply LLMs to transcribed speech for automatic summarization, sentiment analysis, and PII redaction. Major companies, including CallRail, Fireflies, and Spotify, rely on AssemblyAI to build cutting-edge, voice-powered products and extract actionable insights from conversational data.

- Official technology site: https://www.assemblyai.com/
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [epilepsy ally: a chatbot to help parents of kids with epilepsy](https://chicago.aitinkerers.org/talks/rsvp__O0u3ll2BrE)

Some kids have seizures that cannot be stopped with medicine - for many, brain surgery is the only option. As a parent of a child with intractable epilepsy, I have found it daunting to figure out what my child needs. I built a chatbot that sifts through medical jargon and the latest research and helps parents who are facing or who's child has already had surgery.

- Event context: AI Tinkerers Chicago April Meetup — 2025-04-15 — Chicago
- Public talk page: https://chicago.aitinkerers.org/talks/rsvp__O0u3ll2BrE

### [Transcriber R&D project](https://sf.aitinkerers.org/talks/rsvp_ebaB6-i0btI)

I'll present a custom-built tool designed to evaluate the quality of timestamps and text generated by various speech-to-text engines. At Capsule, precise transcriptions and timestamps are essential for video editing, making accuracy in these areas critical. In just 4 minutes, I'll demo a Next.js app that integrates with the media library and visualizes outputs from different versions of our transcription pipeline. This pipeline includes ML models such as VAD, language identification, speech-to-text engines (e.g., Whisper, AssemblyAI, Reverb), alignment model, and LLMs. You'll get a glimpse into how I address complex challenges using techniques like chunking, LLM, Diff, Merge algorithms, and logging. I'll cover solutions for issues such as missed repetitions, punctuation improvements, timestamp alignment losses, hallucinations, Japanese tokenization errors, and how merging outputs from two transcription models enhances quality of text and timestamps.

- Event context: AI Tinkerers - San Francisco - February 2025 Demos + Science Fair — 2025-02-28 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_ebaB6-i0btI

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- [Reverb](https://aitinkerers.org/technologies/reverb) ([Markdown](https://aitinkerers.org/technologies/reverb.md)) — 1 public demo
- [VAD](https://aitinkerers.org/technologies/vad) ([Markdown](https://aitinkerers.org/technologies/vad.md)) — 1 public demo
- [Whisper](https://aitinkerers.org/technologies/whisper) ([Markdown](https://aitinkerers.org/technologies/whisper.md)) — 26 public demos