AssemblyAI

Our main use case for AssemblyAI is automatically transcribing clients' meeting recordings, podcasts, and video interviews, and we also use it to generate summaries and extract key topics from long recordings. It saves our editor's team an enormous amount of time.

In one of my recent projects, we were producing weekly podcasts containing 12 different clients, and we had a meeting with the clients where we had to transcribe company show notes and repurpose them into blog content. Manually transcribing that volume was impossible for our small company, so we integrated AssemblyAI's API into our workflow, and within a minute of a recording being uploaded, it was fully transcribed and speaker-labeled. What used to take three hours per episode was reduced to under five minutes.

For client meetings, when we have the client meeting, some of us find it very difficult to note down the specific points and sometimes miss them, but by using AssemblyAI for that interview call, we get it easily transcribed. We have the main focus, and we get to know all the transcribed main points, so we don't miss out on anything.

We use an API integration to build AssemblyAI into our internal content management system, so when a file is uploaded, it automatically triggers the AssemblyAI transcription pipeline, and returns the result directly into our platform within minutes.

The best features AssemblyAI offers are the speaker diarization, which identifies who is speaking, the automatic summarization and sentiment analysis, topic detection, and the extremely accurate speech-to-text, even with different accents and background noise.

Speaker detection is what makes the biggest difference in my day-to-day work, especially when meetings happen with many people, multiple people interviewing, and panel discussions. It automatically identifies who the client is and who the speaker is, and for client-facing transcript accuracy, knowing who said what is absolutely critical, and AssemblyAI handles this better than any other tool we tested.

AssemblyAI has positively impacted our organization by allowing us to scale from managing five client accounts to 12 without hiring additional staff. Our client capability doubled while our costs stayed controlled, and client satisfaction scores also improved because the turnaround time on a transcript dropped from two days to same-day delivery.

AssemblyAI could be improved because the accuracy drops noticeably with a heavy accent or a very fast speaker, and pricing can become expensive at a high volume, so better multi-support or more affordable enterprise pricing tiers would make it significantly more competitive.

AssemblyAI takes data security seriously, offering data deletion options and not using submission audio to train their models by default, which is critical for us handling confidential client content. However, clearer documentation around compliance certificates such as SOC 2 and GDPR would give enterprise clients more confidence.

AssemblyAI is expensive, but overall, it is a good product.

I have been using AssemblyAI for about six months since joining the company.

AssemblyAI is stable in my experience; however, when the user's voice is unclear, it sometimes lags there.

Overall, the accuracy of AssemblyAI's output is consistently above 95% for clear audio, and it is reliable enough for professional use without heavy manual correction. The reliability of the API uptime has been excellent in our experience.

AssemblyAI's scalability can handle more volume if our company grows.

I never had to contact customer support because we never found any complaints or any bugs that would require us to contact them.

This was my first time using a transcribing application, and AssemblyAI did a great job.

We save approximately 85% of the time on transcribing tasks, and in workforce terms, we estimate AssemblyAI replaced what would have been a full-time transcriber role, which would cost around 35,000 to 40,000 per year. The API subscription costs a fraction of that, making the ROI extremely clear.

We saved around 85% of our workforce's time, and the cost savings are around 35,000 to 45,000 per year, making the ROI extremely clear.

AssemblyAI is a very good application for meetings, client interviewing, and podcasts, so I think everyone should use it in their company. I rate AssemblyAI an 8 out of 10 because the accuracy drops with heavy accents and fast speakers, and the pricing is expensive, so I think 8 is an appropriate rating for this application.

I use AssemblyAI only with audio files, not for real-time transcription. I mainly use only US English, and I have not tried other languages. I upload audio files through AssemblyAI API, and they provide the transcription script with speaker identification and the dialogues.

The main features I appreciate in AssemblyAI are that it provides better accuracy compared to other transcription services, with clear grammar and no errors in spelling mistakes or grammatical mistakes, delivering clear transcription.

The primary benefit I receive from their product is much more accurate transcription. First, it is a very affordable service, and second, the accuracy is much better compared to other services such as Deepgram or AWS transcription services, which are the main benefits. Third, the speaker identification capability is better.

A few drawbacks I observed in the speaker identification are that in some videos where text and names appear on the video frames, AssemblyAI does not identify the actual speaker name, instead providing generic names such as Speaker A, Speaker B, Speaker C, or Speaker X, Y, Z.

AssemblyAI does not identify the real speaker in some audio or video files, just sending Speaker A, Speaker B, or Speaker C. They are not easily identifying speakers in some instances.

AssemblyAI does not provide a cloud service; I simply upload the audio file to the API, and they store it somewhere internally to send me the transcription text.

For additional functions, the API does not provide video uploading functionality, and I need to convert video to audio first before uploading it to AssemblyAI.

I have been working with AssemblyAI for approximately one year.

AssemblyAI should respond more quickly because when I post a ticket, they take too much time to respond to it.

I did not continue working with Deepgram after trying it, but I recently started using AssemblyAI because Deepgram does not provide accurate transcription. I chose AssemblyAI because I did not use Deepgram again.

I only need to create an account on AssemblyAI, and initially, they provide some credits for transcription, which is enough initially. However, if usage increases, I can purchase a subscription from there.

I think the price for the product is a seven.

I can compare AssemblyAI with Deepgram. I would choose only AssemblyAI instead of Deepgram when comparing both products. The main reason I chose it is that it is far better compared to Deepgram regarding speaker identification, the clear verbatim process, and the time-stamp process, providing accurate time-stamping and the dialogues.

If I compare AssemblyAI with other services such as Gameloop, ChatAI, and Deepgram, the accuracy is far better, always maintaining the grammar and providing good, accurate text for audio or video files.

The AssemblyAI noise filtering feature exists, but I did not use that feature. I use the existing API where I upload the audio to AssemblyAI, and after a few seconds or minutes, I continuously check if the transcription is done. Once it is done, I pass the transcription text into a file and generate an SRT file, a text file, and a doc file.

It works fine with different accents.

I rate this product an overall 8 out of 10.