AssemblyAI Reviews

I use AssemblyAI for audio transcription in multiple different languages. It has the capability of translating and transcribing into multiple different languages of both India as well as in the world. It also has good diarization capabilities, which is why I use AssemblyAI.

I had a customer use case problem where I had to transcribe lots of customer support calls into transcriptions in Hindi and multiple different Indic languages, as well as in foreign languages. AssemblyAI was helpful for this purpose.

AssemblyAI has been integrated into multiple different clients' use cases, and it was one of the core features in the AWS pipeline audio analytics pipeline that we created. It has benefited us significantly in saving costs of transcription.

The best features AssemblyAI offers are its blazing fast transcribing skills and accurate results. It also has the capability of diarization, as well as transcribing in multiple different languages, both in foreign and Indic languages.

I particularly value the accurate transcription of the language that the user provides as input and getting the best output without any kind of noise or silence. Automatic silence removal and voice activity detection are the best features of AssemblyAI that I appreciate in my daily use.

The outputs are really accurate. AssemblyAI already cares for the overall grammar, syntax, and the different nuances of the particular speakers. I believe the accuracy part has improved significantly from the previous versions that were available and should continue to improve further to become the best product in the market.

There was a saving of about 40 to 50% in transcription of audio analytics calls because previously, it was all done by humans, which could take days of effort and cost. This has significantly reduced to a great amount.

We tested with Deepgram and AWS transcription service that is already available in the market, and then we switched over to AssemblyAI.

AssemblyAI should definitely cater to multiple different languages of the world as well as in India. There are multiple different Indic languages and dialects available, and AssemblyAI should cater to those. Additionally, there might be multiple speakers available in a room in a particular meeting, and for that, proper diarization is required for identifying the different speakers as well as their names. These are some of the features that require attention by AssemblyAI, and they can definitely improve on that.

The pricing should definitely be looked at and the features should be worked upon as suggested.

I have been using AssemblyAI for about two to three years.

AssemblyAI is definitely stable.

AssemblyAI has a very good scalable solution. It has definitely been integrated in such a way that it handles multiple audios at a time. Regarding the pricing, I believe it is already in a very good range.

Customer support is definitely great with AssemblyAI. If you have any issues or encounter any problems in setting up, you can definitely reach out to the customer support and you can immediately get a solution.

I was using the AWS transcription service. There were problems of identifying the different languages, the different Indic languages that we have. AssemblyAI came into the picture and it solved a great deal of the problem.

The setup was pretty much easy. You just go to the AWS Marketplace and get this particular service provisioned and directly you can start using it with an API endpoint and key. The setup is pretty much easy.

I would say it is a time-saved and money-saved metric that should be considered here. That is how AssemblyAI is ruling the market.

I would give AssemblyAI a rating of 10 out of 10. I would suggest others to go for AssemblyAI because it is the best in the market in terms of accuracy, outputs, and the different languages that it caters to and transcribes. It is a very good product overall.

AssemblyAI has data privacy and security enabled so that the conversations that take place and are used for transcription are not leaked out to the public or leaked out in the public domain. There should not be any sort of sensitivity, privacy, or personally identifiable information data that gets leaked out. These things should be enforced strictly, and I believe AssemblyAI does that already.

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.

The best features AssemblyAI offers are transcription and real-time transcriptions. The speed of real-time transcription stands out to me because it's 20 to 40% faster than the industry benchmark, so speed is definitely one of the pros of AssemblyAI.

AssemblyAI has positively impacted my organization by being a fundamental part of our main use flow, where our bot joins the meetings and transcribes them into text. Once the text is generated, it goes to our internal LLM to get culture scores, making it one of the main fundamental parts of our product.

AssemblyAI could be improved because when we have different accents on the same call, it usually fails, especially when we have American, Asian, and Latin American speakers on the same call, making the transcriptions a bit noisy.

The transcription quality of non-native English speakers should be improved. I choose nine out of ten because it's really good and fast, working well when there is an English speaker on the call, so the quality of the transcription is really good. Latency is almost zero, and it's 20 to 40% faster than the industry benchmarks. I only rate it as nine because it lacks accent detection and the quality for different accents.

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.

In my personal project, I used AssemblyAI for audio entity recognition. I gave it some audio files and AssemblyAI processed them to provide entity recognition. For example, if the audio contained names of someone, it highlighted them as person names and these types of entities.

In the freelance project that I made recently, I used it for transcribing audio interviews. We were making an audio and video interviewing system and we needed an API to transcribe audio into text. AssemblyAI was used for speech-to-text translation because it was the fastest and the best option for our use case.

In the audio and video project I was making for a freelance client, our use case was speed. The main thing that would differentiate us from our competitors was speed. We needed a quick solution that was also cost-effective. AssemblyAI stood out and it provided us quick results that helped us transcribe the audio stream quite instantly and use it to process and show results to the user.

I noticed that it was quite quick. I also noticed that it offers flags to check when the audio has stopped. This helped me identify the different users in that audio and properly transcribe the text and make meeting notes and these types of things.

It was quite accurate. We were using it to transcribe speech to text, and then we used that transcribed text to generate follow-up questions for the interviewers. It needed to be accurate. As our experience suggested, it was quite accurate and we were able to fulfill the use case.

I think the documentation could be improved a bit because it is a little difficult to follow for the first-time user. If you do not have an MCP right now, I recommend that you make an MCP for AssemblyAI API because now is the time of AI and agents. An MCP helps us to integrate it with our system quite easily.

I think it was good and it fulfilled my use cases, but there is always room for improvement. I gave it an 8 and not a 10 because nothing is 10 out of 10 in this world.

I have used AssemblyAI twice now. One time I used it for an audio entity recognition software I made for my personal learning. I recently used it in a freelance project that I was doing.

I was offered assistance when your representative contacted me on LinkedIn and offered to send her the screenshot of the completion, and she will hopefully give me a gift card or something.

Previously we were using Deepgram for audio transcription. Deepgram is an API for audio transcription, but it was comparatively slow and somewhat not cost-effective when compared to AssemblyAI. After shifting to AssemblyAI, the biggest two points we experienced were that the speed of our software increased and our costing of the API reduced. It helped us with the speed and the cost-effectiveness.

My main use case for AssemblyAI is to transcribe audio using the AssemblyAI API, though I faced some issues with it later on. For general transcribing, it performs well, and I also used the summary and text diarization APIs.

I receive call recordings, apply a transcript to them, and conduct analysis on those call recordings, which is my primary use case with AssemblyAI.

One of the best features AssemblyAI offers, in my experience, is that it understands when two people are talking and transcribes those conversations properly, identifying Speaker 1 and Speaker 2 and providing the actual transcript.

The speaker diarization feature works well for my specific use case, especially when I am doing English audio transcription; it handles it pretty well. However, when I try to handle Hindi plus English or Hinglish audios where there is code switching between English and Hindi, then it falls apart significantly.

AssemblyAI has impacted my organization positively, but I could not use it later on because it did not pass the quality benchmarks.

AssemblyAI can be improved by enhancing their voice models and supporting English plus Hindi code switching, similar to an AI model like Sarvam.

I first used AssemblyAI around one year ago, and then I used it again recently, so I have approximately 1.5 years of experience using AssemblyAI.

On a scale of one to ten, I would rate AssemblyAI around seven to eight for English transcription.

I choose an eight for English transcription because it handles the transcription pretty well.

My advice to others looking into using AssemblyAI is that if you are using it for English transcription and your primary goal consists of only English audios, then I recommend it. It is affordable, performs better than alternatives, and it has been available for a long time, so customer support should also be good. It is affordable and easily integrated, requiring minimal hassle—just API calls.

The quality benchmarks AssemblyAI did not pass are related to Hinglish audio; specifically, it was not able to diarize or transcribe it properly.

My overall rating for AssemblyAI is eight out of ten.