I work as a Dietician and Nutritionist, manage a homeopathy clinic, create health education content for social media, and also prepare educational material for patients and students. What I like most about Deepgram is that it helps convert spoken content into text quickly and in a very organized way. I tested it with a health awareness audio recording, and the transcript was generated fast and was easy to review. What makes it useful for my work is that it offers more than basic transcription. Features like speech-to-text, smart formatting, speaker recognition options, summarization, topic detection, and audio file transcription help me work with recordings more efficiently. When I create health education content, prepare awareness campaigns, review educational recordings, conduct online teaching sessions, or organize information for patients, these features help me identify important points much faster.

The performance has been good during my use. Transcripts were generated quickly, the text was easy to read, and the formatting required very little cleanup. I also found the summaries and detected topics useful because they provide a quick overview of longer recordings. This helps save time when preparing patient education material, nutrition guidance notes, health awareness content, presentation outlines, and social media posts. Another thing I like is that it reduces the effort needed to review longer audio files. Instead of repeatedly listening to recordings, I can work directly with the transcript, summary, and detected topics to organize information more efficiently. This is especially helpful when handling educational content, clinic related recordings, and health discussions that need to be converted into written material. I do not use it every day, but whenever I need to work with recorded content, Deepgram helps make the process faster, more organized, and easier to manage. Overall, Deepgram helps save time, keeps recorded information organized, and makes it easier to work with audio-based content in a more structured way. Review collected by and hosted on G2.com.

The transcription quality is generally very good, but with recordings that contain strong accents, unclear speech, or multiple people speaking at the same time, I sometimes need to do a small amount of manual review. It does not happen often, but it can occur with real world audio. Review collected by and hosted on G2.com.

What I like best about Deepgram is the real-time transcription speed and accuracy — the Nova-2 model processes audio almost instantaneously with remarkably low word error rates even on technical jargon and domain-specific vocabulary, which was a persistent failure point with other transcription services we evaluated. Review collected by and hosted on G2.com.

One consistent frustration is the documentation gaps around edge cases - while the core API docs are clean and well-structured, when you move into advanced configurations like combining smart formatting with custom models or fine-tuning diarization sensitivity, the documentation becomes sparse and I've had to rely heavily on community forums and trial-and-error to find answers. Review collected by and hosted on G2.com.

I use Deepgram to turn speech into text, which helps me quickly understand and read what people say in meetings, calls, and videos. It saves me time because I don't have to write notes or listen to recordings again. I like that it quickly and accurately turns speech into text and works well with different voices and accents. Its accuracy and ability to handle different voices and accents really helped when I was processing multi-speaker meetings and recorded calls from global events, even with background noise or speakers with strong accents. Setting up Deepgram was straightforward. The API is well-documented, authentication was simple, and I was able to start transcribing audio in just a few hours without any complex configuration. I also integrate Deepgram with tools like Slack and custom apps using their API. Our team switched to Deepgram from another transcription service because we needed accuracy. Review collected by and hosted on G2.com.

It works really well overall, but it can sometimes struggle when the audio is very noisy or when multiple people are speaking over each other. Review collected by and hosted on G2.com.

I appreciate how fast Deepgram is when using it for real-time production applications, as even small delays can make a big difference. Deepgram's speed makes the end-user experience very good. The accuracy is another aspect I find impressive since it really matters a lot. I've tried other solutions, but they didn't provide the perfect accuracy I get with Deepgram. When making calls, the voice agent sounds clear and natural, which improves the overall experience. The response time is much faster, and conversations feel smoother and more interactive. The voice quality is very important to me, and Deepgram makes sure there are no breakouts, avoiding any irritation. During live calls, it talks like a person with interactive and engaging responses. Review collected by and hosted on G2.com.

It would be great if we can increase capacity of it, because for less number it works fantastic but when we increase the number voice quality gets breaks. It would be better if we can make 8 to 10 number of calls at a time, if we increase the number, voice gets break 4 to 5. Review collected by and hosted on G2.com.

Deepgram provides very accurate and fast speech-to-text transcription, even for long audio recordings and real-time streams. The API is easy to integrate into applications, and the documentation is clear and developer-friendly. I especially like the low latency for real-time voice recognition and the ability to handle different accents and noisy environments. It has been reliable and scalable for production use. Review collected by and hosted on G2.com.

While Deepgram performs very well overall, the pricing can become expensive when processing large volumes of audio. Some advanced configuration options and features also require deeper documentation to fully understand. Occasionally, accuracy can drop slightly with heavy background noise or highly specialized vocabulary. Review collected by and hosted on G2.com.

The speed is the standout feature. I'm using Nova-2 with dual WebSocket streams (mic + tab audio simultaneously) for a real-time voice coaching Chrome extension, and interim results come back fast enough to display a genuinely live rolling transcript. Word-level confidence scores, smart_format, vad_events, and utterance_end_ms all work exactly as documented and saved me a lot of custom logic. The $200 starter credit is also a great touch - it gave me real runway to prototype and validate the product before committing to a paid plan. Review collected by and hosted on G2.com.

Nothing major so far. The documentation could occasionally go deeper on edge cases around dual-stream WebSocket setups and silence/KeepAlive behavior, which required some trial and error to get right. But overall these are minor friction points in an otherwise smooth experience. Review collected by and hosted on G2.com.

The speech-to-text accuracy and punctuation are awesome compared with GCP and Azure STT. Pricing is also better than other services. Review collected by and hosted on G2.com.

Sometimes Nova 2 performs better than Nova 3, and Nova 3 still doesn’t support keywords. Also, the multi-language detection isn’t very accurate when you compare results across multiple streams. In my DilMesh app, I create a separate stream for each language that might be spoken. At our events we generally use Turkish and English, so the app creates two streams—one for Turkish and one for English—and then selects the final results based on the confidence response. Multi stream method works terrific when you compared with built-in multi language detection. Review collected by and hosted on G2.com.

I really like the outstanding accuracy of Deepgram. In our law firm, where precision is critical, it consistently delivers highly accurate transcriptions even with varied accents, legal terminology, and occasionally poor audio quality. The speed of Deepgram is also impressive; what used to take hours of manual work is now done in minutes, which helps us process evidence faster, especially with tight court deadlines. The initial setup was relatively straightforward, thanks to the clear and well-structured API documentation that made integration manageable with our existing workflow. Review collected by and hosted on G2.com.

Occasionally, Deepgram tends to hallucinate — generating words or phrases that were not actually spoken in the recording. In a legal context, this is a concern because inaccurate transcriptions can be misleading. It requires us to manually review and verify transcripts before relying on them, which adds some extra time back into our workflow. Review collected by and hosted on G2.com.

I find Deepgram to be an industry leader with good pricing. The initial setup was trivial for us, and compared to Azure speed services that I used at my last company, Deepgram is much easier. Review collected by and hosted on G2.com.

I'm a bit frustrated by having to research potential NAT port exhaustion issues with our AWS setup while using Deepgram. I really wish Deepgram had a colo option in USEast-1 in AWS, given how ubiquitous that particular region is for US businesses. I don't want to self-host Deepgram at our present scale, but also don't want to rely on numerous public Internet gateway hops. That's unfortunate because we are presently stuck in the middle somewhere. Review collected by and hosted on G2.com.

The best thing about Deepgram is that it lets users try the platform’s STT and other modules first using trial credits, which helps them get a fair understanding of the product before deciding to buy it. Review collected by and hosted on G2.com.

So far, I haven’t figured out any issues that I would say I disliked. Review collected by and hosted on G2.com.