ekhos.ai

EKHOS AI covers the core transcription needs in one on-device application: transcription of audio and video files, speaker identification, live microphone and live speaker transcription, support for 98 languages, and a built-in media player for proofreading. All of it runs locally on your machine — the site states there is no cloud service, no telemetry, and no usage limits. The main conditions to be aware of: it is Windows software installed from the Microsoft Store, it requires a machine that meets the listed hardware requirements, and full use requires an account (free or Premium).

Feature overview

How the privacy model shapes the feature set

The distinguishing feature is not a single capability but where processing happens. EKHOS AI is described as professional-grade transcription software for legal, medical, law enforcement, journalism, research, and podcasting work, and it runs on your device rather than in the cloud.

Two consequences follow:

• No usage caps. Because transcription runs locally, the site advertises unlimited transcription rather than metered minutes.
• Data stays local. The site states no cloud and no telemetry, and that transcription libraries are stored on the local hard drive. One reviewer specifically notes that this keeps information off third-party servers — the reason they chose it over cloud alternatives.

The trade-off is hardware. Local AI transcription depends on your own machine, and the site publishes separate hardware requirements and installation instructions. A user reports that MP3 transcription runs particularly fast when it can use the video card's memory, which suggests GPU capability is a meaningful factor in speed.

Getting from install to a finished transcript

1. Create your account — sign up to Free or Premium.
2. Confirm your email — click the verification link sent to your inbox.
3. Install the EKHOS application — available from the Microsoft Store; check the hardware requirements and installation instructions first.
4. Transcribe — load an audio file, or use live mic / live speaker mode for real-time capture.
5. Proofread — use the built-in media player to check the transcript against the source audio, with speaker labels in place.

Expected result: a transcript on your own device, with speakers distinguished and no data sent to a cloud service.

Common sticking points

• Platform. Installation is via the Microsoft Store, so this is a Windows workflow; the site does not describe a macOS or mobile version.
• Hardware first. Because the AI runs locally, an underpowered machine will affect speed. Review the hardware requirements before installing rather than after.
• Account required. Even the free path starts with account creation and email confirmation — it is not a download-and-run tool.
• Live vs. file. Live mic and live speaker transcription are separate modes from file transcription; pick the mode that matches whether your audio already exists or is happening now.

Who this fits

If your work involves confidential recordings — legal, medical, journalistic, research, or law-enforcement material — the on-device model is the reason to consider EKHOS AI, and the 98-language coverage plus speaker identification covers most multilingual, multi-speaker material. If you need transcription on a non-Windows device, or you would rather not manage local hardware requirements, a cloud service will be a better fit despite the privacy trade-off. Pricing details are listed on the site's pricing page.

AI audio transcription converts speech into text by combining signal processing with machine learning models trained on huge amounts of paired audio and text. In practice, the pipeline runs through several stages: audio preprocessing, acoustic and language modeling, punctuation and formatting, and—if enabled—speaker diarization and summarization. Accuracy is not a single fixed number; it depends on recording quality, accents, background noise, overlapping speech, vocabulary, and how well the chosen language is supported. This article explains each stage and the practical factors that move accuracy up or down, so you can judge when automated transcription is enough and when human review still matters.

The core pipeline: from sound wave to readable text

1. Audio preprocessing

Before any speech recognition happens, the file is normalized and cleaned up. Typical steps include:

• Resampling to a consistent sample rate (commonly 16 kHz for speech models).
• Channel handling: mono conversion or selecting the dominant channel when stereo tracks differ.
• Noise reduction and gain normalization to bring quiet speakers up and steady loud peaks.
• Voice activity detection (VAD) to find where speech actually occurs and skip silence.

Good preprocessing improves everything downstream. A clean, consistent input gives the model less to compensate for.

2. Speech recognition (acoustic + language modeling)

Modern systems use neural networks—often transformer-based—that map short audio frames to probable words or subword units. Two components work together:

• The acoustic model estimates which sounds were spoken.
• The language model estimates which word sequences are plausible in the target language.

The decoder combines both to produce the most likely transcript. This is why context matters: a model that "knows" a phrase is common will favor it over a phonetically similar but unlikely alternative.

3. Punctuation, casing, and formatting

Raw recognition output is a stream of words. A separate step adds:

• Sentence boundaries and punctuation.
• Capitalization of proper nouns and sentence starts.
• Number, date, and currency formatting.

These are learned from text data, so they follow the conventions of the training material rather than any single style guide.

4. Speaker diarization

Diarization answers "who spoke when." The system extracts voice characteristics (embeddings) from each speech segment, clusters similar segments, and assigns labels like Speaker 1, Speaker 2. It works best when speakers sound distinct and don't talk over each other. Overlapping speech and similar voices are the main failure modes.

5. Summaries and derived outputs

Once a transcript exists, summarization models condense it into key points, action items, or topics. Because summaries are generated from the transcript, any transcription error can propagate into the summary. Speaker labels also let a summary attribute statements to the right person—if diarization was accurate.

What actually affects accuracy

Accuracy varies widely by conditions. The table below summarizes the main factors and their typical effect.

Language coverage and multilingual models

A system advertising "54+ languages" does not mean equal quality in all of them. High-resource languages (English, Spanish, French, German) usually have more training data and better accuracy. Lower-resource languages may show more errors, especially with specialized terms. Multilingual models can handle code-switching—mixing languages in one conversation—but results depend on how much mixed-language data the model saw. If your content is in a less common language, test a sample before committing.

Domain-specific vocabulary

Names, product terms, medical or legal jargon, and acronyms are frequent error sources because they're rare in general training text. Many tools let you supply a custom vocabulary or keyword list to bias the decoder. This is one of the highest-leverage fixes you can apply.

Practical steps to improve your results

1. Record well. Use a close microphone, a quiet room, and a consistent setup. This single step often matters more than any setting.
2. Use one speaker per channel when possible; it makes diarization trivial and more reliable.
3. Add a custom vocabulary for names, brands, and technical terms.
4. Choose the correct language explicitly rather than relying on auto-detection, especially for short clips.
5. Review the transcript against the audio for high-stakes content.
6. Check speaker labels if attribution matters; correct them before generating summaries.

A simple quality-check template

For any important recording, run this quick pass:

• [ ] Does the transcript match the audio in the first two minutes?
• [ ] Are proper nouns and numbers correct?
• [ ] Are speaker labels consistent and correctly assigned?
• [ ] Do punctuation and paragraph breaks aid readability?
• [ ] Does the summary reflect the actual discussion, not just keywords?

When human review is still needed

Automated transcription is fast and increasingly accurate, but certain situations call for a human pass:

• Legal, medical, or financial records where a single word changes meaning.
• Heavily accented or overlapping speech in noisy environments.
• Highly technical content with dense jargon.
• Anything published under your name where errors carry reputational cost.

A common workflow is machine transcription first, then targeted human editing—this captures most of the speed benefit while controlling risk.

Choosing a tool: what to compare

When evaluating transcription software, compare on the dimensions that match your use case:

• Language support for your specific languages, not just the headline count.
• Speaker detection quality if you need attributed transcripts.
• Custom vocabulary support.
• Export formats (SRT, VTT, DOCX, JSON) for your downstream tools.
• Summarization if you want derived outputs.
• Pricing model—check the vendor's current pricing page, since plans and rates change.

Sonix, for example, positions itself around transcription in 54+ languages with AI summaries and speaker detection, and offers a free trial without a credit card. Verify current features and pricing directly on its site, as these details evolve.

Bottom line

AI transcription works by cleaning audio, recognizing speech with acoustic and language models, then adding punctuation, speaker labels, and summaries. Accuracy is driven less by the model alone and more by your recording conditions, language, vocabulary, and whether speakers overlap. Improve the input, supply domain terms, and reserve human review for high-stakes content—and you'll get reliable results from automated transcription in most everyday cases.

EKHOS AI keeps transcription private by running its AI models locally on your own device rather than in the cloud. According to the site, audio is processed on your machine, with "No cloud. No telemetry. No limits," and the software "works offline." This matters most if you handle sensitive recordings — legal, medical, law enforcement, journalism, or research material — and don't want the audio or transcript touching a third-party server. If you only need occasional transcription of non-sensitive files, the privacy architecture is less of a deciding factor.

The core mechanism: local AI, not cloud AI

The privacy claim rests on where the computation happens. EKHOS AI describes itself as "professional-grade transcription software" that runs "on your device," with libraries stored on the local hard drive. That means:

• Audio stays on your machine. The transcription model processes the file locally instead of uploading it to a remote server.
• No telemetry. The site states there is no telemetry, so usage data isn't sent back to the vendor.
• Offline operation. Because the models run locally, transcription can work without an internet connection.

The practical consequence: there is no third-party server in the transcription path that could receive your audio. That is the specific claim to evaluate, and it's the one a reviewer on the site echoes — Tjerk notes the software "runs standalone and stores all libraries on the local hard drive," which "ensures that the information doesn't end up on a third-party server."

What "private" does and doesn't cover

Local processing removes the cloud from the transcription step, but it doesn't make every part of the workflow offline. Based on the site's own setup steps, some account-related actions still involve the vendor:

So the privacy guarantee applies to the audio and transcript content, not to account creation or app installation. If your concern is specifically that recordings or transcripts reach a server, local processing addresses it. If your concern extends to any vendor contact at all, note that signup and email verification are still part of getting started.

Why this matters for sensitive work

The site positions EKHOS AI for "legal, medical, law enforcers, journalists, researchers, podcasters and more." For these users, the risk isn't transcription quality — it's where the data goes. A cloud service, by design, requires uploading audio to someone else's infrastructure. A reviewer (Ron) frames the choice exactly this way: he wanted software that "could transcribe locally without data going to a cloud."

Two conditions make the local approach worth it:

• Your recordings contain information you're obligated or prefer to keep on-premises (client conversations, patient notes, source interviews).
• You can meet the hardware requirements. Local AI models need a capable machine. The site links to hardware requirements and installation instructions, and one reviewer notes "the PC needs to be set up correctly for this." Check those requirements before committing — this is the main trade-off of local processing versus cloud.

How to verify it yourself

You don't have to take the privacy claim on faith. After installing:

1. Disconnect from the internet and run a transcription. If it completes offline, the model is genuinely local.
2. Watch your network activity during a transcription job. Local processing shouldn't show sustained upload traffic of your audio file.
3. Check where files are stored. The site says libraries live on the local hard drive, so you can confirm transcript and model files are on your disk.

The offline test is the most direct: a cloud-dependent tool can't transcribe with no connection, while a local one can.

The bottom line

EKHOS AI's privacy model is local-first: AI runs on your device, audio isn't uploaded, there's no telemetry, and it works offline. That makes it a reasonable fit when keeping recordings off third-party servers is a hard requirement and your hardware can run the models. It's a weaker fit if you want zero vendor interaction (signup and email verification still happen) or if your machine can't meet the local-processing requirements. The site lists pricing starting at $9/month with a 25% saving, and offers a free signup option — check the pricing page for current terms before deciding.

EKHOS AI lists a Premium plan at $9 per month, shown on the site as saving 25%. The site also offers a free sign-up path alongside the Premium option, so you can start with an account before deciding whether to upgrade. The main practical difference the site states is unlimited transcription — that is the headline benefit attached to the paid tier, while the free tier is presented as an entry point rather than a full working plan.

What the site says about pricing

Two things are worth noting. First, the $9/month figure appears on the homepage as a promotional rate with a stated 25% saving, so the standard monthly price may be higher than $9 — the pricing page is the place to confirm the current number. Second, the site does not publish a detailed free-vs-Premium feature table on the homepage, so the exact limits of the free tier (minutes, file count, language access, or export options) are not something you can verify from the homepage alone.

What Premium appears to include

The homepage pairs the price with a set of capabilities that describe the product as a whole:

• Unlimited transcription — stated directly next to the price
• Speaker identification — separating who said what
• 98 languages supported
• Works offline
• Local AI processing — no cloud, no telemetry
• Media player for proofreading
• Live mic and live speaker transcription
• Transcribe any audio file

Because the site presents these as product features rather than a tiered comparison, treat them as "what EKHOS AI does" rather than a confirmed Premium-only list. If you need to know whether, say, speaker identification or live transcription is available on the free tier, that is a question for the pricing page or support.

How the sign-up flow works

The site lays out three steps:

1. Create your account — choose "Sign up to Premium" or "Sign up to Free."
2. Confirm your email — click the verification link sent to your inbox.
3. Install the EKHOS application — install from the Microsoft Store.

The site links to hardware requirements and installation instructions at this stage. This matters for a buying decision: EKHOS AI is a Windows desktop application distributed through the Microsoft Store, not a browser tool. Before paying, check the hardware requirements page — one user review specifically notes that "the PC needs to be set up correctly for this," and that GPU memory is used to speed up transcription of MP3 files.

Is Premium worth it for your use case?

The upgrade case is strongest when your transcription volume is high and your content is sensitive.

Premium makes sense if:

• You transcribe regularly enough that per-use limits would interrupt your workflow — the "unlimited" framing is the core selling point.
• You handle confidential material (legal, medical, law enforcement, journalism, research) and want processing to stay on your machine. The site's positioning is explicit: "No cloud. No telemetry. No limits."
• You work offline or on restricted networks.
• You need multi-language work — 98 languages are listed.

Consider staying free or looking elsewhere if:

• You only transcribe occasionally and the free tier covers that volume.
• You are not on Windows, since installation is via the Microsoft Store.
• Your machine does not meet the hardware requirements, particularly if you want the GPU-accelerated speed one reviewer describes.

What users report

The homepage carries several reviews. A user named Tjerk describes transcribing Dutch conversations and meetings, notes that MP3 transcription "works particularly well by utilizing the video card's memory," and says he would recommend it over cloud alternatives because data stays local. Ron cites privacy as the reason for choosing it and praises support responsiveness. Dominic calls the interface intuitive and the accuracy "great." Sarah highlights the customer service experience.

These are vendor-hosted testimonials, so read them as directional rather than independent. The recurring theme — local processing as the reason to pay — does match the product's stated design.

Before you buy

• Open https://ekhos.ai/pricing to confirm the current price, whether $9/month is promotional, and what the free tier actually limits.
• Check the hardware requirements and installation instructions linked from the sign-up steps, especially if you want GPU-accelerated transcription.
• Confirm the Microsoft Store listing is available in your region.
• If your decision hinges on a specific feature (live transcription, speaker ID, export formats), verify whether it is included at your tier rather than assuming from the homepage feature list.

The short version: EKHOS AI's paid tier is advertised at $9/month for unlimited, fully local transcription on Windows, with a free sign-up available as a trial path. The price and the free-tier boundaries are the two details you should confirm on the pricing page before committing.

EKHOS AI is a transcription application that runs entirely on your own computer instead of in the cloud. It converts audio and video files into text with unlimited usage, and it is built for people who handle sensitive recordings — legal, medical, law enforcement, journalism, research, and podcasting are the audiences named on the site. If your main concern is keeping recordings off third-party servers, that is the problem it is designed to solve. If you only need occasional transcription and don't care where the data goes, the local-only design may be more than you need.

The core idea: transcription without a cloud

Most transcription services upload your file to a remote server, process it there, and send text back. EKHOS AI takes the opposite approach. The site describes it as "Private AI Transcription. On Your Device," with the stated promises of "No cloud. No telemetry. No limits."

In practice that means:

• The AI model and its libraries live on your local hard drive.
• Audio never leaves your machine during processing.
• The app can work offline.
• There is no usage cap tied to a server-side quota.

One reviewer on the site, Tjerk, describes exactly this setup: the software "runs standalone and stores all libraries on the local hard drive," which he says keeps information from ending up on a third-party server. He also notes that MP3 transcription uses the video card's memory, which speeds things up noticeably — a useful detail if you plan to process long files.

What it can do

The combination of speaker identification and a proofreading player matters for interview and meeting workflows: you can listen back and correct the transcript in the same tool rather than switching apps.

Who it is aimed at

The site names legal, medical, law enforcement, journalists, researchers, and podcasters. The common thread is recordings that are either confidential or too sensitive to hand to a cloud vendor — client consultations, patient notes, interviews with sources, field recordings.

A second reviewer, Ron, frames the choice plainly: he had "privacy concerns with transcribing audio files" and wanted something that worked locally. That is the decision EKHOS AI is asking you to make — local processing versus the convenience of a browser-based service.

How you get started

The site lays out three steps:

1. Create an account — sign up for Premium or for the Free tier.
2. Confirm your email — click the verification link sent to your inbox.
3. Install the EKHOS application — install from the Microsoft Store.

Two things to check before you commit: the hardware requirements and the installation instructions, both linked from the setup section. Because the AI runs locally, your machine's specs — particularly the GPU — determine how fast transcription goes. Tjerk's comment about the video card doing the heavy lifting is a hint that a machine without a capable GPU will be slower.

Pricing and platform notes

The site shows a price of $9/month with a "Save 25%" label, and there are separate links for Pricing and for "Sign up to Premium," implying a free tier and a paid tier. The page does not spell out what the free tier includes, so treat the free option as something to verify on the pricing page rather than assume.

Platform-wise, installation is described through the Microsoft Store, which points to Windows. The page does not state macOS or Linux availability.

How to decide

EKHOS AI is worth a closer look if:

• Your recordings are confidential and you want them processed on your own hardware.
• You transcribe often enough that per-minute cloud pricing or usage caps are a problem.
• You need speaker labels and a way to proofread against the audio.
• You work in one of the professional fields the site targets.

Look elsewhere if you need a browser-based tool with no installation, you're on a non-Windows machine, or your computer lacks the hardware the app requires. The fastest way to settle it is to check the hardware requirements against your machine, then try the free sign-up before paying for Premium.