Portuguese Meeting Transcription Accuracy: We Tested 4 AI Tools (2026)

A solid Portuguese meeting transcription tool has to do more than just keep up with the conversation. AI meeting assistants are now a key way of taking all of the ideas and action points from your conversations in Portuguese and turning them into a way that they can fit into workflows and be easily managed, with minimal legwork.

The catch is that for Portuguese speakers, many tools are built English-first, and Brazilian Portuguese often has a rapid pace of speaking, fast contractions, a sprinkle of loan words, and is very easily a language that an anglicized tool might struggle to keep up with.

Equally, a summary is only as good as the words that have been captured; if these are captured incorrectly in any language, it can make everything that comes after it impossible to work with.

To see which tools actually hold up, we put four of the best-known meeting assistants through the same test: three real Brazilian Portuguese meetings, scored blind by two LLMs and a native speaker across accuracy, real-world usefulness, features, and security. Here is how they compared, before we get into the details.

Transcription Accuracy

Portuguese meeting transcription accuracy starts and ends with getting the words spoken in any Portuguese-language meeting correct. Meetings are often busy, with ideas, figures, and action items discussed at a rapid pace, going off on tangents, and capturing all-important information needed for ongoing decisions.

Portuguese, as a language, is nuanced around diacritics, contractions like pra and tá, loan words, and acronyms. Our testing confirmed this, with many of the tools struggling to capture nouns and figures when spoken rapidly, sometimes resulting in catastrophic errors.

tl;dv scored the best marks by a fairly wide margin, scored anonymously by both the LLMs (Anthropic’s Claude and OpenAI’s ChatGPT) and our native speaker. Below is the full line-by-line breakdown of how each tool performed.

Raw Accuracy of Portuguese Transcription

There were some critical errors in the basics of some tools, and the word error rate (WER) of some tools was so poor that they scored 0. Tactiq turned se aquele mercado é viável (viable) into se aquele mercado é ****, a term that is actually considered a slur and should be treated as a serious liability.

Equally, Read.ai turned receber cada vez mais voos into receber cada vez mais bolos, then aeroportos que não tem bolos. Bolos is the noun for cake, which is unlikely in a discussion about aviation.

In-Language Handling

tl;dv led the language-specific row too, 17 out of 20, with Read.ai close behind on 16 and Tactiq last on 10. This is the accent-and-spelling layer: holding the nasal ã, keeping á apart from à, spelling fígado rather than a phonetic guess.

The weaker tools often ended up leaning into incorrect, and sometimes invented, words as soon as the vocabulary became a bit technical. There was a medically based sound clip that exposed these weaknesses very clearly, with Gemini using the word flíguido, where the speaker said fígado (liver), and dropping the opening h from hepatologista to leave epatologista. Tactiq suffered here too, writing patologista, a different medical specialist altogether. Read.ai produced mutaconografia for ultrasonografia (ultrasound), a term that does not exist in any language.

tl;dv kept the real spellings intact, accents and all. Its output reads like Portuguese written by someone who speaks it, and was the clearest to our native speaker, who said it was the most accurate and the most legible of all the outputs. It was also the tool they would select when we did our native-speaker testing.

Entity Detection

Across all our language testing in Swedish, French, Japanese, and Spanish, proper nouns and numbers have often been weak points for some tools.

tl;dv handled this incredibly well in Portuguese, scoring the full points. It was able to manage the brand name of Sirolimus, whereas our three other tools gave different versions of the phonetic word. This was without adding any custom vocabulary. It was also able to retain the name of a company, Roche, whereas Tactiq tried to guess, turning it into rodovias (highways).

Numbers were another sticking point, and a key figure that must be captured correctly in any type of formal meeting. Tactiq shrank R$4 bilhões to R$4 milhões, a thousandfold miss. tl;dv’s issue was only formatting: it writes figures as words, so 30 milhões comes out as trinta milhões. Every digit is correct, but our native reviewer found the long-hand slower to scan than plain numerals, which is why tl;dv scored 4 out of 5 on numbers rather than sweeping the row.

Real-World Meeting Quality

The accurate transcription of meetings was the core of what we tested, but being able to take those raw outputs and turn them into actionable outcomes matters just as much. Meetings often come with decisions, actions to be taken, and follow-ups, so in this section, we took a look at how each tool handled the continuation and how easily these can be transferred into documentation that leads to progress.

Of all four tools, scored across the different areas, tl;dv achieved a score of 43, a solid lead over Read.ai, which was able to achieve 35. Tactiq followed on 33, and Gemini trailed at 26.

Diarization

This is how well each of the tools is able to isolate and name the different speakers from the audio. To test this, we uploaded the same clip directly to each of the platforms to see how well it was able to parse out the speech and correctly identify each speaker. tl;dv scored the full 10 points and was able to isolate and correctly attribute speech to each speaker. Read.ai, at 6, was able to correctly identify the multiple speakers, with some issues on attribution, whereas both Gemini and Tactiq allocated all speech to a single speaker and achieved a score of 2.

The clip used was a medical-based hearing, with a regulator, a doctor, and a named deputy trading turns. Where Gemini and Tactiq fused every voice into one, this means that a clinical point from the doctor can read as if the deputy said it, and indicates that the incorrect attribution could lessen the impact and authority of the notes and summaries.

The key here is that if you have more than one person speaking in a meeting, for Portuguese, Gemini, and Tactiq should be relied upon with caution, based on our testing.

Hallucinations & Inserted Lines

Both Read.ai and tl;dv were able to transcribe and generate summaries and outputs that were free from hallucinations and invented lines. Tactiq and Gemini both also scored well, but slipped slightly in a few areas. Gemini produced the oddest example of the set, dropping the phrase na escola (at school) into the middle of a discussion about liver failure in gene-therapy patients.

tl;dv and Read.ai invented nothing across all three sessions, which is why they share the top mark. Inserted text is the quiet danger here, because it reads fluently and gives no signal that it was never spoken, so a reader skimming the notes has no way to spot the fiction. Read.ai had one small slip of its own, dropping an English “Yeah.” into the middle of a Portuguese sentence about air routes, minor enough not to cost it the mark.

Summaries, Action Items & Chapters

This is where we looked at the tools’ ability to take the raw transcription data and turn it into a succinct, useful, actionable output for a Portuguese speaker. tl;dv was able to take full marks across several lines, including action-item extraction, auto-chaptering, and general usefulness, giving Portuguese-language directions.

tl;dv kept all of its summaries in Portuguese rather than switching to English, which matters when the notes go back to a Brazilian team. Read.ai landed in the middle: useful summaries and action items, but weak sectioning, so its notes were harder to navigate than tl;dv’s or Tactiq’s.

Tactiq was also able to give some solid action items, isolating the correct parts into the various chapters, in spite of the issues with the core transcription. Gemini offered the weakest summary of all the tools, missing specific action items and offering the least actionable takeaways of the four.

Capabilities and Features

On top of being able to accurately transcribe in Portuguese and take those discussions and turn them into results, there are also a range of features and capabilities that can help to integrate your meeting content into day-to-day workflows.

In this section, we took a look at the attributes and features that add to what each tool can do, with a top score available of 72.

tl;dv scored 66, Tactiq 59, Read.ai 57, and Gemini 40. Three of the four tools were very strong, offering a range of useful add-ons and features to make workflows run more smoothly. Gemini struggles against these specifically because it’s part of Google Workspace rather than being a standalone tool.

Portuguese (Brazil) UI Localization

One of the biggest challenges when working with English-first tools in languages such as Portuguese is that the transcription and outputs are often available in multiple languages, but the user interface is not. Of the tools that we tested, three offer Portuguese as an interface option: tl;dv, Gemini, and Tactiq. Read.ai can still transcribe and summarize in Portuguese, but it does not offer the option to have the software in the language. This means that if you don’t speak or read another language, it can be difficult to navigate the dashboard.

Voice Printing

One feature that only tl;dv has is voice printing. This is a setting that you can opt into, where the tool learns your voice, allowing for automatic voice recognition and attribution when out-of-the-box speaker naming isn’t available.

Custom Notes & Templates

Depending on the role you have and the type of business you are in, there are different requirements and needs for your meeting output. For example, a founder and a salesperson will both hold meetings but have very different requirements and takeaways from each other. This makes customization for elements such as notes and set templates incredibly useful. A sales team can have a default meeting template set up to feed into their CRM system that picks out key items from the conversation. Of the tools that we tested, only tl;dv and Tactiq have this option.

Native MCP Server

Many meetings are captured across Portuguese-speaking countries, and within them, there are many ideas, thoughts, and things to do that ultimately can end up just sitting in transcripts and meeting notes gathering dust. The ability to connect your tool to an LLM such as Claude or ChatGPT can unlock an incredible amount of opportunity to make sure that whatever the outcome of your meeting, it’s used in the most effective way possible.

tl;dv has a native MCP server that allows users to plug their meetings into their preferred LLM and draft follow-ups or question months of past calls in plain language, without exporting a single file. This is particularly useful for in-depth analysis of sales calls and forecasting, and it offers marketing and social teams the chance to mine customer insight for pain points and to confirm or inspire content, giving a quick and easy way to find out exactly what you need to know.

In addition to tl;dv, Tactiq and Read.ai both offer this as well. Despite Google leaning heavily into the MCP angle in 2026, offering MCP at the platform and developer level, it does not offer a native MCP that feeds into the popular LLMs. So, hypothetically, you can connect your Google Drive (where the transcripts and summaries live for Gemini) to a workaround, but it’s not a native MCP connection, unlike the others.

Custom Vocabulary

From our raw transcription, there were some rather amusing, but also some very serious, errors in specific words in Portuguese. This is understandable when dealing with heavy jargon or specific terminology, and in many of these instances, the ability to input custom vocabulary would be of real benefit and could have avoided some of these errors. For our testing, we did not add any custom vocabulary, but the ability to do so is on tl;dv, Read.ai, and Tactiq. Google’s Gemini does not offer this as an option.

Trust, Security

The final section of scoring for our Portuguese meeting accuracy piece was based on trust, security, and data. This is one of the most important areas of judgment around any software or tool, and is the one that is likely to get more scrutiny than others. In our assessment, we looked at areas such as regional hosting options, recognized security certifications, the position of each tool on training AI on your audio, data retention controls, the transparency of pricing, and whether there was a usable free tier.

This section is worth a total of 18 points, and the results were incredibly close, showing that each of the tools takes these areas seriously, which is reassuring for anyone who cares about how their data is protected. Both tl;dv and Read.ai scored a perfect 18 out of 18, with Tactiq and Gemini dropping one line each to finish on 15 points each.

Data Residency Options

Where your meeting data is stored matters whenever the conversation involves sensitive information.

Brazil’s data protection law, the LGPD, does not force companies to keep personal data inside the country, so local hosting is not a legal requirement in itself. Even so, the tools differ on whether they give you a say. tl;dv, Read.ai and Gemini all give you a choice of hosting region, so you can keep Brazilian meeting data in a location you control. Tactiq gives you no such option, so your recordings sit wherever it defaults, usually outside Brazil, with nothing you can change. That is the single row that cost Tactiq a perfect trust score.

Accreditation

Each of the tools holds some recognized security and data accreditation, such as SOC 2, ISO 27001, and GDPR compliance, so on this line, each tool scored full marks.

Free Tier Availability

When choosing a tool for Portuguese meeting transcription, it’s ideal to give it a test before you commit, especially with a language like Portuguese, where accuracy varies so much from tool to tool. tl;dv, Tactiq and Read.ai all offer a free tier, so you can run your own meetings through them and judge the Portuguese output before paying a cent. Gemini is the exception. Meeting transcription sits behind a paid Google Workspace or Gemini plan, so there is no truly free way to trial it first, and that is the reason that costs it a point here.

The Methodology

To give the fairest possible results, we ran our testing through a structured and standardized process.

The Test Set

The set covers three real Brazilian Portuguese meetings, all committee recordings from the Câmara dos Deputados, chosen to stretch the tools across different registers and subject matter.

The first was a public-sector policy session on air transport, dense with figures, percentages and sector terms, and delivered mostly as a single-speaker presentation.

The second was a public hearing on the safety of a gene therapy, the hardest of the three, with a regulator, a doctor, and a named federal deputy trading turns, plus a steady run of drug names, medical terms, and company names such as Roche and the immunosuppressant Sirolimus.

The third was a public-health debate on the taxation of tobacco, alcohol, and sugary drinks, thick with acronyms, institutions, and monetary amounts.

Each clip ran roughly ten minutes, with multiple speakers in the two hearings and a single presenter in the policy session. Accuracy and word error rate were measured against a near-verbatim Portuguese reference built from the official records and published materials, so every output sat on the same fixed ground truth.

The Review

The data that was collected was anonymized and scored against our matrix by both Claude and ChatGPT. We then asked our native speaker, Suellen Lorga, to look at the anonymized outputs to identify and rank each of the tools from a Brazilian speaker’s point of view. It was at this part of the test that we were able to confirm some of the more specific errors, reading directly against the audio.

In addition to the transcripts, we also looked at the summary, and then did an additional test by uploading one of the selected clips to the tools, rather than using the live audio. This allowed us to check the quality of the diarization when given a raw file.

The Tool Set

We tested four tools: tl;dv, Google Gemini, Tactiq, and Read.ai. Three of them, tl;dv, Tactiq, and Read.ai, are dedicated meeting tools that record a call, transcribe it, and build a searchable library around it. Google Gemini is the odd one out by design. We included it as the general-assistant option that a large number of Brazilian teams already have sitting inside Google Workspace, to see how a broad AI model copes with the same job against purpose-built rivals.

Each tool captured the three meetings live, by playing the audio as if it were a real meeting. We then ran a fourth pass on one of the clips, uploaded directly through each tool’s own upload function, to pull clean speaker separation and to give behavioral stability a second condition to be judged against.

For Gemini, which has no meeting-capture step of its own, that direct upload was a workaround, an m4a converted from the original mp4. Each tool ran on a current paid tier: tl;dv on Business, Gemini through a Business Starter Workspace account, and Tactiq and Read.ai on their paid plans, with no custom vocabulary added.

Engine & Plan Breakdown

Each of the four tools transcribes in its own way, and how that’s achieved comes down to the engine. It can also explain a lot about the spread of the accuracy. Some run a dedicated speech engine, one uses meeting-platform captions, and one keeps its engine private. Here is what sits under each.

Scope & Caveats

We ran our testing as fairly as possible, but there will always be some elements that impact the overall scores. So here’s what to keep in mind when reading our results:

• We focused on Brazilian Portuguese, selecting clips that typified this dialect. The overall ranking is a reasonable steer for European Portuguese, too, but the exact accuracy scores would shift.
• All three meetings were formal hearings from the Câmara dos Deputados. We picked these because they’re genuinely difficult, and include complex topics, jargon, and multiple speakers, but they won’t reflect every kind of meeting you might have.
• We captured the meetings live by playing the audio into each tool as if it were a real meeting, using a single-source audio feed, then ran a fourth pass by uploading one clip directly to pull clean speaker separation and to see how consistently each tool held up across both conditions.
• Everything ran on a paid plan with no custom vocabulary added, so what you’re seeing is how each tool performs straight out of the box.
• For the capability and trust scores, we marked each tool on whether a feature is available and works, not on how well it performs.
• These tools change all the time, so something that was missing when we tested may well have been added since.

What Is the Best Tool for Portuguese Meeting Transcription Accuracy?

On the strength of this test, tl;dv is the best Portuguese meeting transcription tool of the four we looked at, and the win isn’t by a narrow margin. It scored 184 out of 200, topping three of the four tiers and tying the fourth. More to the point, it won on the parts that actually decide whether a transcript is accurate or not. It had the lowest word error rate, the cleanest handling of accents and technical terms, and a solid diarization score when two of its rivals blended every speaker into one. It kept its summaries in Portuguese, and it was the tool our native reviewer said she would choose during blind testing.

Read.ai is a clear second on 154. It handled accents well and stayed steady across the different meetings, so it suits a team that wants exports and a live transcript and can live with the occasional slip, like the flights that became cakes.

Tactiq came third on 134. It is a genuinely feature-rich tool, but its Portuguese recognition let it down badly, including turning a routine word into a slur, so we would be cautious using it for anything high-stakes. This is obviously a single instance, but it was serious enough to note, and not something we have come across in our testing across tl;dv and other tools.

Google Gemini finished last on 122. It is convenient if you already live in Google Workspace, but as a dedicated Portuguese transcriber, it trailed on accuracy, on speakers, and on features. Even aside from the transcription accuracy in Portuguese, its real-world functionality and lack of ability to integrate as easily as other tools would be enough to keep in mind.

If you are a Portuguese-speaking team transcribing meetings that matter, tl;dv is our pick. Try tl;dv today in your own Portuguese-language meeting and see for yourself.