Turn Zulu audio
do tekst, któremu możesz ufać.

A different approach to Zulu transcription.

Zulu transcription is the process of converting spoken isiZulu, in interviews, focus groups, calls, and recordings, into accurate, structured text. isiZulu is spoken by more than 12 million people, mainly in South Africa where it is one of eleven official languages, with speaker communities across Eswatini, Botswana, Lesotho, Malawi, and Mozambique. Speak AI transcribes it directly, alongside 100+ other languages, without routing it through a manual translation step first.

Why manual Zulu transcription breaks down

Most teams still handle Zulu recordings the slow way: a bilingual staff member replays the file, types out the words, and guesses at anything they mis-hear the first time. A single focus group or set of interviews can take a full day to turn into usable notes, and the tone, pacing, and emphasis in what was said gets lost the moment it becomes plain text. Tools built for English alone often mishandle Zulu’s click consonants and noun-class prefixes, forcing a second manual pass just to fix the transcript.

Reading isiZulu the way a fluent listener would

Speak AI reads Zulu recordings on three layers at once: the words themselves, the tone, energy, and emotion in how they were said, and, for video, what is happening on screen. Each recording is transcribed in your language, with 100+ supported, and can be translated to and from English on request. Names, speakers, and themes are extracted into structured fields, and Panele sterowania, które możesz dostosować i oznakować własną marką track sentiment and topic trends across recordings over time, so this quarter’s interviews are measured against last quarter’s.

What teams ask their Zulu transcripts

• “Summarize what every Zulu-speaking participant said about pricing this quarter.”
• “Which interviews mention delivery delays, and what exactly did people say?”
• “Show me every recording where the speaker sounded frustrated.”
• “Translate this Zulu focus group into English and keep the speaker labels.”
• “What themes came up most often across all the Zulu interviews this month?”

From a folder of recordings to a searchable archive

The result is a library your whole team can query, not a folder of files only one bilingual staffer can make sense of. Ask across your entire Zulu transcript history with AI chat, using ChatGPT, Claude, and Gemini built directly into the workspace, instead of exporting text and pasting it somewhere else. One California-based education program used the same embedded-recorder and automatic transcription pipeline to process 160+ hours of bilingual student submissions and save $4K+ in labor, without adding staff. And because Zulu recordings rarely stand alone, the same engine also scores and analyzes every other call, meeting, and interview your team runs through the serwer MCP, on the same criteria, in the same workspace.