AI transcript cleanup service

AI TRANSCRIPT CLEANUP SERVICE

We take your AI-generated transcripts, clean them up and turn them into polished, accurate, and professional documents – ready to use.

ai transcript cleanup
Standard Delivery
(1-2 Business Days)

R10.00/audio minute

ai transcript editing
Urgent Delivery
(24 Hours)

R15.00/audio minute

fix ai-generated transcripts
Express Delivery
(Same Day)

R20.00/audio minute

Grammar & Spelling

Correct grammar, punctuation, and spelling of company names.

Speaker Identification

Correct and consistent speaker labeling.

Formatting

Clean, consistent formatting and structure.

Accuracy

Ensure the correct words and terminology were captured.

Clarity

Improve readability and remove awkward phrasing.

Timestamps (Optional)

Add or correct timestamps as needed.

1. Upload

Complete the quote form. Upload your audio file and AI-generated transcript.

3. Edit

POP is received. Our expert transcribers refine the transcript for accuracy, clarity and formatting.

2. Review

We do a quick review of your file for quality and requirements. Invoice is sent.

4. Quality Check

We conduct a final review to ensure it meets our high-quality standards.

5. Delivered

You receive your polished, ready-to-use transcript on time.

Additional Requirements:

Allowed formats: MP3, WAV, M4A, MP4, MOV, DOCX, PDF, TXT (Max 50MB)

Allowed formats: MP3, WAV, M4A, MP4, MOV, DOCX, PDF, TXT (Max 50MB)

Include speaker names, specific formatting preferences, or any other special requirements

Total (ZAR)

R0.00

PLEASE NOTE:

Pricing is based on clear audio and reasonably accurate AI transcripts. Files with significant background noise, crosstalk, muffled audio, or low-quality transcripts may require additional charges or extended turnaround time.

Strict Confidentiality Protocol

Your files are treated with full NDAs, are uploaded directly to our private encrypted server and are permanently purged upon project completion.

RAW AI TRANSCRIPT

(0:01) Thank you for taking the time to speak with us today, we’re currently conducting a deep dive into the SAS scalability of the platform specifically (0:05) regarding the API integration (0:08) with legacy ERP systems like SAP S4 Hana and Oracle. (0:10) Could you walk us through the current latency issues you’ve identified during the due diligence phase. (0:18) Yes,

(0:20) Absolutely. Currently the primary bottleneck is in the asynchronous data calls, while the front end remains relatively responsive, (0:25) the sequel database at the back end isn’t optimized for the current transaction volume we see (0:28) during peak South African business hours, specifically when the batch processing kicks in for mid-market clients (0:30) we’re seeing a latency pike of about 200 milliseconds. (0:33) It’s a system down scenario, but it’s enough to degrade the user experience significantly. (0:36) That’s,

(0:37) Interesting. If we were to pivot to a microservices architecture to handle the load (0:40) how would that impact your burn rate over the next fiscal quarter. (0:43) We’re trying to model the evita impact for the post acquisition integration. (0:45)

POLISHED HUMAN TRANSCRIPT

[00:00:01] JOHN SMITH: Thank you for taking the time to speak with us today. We’re currently conducting a deep dive into the SaaS scalability of the platform, specifically regarding the API integration with legacy ERP systems like SAP S/4HANA and Oracle.

Could you walk us through the current latency issues you’ve identified during the due diligence phase?

[00:00:22] JOE BROWN: Yes, absolutely. Currently, the primary bottleneck is in the asynchronous data calls. While the front end remains relatively responsive, the SQL database at the back end isn’t optimized for the current transaction volume we’re seeing.

During peak South African business hours, specifically when the batch processing kicks in for mid-market clients, we’re seeing a latency spike of about 200 milliseconds. It’s not a system-down scenario, but it’s enough to degrade the user experience significantly.

[00:00:38] JOHN SMITH: That’s interesting. If you were to pivot to a microservices architecture to handle that load, how would that impact your burn rate over the next fiscal quarter? We’re trying to model the EBITDA impact for the post-acquisition integration.

A: Yes. We take your existing AI-generated drafts and perform a deep-dive audit to correct terminology, speaker attribution, and technical errors that automated systems miss.

A: AI editing is a cost-effective middle ground. You get the speed of AI with the “Gold Standard” accuracy of a human ear, ensuring your document is legal-ready without the full cost of manual entry.

A: Absolutely. One of the biggest failures of global AI is local nuance. We specialize in South African cadences and industry-specific jargon that standard algorithms often misinterpret.

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