Professional transcription for teams in Sri Lanka.

Yes. Sinhala is one of the core languages we work with for clients based in Sri Lanka, alongside Tamil, English where relevant. Every project starts with an AI-generated first pass in Sinhala, and you can add a native-speaking reviewer whenever the content is sensitive, technical, or intended for a wide audience.

Yes. Sinhala and Tamil, alongside English used widely in business. Our reviewers are matched to the accent and speech style in your file, not just the language, because a model trained mostly on one accent can mishear names, numbers, and local terms that a locally-matched reviewer catches immediately.

Turnaround for Sri Lanka-based clients depends mainly on file length and audio quality, plus whether you add human review. Standard and rush options are both available, and we account for the UTC+5:30 time difference when scheduling review and delivery. As a rough guide, a short AI-only pass can be ready within hours, while a fully reviewed file for a longer recording usually takes a day or two. We'll confirm an exact estimate once we see the file.

Yes. For clients in Sri Lanka, AI transcribes your file first, and you can add a professional human reviewer for important content, complex audio, or specialized terminology before delivery. You're never required to add review. It is an optional layer you turn on for the projects where accuracy matters most, and skip for lower-stakes, high-volume work.

We regularly transcribe content for clients in Tourism & hospitality, Customer support & BPO, Technology & startups across Sri Lanka, along with teams handling one-off projects outside those industries. Each industry brings its own terminology and formatting expectations, and we adjust our process, from glossary handling to reviewer selection, to match what your sector actually needs.

It varies with audio quality, background noise, and accent. In Sri Lanka, that often means Sinhala and Tamil, alongside English used widely in business. This is exactly why we flag words the AI isn't confident about rather than guessing. If you add human review, a reviewer resolves every flagged word against the actual audio, so your final accuracy depends less on recording conditions and more on how much review you choose to add.

Yes. One-off transcript projects and ongoing volume both work for Sri Lanka-based teams. Recurring clients typically get a standing brief so terminology, formatting, and review preferences don't need to be re-explained each time. That standing brief can also lock in a rate for larger volumes and a consistent point of contact, so scaling up doesn't mean starting from scratch on every file.