Why results are defensible
Trust in a transcript does not come from confidence scores alone. It comes from a process that can be examined, explained and independently reviewed.
Your material is processed on our own infrastructure. It does not pass through public cloud transcription services by default. Processing arrangements, storage and retention conditions are defined as part of the project scope.
Every recording is processed through multiple independent recognition and analysis paths. Where independent paths agree, the evidence becomes stronger. Where they differ, the divergence is documented and taken into account — not silently resolved by picking one result arbitrarily.
Nothing is finalised automatically. A working baseline is selected through a documented, traceable process involving operator review. You receive a result that has been deliberately chosen — not the first output produced.
Passages where recognition confidence is low are marked explicitly. They are not silently corrected or omitted. You can see where the limits of the transcript are — because knowing those limits is part of what makes a transcript trustworthy.
Your original material is never modified. Processing is performed on a controlled copy. The source remains intact and untouched throughout processing.
Every project is accompanied by a documented account of how the material was processed — including inputs, processing conditions, selected versions and uncertainty flags. The resulting output can be explained, reviewed and, where necessary, independently assessed.
Being explicit about limitations is part of what makes a process trustworthy. We do not make claims we cannot stand behind.
We do not claim perfect accuracy for difficult material.
Degraded recordings, strong accents, overlapping speakers and poor source quality introduce real limits. We document those limits. We do not pretend they do not exist.
We do not claim universal multilingual accuracy.
Language conditions, code-switching patterns and recording quality affect what is achievable for multilingual material. We assess your collection before committing to a processing approach — because the conditions of your material determine what approach is appropriate.
We do not offer instant automated output.
Controlled processing, operator review and structured delivery take time. If volume and turnaround speed matter more than documentation and review, we are probably not the right match.
R2 Mechanics is a member of NVIDIA Inception, a program designed to support companies developing AI and accelerated-computing technologies.
For R2 Mechanics, participation supports our ongoing work in applied speech and audio analysis. The program provides access to technical resources and an ecosystem relevant to the continued development of our processing methods and infrastructure.