Offline-First Transcription Pipeline —
Transparent, Secure, and Archival-Grade

Secure Project Intake & Data Handling

All data exchange is handled via a dedicated, encrypted Nextcloud instance. Each client receives a personal account with private folders for uploads and project materials.

  Upload any source format (audio, video, mixed, or documents) — optional pre-formatting and conversion (e.g., container normalization, codecs, sample rate) according to institutional specifications.

  Store project materials together: contracts, raw files, client forms, and instructions in one secure workspace.

  An optional online intake form pre-collects all parameters (languages, duration, confidentiality level, delivery format); the workflow automatically initiates after upload confirmation.

  100% offline-first processing — encrypted transfer, no telemetry, and no third-party access.

GPU-Accelerated, Precision-Aligned Transcription

Transcription is performed locally using WhisperX-enhanced speech processing on high-performance GPU systems designed for institutional workloads. Each segment is aligned with frame-level precision, ensuring accuracy even in multi-speaker or noisy recordings.

  WhisperX-based alignment provides precise timestamping and consistent transcription continuity.

  GPU acceleration ensures fast turnaround even with long-form archives or large institutional datasets.

  Speaker-aware processing detects overlapping dialogue and preserves speaker identity for later structuring.

Transcripts are generated entirely offline — no telemetry, no cloud APIs, guaranteeing full data sovereignty and verifiable provenance for every output.

Structured Segmentation & Chapter-Level Navigation

After transcription, each recording is automatically segmented into logical chapters and speaker sections. This structuring enables intuitive navigation and review, forming the backbone for later HTML rendering and analysis.

  Automatic segmentation based on acoustic, linguistic, and contextual cues.

  Named speaker roles are assigned to each dialogue segment to ensure traceability and clarity.

  Time-synced chapter markers enable fast reference during playback and annotation.

Chapters and speaker boundaries can be manually refined or adjusted on request, ensuring maximum fidelity for archival, legal, or research-grade material.

Local Contextual Intelligence

Offline LLMs generate structured summaries, topic indexes, and entity maps — operating fully offline within the R2 Mechanics environment. This stage enriches the transcript with contextual understanding and cross-referenced metadata.

  Semantic side-notes and entity mapping connect people, places, and concepts within each transcript.

  AI-generated entity cards, topic indexes, and deep links provide precise navigation and contextual cross-reference.

  Multilingual context notes and time-aligned summaries enable cross-institutional collaboration and research exchange.

These AI-driven insights enrich each transcript with contextual understanding, enhancing archival value, verifiability, and long-term research usability.

Interactive, Navigable, Archival-Grade

Each transcript is rendered as a searchable, clickable, and media-synchronized HTML document. This ensures intuitive navigation, structured review, and long-term accessibility across archival systems.

  Chapters, timestamps, and speaker labels are linked to the audio timeline for in-place chapter playback.

  AI-generated entity cards, topic indexes, and deep links enable precise navigation and semantic exploration.

  Integrated playback and visual markup combine text, audio, and metadata for research-grade reproducibility.

Outputs are auditable and exportable offline (HTML, DOCX, optional PDF), ensuring reviewability, provenance, and sustainable accessibility for archival and institutional use.

Archive-Ready, Exportable, and Secure

Completed projects are securely stored and made available through the same Nextcloud account used for upload, enabling clients to download their finalized transcripts and reports directly. This ensures a continuous, verifiable workflow from project intake to final delivery — fully offline and audit-ready.

  Secure local storage and encrypted client download via dedicated Nextcloud instances — complete data control with no external dependencies.

  Optional WARC-standard export for long-term archival, integrity tracking, and compliance with institutional preservation standards.

  Integration-ready outputs (HTML, DOCX, PDF) for seamless inclusion in institutional repositories, digital archives, or automated document workflows.

All exports remain fully offline-first, preserving the same data sovereignty, security, and verifiable traceability that define the entire R2 Mechanics pipeline.