MASNOOD

MASNOOD

Operating Model

A structured operating model from requirement design to secure delivery.

1

Requirement Discovery

Clarify outcomes, data types, regions, risks, and delivery constraints.

Outputs

Validated brief, scope map, data taxonomy

Quality controls

Stakeholder review and acceptance criteria

2

Project Design

Convert requirements into workflows, guidelines, sampling rules, and review gates.

Outputs

Execution plan, labeling schema, security plan

Quality controls

Pilot batch and guideline calibration

3

Contributor Sourcing

Select vetted contributors by dialect, skill, geography, and project sensitivity.

Outputs

Contributor roster, training plan, NDA records

Quality controls

Identity checks and qualification tests

4

Data Collection

Collect voice, text, or operational datasets under controlled project rules.

Outputs

Raw datasets, metadata, collection logs

Quality controls

Sampling checks and environment validation

5

Transcription & Annotation

Apply structured transcription, labeling, enrichment, and dialect classification.

Outputs

Annotated datasets, transcripts, label reports

Quality controls

Dual review and conflict resolution

6

Quality Review

Measure completeness, accuracy, consistency, and linguistic quality before delivery.

Outputs

QA scorecards, error analysis, release notes

Quality controls

Acceptance sampling and audit trails

7

Secure Delivery

Package, encrypt, transfer, and confirm deletion or retention rules.

Outputs

Final data package, documentation, delivery certificate

Quality controls

Access controls and delivery verification

Hybrid 3-Phase Delivery Workflow

Automation accelerates throughput; native experts and QA gates protect accuracy — the model generic vendors cannot replicate at Arabic scale.

1

Phase 1 — Automated pre-processing

Python pipelines for format normalization, speaker diarization, silence trimming, and noise flagging before human review.

  • Audio segmentation
  • Diarization
  • PII detection scripts
  • Batch QC dashboards
2

Phase 2 — Expert native review

In-region linguists apply verbatim transcription, dialect classification, code-switching tags, and domain-specific schemas.

  • 32-dialect guidelines
  • Code-switching tags
  • Speaker metadata
  • Calibration batches
3

Phase 3 — QA audit & sign-off

Dual-pass verification, inter-annotator agreement checks, error taxonomy, and release scorecards before encrypted delivery.

  • Double-blind QA
  • Accuracy scorecards
  • Conflict resolution
  • Delivery certificate