4,000+
Finished audio hours delivered
High-fidelity, dialectal speech corpora
Arabic AI Data Infrastructure
Building IntelligenceThrough Better Data
MASNOOD helps enterprises, governments, and AI teams build reliable AI systems through high-quality Arabic data, annotation, transcription, model evaluation, and enterprise-grade linguistic intelligence.
Trusted by AI, Data, and Transformation Teams
32
Arabic dialects
97.4%
Verified accuracy
13,880+
Projects delivered
4,000+
Audio hours delivered
Arabic Dialect Coverage
SaudiGulfEgyptianLevantineNorth AfricanIraqi+26 more
Our Clients
Global technology leaders and healthcare institutions rely on our Arabic linguistic and data operations.
Operating Model
Arabic AI Data Lifecycle
Five disciplined stages from Arabic data acquisition to enterprise-ready AI outcomes.
01
Data Collection
Arabic voice and text acquisition
02
Validation
Quality review and verification
03
Annotation
Human-in-the-loop labeling
04
Evaluation
Model testing and performance review
05
Enterprise AI Systems
Reliable Arabic AI outcomes
Arabic Dialect Coverage
SaudiGulfEgyptianLevantineNorth AfricanIraqi+26 more
Proven at scale
Track record you can measure
Verified delivery metrics across enterprise Arabic data programs — not marketing claims.
17M+
Words processed
Transcription, translation, and annotation
13,880+
Projects delivered
Multilingual and Arabic-focused programs
97.4%
Verified accuracy
Cross-validated QA benchmark on major deliveries
32
Arabic dialects
Natively annotated across MENA regions
100%
Native annotators
Vetted in-region linguistic specialists
Impact highlights
Programs that moved the needle
Anonymized delivery snapshots from enterprise Arabic data engagements — measurable outcomes without naming clients.
Sector: Global speech AI
Pan-regional voice corpus at production scale
A tier-1 technology program required dialectal speech data across Gulf, Levantine, and Egyptian variants for ASR model training — with dual-pass QA and encrypted delivery.
- 4,000+ PFH delivered
- 32 dialect groups
- 97.4% verified accuracy
Sector: Healthcare & clinical AI
Clinical-grade Arabic transcription pipeline
A healthcare institution needed HIPAA-aligned Arabic clinical dictation datasets — bilingual medical terminology, PII redaction, and audit-ready documentation for procurement review.
- 97.4% accuracy benchmark
- HIPAA-aligned workflow
- PII redaction + AWS S3
Sector: Enterprise NLP & annotation
High-volume text programs across MENA
Continuous ingestion of Arabic text for sentiment, speaker ID, and dialect tagging — native annotators, calibration batches, and weekly milestone reporting at enterprise volume.
- 17M+ words processed
- 13,880+ projects delivered
- 100% native annotators
Sector: Sovereign & government AI
Secure Arabic data for national AI initiatives
Government-aligned programs demanded in-region collection, NDA-based contributor networks, SOC 2 / ISO alignment, and structured handoff with delivery certificates.
- NDA-governed delivery
- Dual-pass QA
- Encrypted cloud handoff
Figures represent aggregate verified delivery metrics across MASNOOD programs. Client identities withheld by policy.
The Arabic AI Data Challenge
The gap is not just language. It is data quality, context, governance, and repeatable delivery.
32 Arabic dialects
Projects must account for regional variation across six geographic groups — not one standard form of Arabic.
Limited high-quality Arabic datasets
Most available corpora lack dialect depth, consent trails, and governance.
Complex cultural and linguistic context
Intent, idioms, and local nuance directly affect model behavior.
Enterprise-grade security requirements
Data handling must satisfy procurement, privacy, and retention rules.
Core Capabilities
Enterprise-grade capabilities for Arabic AI data and model evaluation.
Arabic Data Collection
We source high-quality Arabic voice and text datasets across regions, dialects, demographics, and recording environments.
Request this serviceAudio Transcription
Human-verified transcription for calls, telephonic conversations, and speech datasets — verbatim output with diacritics, punctuation, phonetic rules, and tags such as [noise], [laughter], and [overlap].
Request this serviceData Annotation & Labeling
We classify, label, and enrich text and audio for sentiment analysis, speaker identification, dialect tagging, keyword labeling, and ML training workflows.
Request this serviceDialect Classification
We help AI teams classify Arabic data by dialect, region, speaker attributes, and linguistic context.
Request this serviceLLM Evaluation
We evaluate Arabic model outputs for accuracy, relevance, cultural appropriateness, safety, and linguistic quality.
Request this serviceAI Safety & Red Teaming
We test models for unsafe outputs, bias, hallucinations, cultural sensitivity issues, and Arabic-specific failure modes.
Request this serviceWhy MASNOOD
A model that combines broad Arabic coverage with disciplined enterprise operations.
Pan-Arab coverage
Dialects and regions represented from project design through collection.
97.4% verified accuracy
Human-in-the-loop review, calibration batches, and cross-validated QA benchmarks for linguistic nuance and precision.
Enterprise security
Access controls, encryption, and least-privilege handling built into delivery.
Scalable operations
Contributor sourcing and QA workflows that scale with project volume.
Linguistic expertise
Native speakers and reviewers who understand dialect, context, and cultural nuance.
Structured delivery
Defined stages from brief to secure handoff with audit trails.
From Requirement to Secure Delivery
Requirements → Project Design → Contributor Sourcing → Collection → Annotation → Quality Review → Secure Delivery
1
Requirement Discovery
2
Project Design
3
Contributor Sourcing
4
Data Collection
5
Transcription & Annotation
6
Quality Review
7
Secure Delivery
How We Work With Clients
From first inquiry to secure delivery — a transparent six-step engagement with 12–24 hour response times.
1
Initial Response
Every website or email inquiry receives a formal acknowledgment within 12–24 hours with next steps.
2
Discovery Call
A virtual session (Zoom or Microsoft Teams) to define dialects, speaker demographics, file formats, and security requirements.
3
NDA & Confidentiality
A mutual NDA is signed before any sample datasets or deep technical requirements are shared.
4
Proposal & Quote
A Statement of Work (SoW) covering scope, QA metrics, pricing, and delivery timelines — typically within two business days after discovery.
Packages for Every Stage
Pilot projects, enterprise volume programs, and strategic partnerships — with QA tiers matched to your scale.
Pilot / Startup
Proof of concept (PoC) and initial model testing.
Enterprise & Growth
Mid-to-large scale projects (50 to 500+ audio hours).
Custom & Global AI Partnership
Global tech enterprises requiring continuous data ingestion pipelines.
Built for Teams Advancing Arabic AI
Serving organizations building the future of Arabic AI.
AI Companies
AI companies need reliable Arabic datasets to improve speech, language, and conversational models.
Government
Government programs require secure, compliant, and locally relevant data operations.
Research Institutions
Researchers need curated datasets that reflect real linguistic diversity.
Universities
Universities can accelerate NLP and speech research through structured Arabic datasets.
Enterprise Data Teams
Enterprise teams need labeled, validated, and governed data to power analytics and AI initiatives.
Contact Centers
Contact centers can transform Arabic conversations into insight through transcription, classification, and sentiment analysis.
Quality and security are embedded into every MASNOOD engagement.
A disciplined approach to quality, confidentiality, delivery, and data governance.
Join the MASNOOD Contributor Network
Join a trusted network building high-quality Arabic AI data.
Native Speakers
Transcribers
Annotators
Linguistic Reviewers
Model Evaluators
Build better Arabic AI with enterprise-grade data.
Building the Arabic data layer for reliable AI systems through quality, security, and linguistic intelligence.