Arabic Excellence
Arabic‑native tokenization, dialect coverage, and evaluation practices built for MENA deployments.
Why Arabic‑native matters
Arabic is not a simple translation layer. Tokenization, morphology, and dialect variability all impact accuracy, latency, and cost. Atlas prioritizes Arabic workloads so you get better results without translation overhead.
- Lower latency: better tokenization reduces unnecessary generation overhead.
- Higher quality: fewer fragmented tokens improves context integrity and consistency.
- Regional nuance: dialect support captures local idioms and intent.
Tokenization advantage
Arabic‑native tokenization reduces fragmentation compared to English‑first tokenizers. This improves speed and cost efficiency, especially for long‑form Arabic content.
English‑first models
Arabic words are often split into smaller fragments, increasing tokens and latency.
Arabic‑native routing
Atlas prioritizes Arabic‑optimized models and tokenization for better efficiency.
Dialect coverage
Atlas is optimized for Modern Standard Arabic and major regional dialects. Coverage evolves as we expand datasets and customer deployments.
Modern Standard Arabic (MSA)
Formal documents, public sector, education
Gulf (Khaleeji)
KSA, UAE, Kuwait, Qatar
Levantine (Shami)
Jordan, Lebanon, Palestine, Syria
Egyptian (Masri)
Egypt
North African (Maghrebi)
Morocco, Algeria, Tunisia
Evaluation approach
We evaluate Arabic performance across benchmarks, dialect‑specific prompts, and deployment‑level tests. Results are reviewed during pilots and can be shared upon request.
- Benchmark coverage for Arabic understanding and generation
- Dialect‑specific prompts and real‑world use cases
- Latency and throughput tests on customer‑like infrastructure
- Operational checks for routing, isolation, and security
Tuning guidance by dialect
For dialect‑specific performance, start with a focused dataset of high‑quality examples and iterate with evaluation feedback. We can help scope a tuning plan during a Free POC Pilot.
Start small, iterate fast
Begin with curated prompts and representative conversations for your target dialect.
Measure before you scale
Evaluate accuracy, tone, and response quality before expanding datasets.
Keep it in‑region
Use region‑appropriate sources and linguistic context to preserve nuance.
Align with routing strategy
Tune only the models you plan to route to in production.
Cost impact
Arabic‑native tokenization plus intelligent routing typically reduces cost by 40–60% depending on workload mix. You can validate savings during the Free POC Pilot on your own infrastructure.
Ready to build?
Start with the Quick Start guide or request a pilot to validate Arabic performance on your infrastructure.