LLMs
Bilingual domain LLMs with full MLOps.
Overview
Arabic/English LLMs fine-tuned on your domain, deployed in your jurisdiction, with retrieval-augmented generation, evaluation harnesses, and continuous training pipelines.
Capabilities
- Arabic + English fine-tuning pipeline with dialect coverage
- Retrieval over private knowledge bases and structured data
- Role-based access, redaction and PII guardrails
- Continuous evaluation harness with regression detection
- Operator console with usage, cost and safety telemetry
- Air-gapped or VPC deployment
From discovery to production
- STEP 1
Discovery
Two-week assessment of data, infrastructure and use-cases. Output: a sequenced rollout plan.
- STEP 2
Foundation
Stand up the platform inside your environment, networking, identity, observability, MLOps.
- STEP 3
Fine-tune
Continuous fine-tuning on your corpora with red-team gates between releases.
- STEP 4
Ship
Production rollout to the first cohort of users, with measured outcomes inside 12 weeks.
Tech stack
Where this ships
LLM Solution, Gulf Region
A national technology agency needed to accelerate public-service delivery under strict data sovereignty rules, without sending citizen data to third-party cloud LLMs. Existing workflows were manual, error-prone, and fragmented across ministries, with no unified AI capability and no way to deploy commercial LLM services within national security requirements.
Private Media Platform
A media group needed to differentiate against commoditised news, build an interactive reader experience, and guarantee editorial safety. They could not risk a data breach or a model that generated harmful or inaccurate editorial content, but they also needed to ship fast.
Common questions
Do you train from scratch?
Almost never. We fine-tune strong open-weight bases, faster, cheaper, auditable.
Where does the model live?
Inside your environment. On-prem, customer VPC, or sovereign cloud.
Ready to build sovereign AI?
Tell us what you're working on. We respond within one business day with a clear next step.