AI delivery
AI delivery
Corpshore Emirates brings the group's AI practice to the UAE from Dubai and Abu Dhabi, covering strategy, Arabic and multilingual data, annotation, RLHF, model evaluation, synthetic and robotics training data and intelligent automation. Corpshore AI is ranked fifth among the top 50 AI outsourcing companies worldwide, and that practice runs more than 15,000 AI seats across twelve or more countries in over thirty languages.
Most enterprises in the Gulf now have a model they want to build, fine-tune or govern, and a data problem in the way. The data is multilingual, it is often Arabic-first, and it has to move across borders under real regulatory constraint. Corpshore treats the data operation as the hard part of AI rather than an afterthought, and staffs it with annotation teams, linguists, ML-ops engineers and quality leads who work to a defined acceptance standard.
The UAE front of house sits in Dubai and Abu Dhabi, with the wider Corpshore AI network behind it for scale and rare-language coverage. That lets a client keep Arabic dialect work, regulated data and government-adjacent projects close to home, while pricing high-volume annotation and evaluation for the network. One contract, one account team and one governance layer cover the whole delivery.
What this service covers
AI strategy and roadmapping
Readiness assessment, use case definition and a phased roadmap that ties each model or automation to a measurable business outcome rather than a proof of concept that never ships.
Arabic and multilingual NLP
Data and evaluation work for Modern Standard Arabic, Gulf and wider dialects and low-resource languages, where clean labelled data is scarce and hard to source.
Data collection
Field and remote collection of text, speech, image, video and sensor data to a defined schema, including rare languages and underserved locales.
Data annotation and labelling
Text, image, video, audio and multimodal annotation run through a layered quality pipeline with inter-annotator agreement measured, not assumed.
RLHF and model alignment
Preference data operations, human feedback collection, ranking and rating, and red teaming support for safety and alignment work.
Model evaluation and red teaming
Structured human evaluation of model output against a rubric, adversarial testing and safety review across languages and dialects.
Synthetic and robotics training data
Synthetic data generation to fill coverage gaps and robotics training data including teleoperation, demonstration and sensor capture.
Intelligent automation and conversational AI
Intelligent document processing, robotic process automation and Arabic-capable conversational agents built and operated to a service level.
How it is delivered from the UAE
Delivered from Dubai and Abu Dhabi for Arabic dialect, regulated and government-adjacent work, with the wider Corpshore AI network of more than 15,000 seats behind it for high-volume annotation, evaluation and rare-language coverage. Projects run as managed deliverables or as dedicated teams embedded with the client, in Arabic, English and the language mix the model requires.
Small
5 to 15 specialistsA single project pod of annotators or evaluators with a project lead and a quality lead, suited to a pilot dataset or a single evaluation cycle.
Mid-market
15 to 60 specialistsDedicated annotation and evaluation teams by language and modality, each with a team lead, a linguist or domain specialist, an ML-ops engineer and a dedicated quality lead running agreement and acceptance metrics.
Enterprise
60 specialists and aboveA multi-language, multi-modality operation with a delivery manager, a quality and calibration layer, ML-ops and tooling engineers and an account director, blended across the UAE and the wider network.
Compliance and data handling
- Personal data in training and evaluation sets handled under UAE Federal Decree-Law No. 45 of 2021 (PDPL), with DIFC Data Protection Law 2020 or ADGM Data Protection Regulations 2021 applied where the client or the processing sits in those jurisdictions.
- Cross-border transfer of training data governed by a documented basis and data-handling agreement, with EU GDPR applied where data subjects or clients fall under it, so data that leaves the UAE does so on a defensible footing.
- Data provenance, licensing and consent recorded for collected and sourced datasets, so a client can evidence where each item came from and on what basis it may be used.
- Role-based access, workspace data minimisation and de-identification applied to sensitive datasets so annotators and evaluators see only what the task requires.
Technology
- The client's own annotation, evaluation and MLOps platforms, operated by our teams
- Annotation and labelling tooling across text, image, video, audio and multimodal work
- Human feedback, preference-ranking and model-evaluation tooling
- Data collection, quality-audit and inter-annotator agreement tooling
KPIs and reporting
- Annotation throughput. By modality and language, per shift and per project, trended against forecast.
- Inter-annotator agreement. Per task and per guideline version, with disagreement analysis feeding guideline updates.
- Quality and acceptance rate. Against the client's acceptance criteria, sampled by an independent quality lead.
- Turnaround time. From batch release to accepted delivery, per batch, against the agreed service level.
- Rework rate. Share of items returned for correction, trended to show guideline and training effect.
Governance cadence
Daily production stand-ups, a weekly delivery review with the client covering throughput, agreement and acceptance, a monthly business review against the service level agreement and a quarterly review of roadmap and quality trend. Guideline changes are versioned and calibrated with the client before they take effect.
Industry applications
Government and public sector
Arabic-first data collection, annotation and model evaluation with data residency and provenance built into the service.
Banking and financial services
Document processing, model evaluation and automation for regulated workflows, with masking and access control on sensitive data.
Technology and startups
Annotation, RLHF and evaluation at the pace a model team needs, from a first labelled dataset to continuous evaluation cycles.
Healthcare
Clinical and multilingual data annotation and evaluation handled under strict de-identification and access control.
Pricing and engagement models
Frequently asked questions
What does Corpshore's AI delivery practice actually cover?
It covers the full data side of AI. That means strategy and roadmapping, Arabic and multilingual data collection, annotation and labelling across every modality, RLHF and preference data, model evaluation and red teaming, synthetic and robotics training data, and intelligent automation and conversational AI, delivered as managed projects or dedicated teams.
How credible is Corpshore in AI data work?
Corpshore AI is ranked fifth among the top 50 AI outsourcing companies worldwide by Outsource Accelerator. The practice runs more than 15,000 AI seats across twelve or more countries and works in over thirty languages, including rare and underserved ones. That network sits behind the UAE delivery front.
Can the work be done in Arabic and Gulf dialects?
Yes. Arabic is a first-class delivery language, not an add-on. Corpshore staffs native speakers of Modern Standard Arabic, Gulf and wider dialects for collection, annotation, RLHF and evaluation, and extends into low-resource languages where clean labelled data is hard to source.
How is training data kept compliant when it crosses borders?
Cross-border movement runs on a documented legal basis and a data-handling agreement, under the UAE PDPL and, where relevant, DIFC or ADGM law and EU GDPR. Provenance, licensing and consent are recorded per dataset, and sensitive data is de-identified and access-controlled before it moves.
Do you use our tools or your own?
Either. Teams work in the client's annotation, evaluation and MLOps platforms where those are set, and bring category-standard tooling where they are not. We do not claim named vendor partnerships. The choice follows the client's stack and security position rather than a fixed template.
How do you measure quality on annotation and evaluation?
Quality is measured, not asserted. Inter-annotator agreement is tracked per task and guideline version, an independent quality lead samples output against the client's acceptance criteria, and rework and disagreement analysis feed back into guideline updates and targeted retraining.
Can Corpshore help before we have a clear AI use case?
Yes. The strategy and implementation service runs readiness assessment, use case definition and roadmapping first, so effort goes to a use case with a measurable outcome rather than a proof of concept that never reaches production. Data work then follows the roadmap.
How quickly can a data or evaluation programme start?
A pilot dataset or a first evaluation cycle can start within weeks of a signed contract and completed security review. Larger programmes ramp through guideline calibration, a pilot batch and quality sign-off before moving to steady-state throughput, so quality holds as volume grows.
Related services
- Ai strategy and implementation
- Arabic nlp and language ai
- Data annotation and labelling
- Rlhf and model alignment
AI, annotation, linguist and ML-ops roles across the UAE and the wider network are on the jobs board.
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