AE-1
A private AI workspace for teams that work in Arabic and English.
The AE-1 Core. One workspace for chat with files, memory and web search, connectors, decks and PDFs, schedules, Messages and the admin console, in six languages.
Explore AE-1Three products. One boundary.
A private assistant for your people, the model that does the thinking, and the engine that trains models on your data. All of it runs inside your walls.
S1
The intelligence model from Sharq.
From the S1 page. One model, made to understand what you mean and to do the work that follows.
Explore S1Open base modelYour model, trained on your records
Sharq Engine
Trains and serves models on your data, on your infrastructure.
Illustration. A fine-tuning run pulls a general model toward the way your organisation writes and decides.
Explore Sharq EngineFrontier models know the world. They don’t know yours.
A rented model has never heard your Khaleeji customers, read your credit policy or seen how your best agents close a case. Sharq takes what your organisation already knows and turns it into a model that works inside your world, and belongs to you.
| Hosted frontier API |  | |
|---|---|---|
| Arabic adaptation | General‑purpose ArabicUsually steered with prompts and examples. | Fine‑tuned on your conversationsYour own Gulf, Levantine or Egyptian conversations, scored on dialect evals. |
| Data residency | Set by the providerIts hosting regions and its data terms. | Your racks or your cloudYour cloud account in a UAE or KSA region, or Sharq’s in‑region hosting. |
| Pricing model | Usage‑basedUsually per token. | Pilot fee, then a platform planCompute billed at cost. The weights are yours to keep. |
| Policy controls | Applied through promptsSystem prompts and the provider’s safety settings. | Trained into the modelChecked on policy‑adherence evals before each release. |
| Model updates | The provider’s scheduleReleased when the provider decides. | A cadence you approveRetrained on your team’s corrections. |
What a run looks like.
The console your team works in, from first dataset to a served model.
Open the consoleRelease gate3 of 3 over the frontier baseline
15:07:14eval at step 3,900: gulf-dialect 0.80, policy 0.93
15:20:14epoch 3 done: gulf-dialect 0.81 +0.19 against baseline
15:20:14run complete, weights written to s3://collections-assist/run-03
Try it. Point along the line, pick an eval, pause the run, change the base model and start another, then deploy it.
Illustrative run, computed in your browserMeasured on the numbers you already report.
We don’t quote savings in advance. Every pilot is judged on the operating metrics the business owner already tracks, against the stack you use today.
| Baseline Your current stack, measured in weeks 1 to 2 | Pilot model The same cases, side by side, in weeks 9 to 10 | |
|---|---|---|
| Arabic task successHow often the model gets the task right in your customers’ dialects, including code-switched Arabic and English. | % of tasks, not measured yet | % of tasks, not measured yet |
| Cost per taskWhat each completed task costs to run, compute included, compared with what you pay per task today. | per task, not measured yet | per task, not measured yet |
| Case throughputCases resolved per agent, per day, in the workflow the pilot targets. | cases per agent, per day, not measured yet | cases per agent, per day, not measured yet |
| Left blank on purpose. Results are measured on your own workload and reported to you. | ||
How a pilot runs, week by week.
One workflow where your current stack is too expensive, too inconsistent or not allowed to leave the country. Twelve weeks later you have a private model and a benchmark to prove it.
Weeks 1 to 2
Listen
We sit with your operations team and your records, and learn what the work actually is. One workflow, one owner, one number that has to move.
You bring Call recordings, tickets, documents. The messy real thing.
You get A data audit and a written target for the pilot.
Weeks 3 to 8
Train
Your data is cleaned, stripped of personal details and labelled by dialect. We fine-tune an open model on it, inside your environment, and iterate against Arabic evals every few days.
You bring Two hours a week from a domain expert to review samples.
You get A model that speaks like your best agents, and the dataset behind it.
Weeks 9 to 10
Prove
Side by side with what you use today, on live cases, on the outcome you named in week one.
You get A benchmark report: task success, cost per task, throughput.
Week 11 onwards
Improve
The model joins the team. Accepted edits and escalations become the next training set, on a cadence you approve.
You get Quarterly refreshes, each one re-checked against the same evals.
One platform, from raw records to a served model.
Every stage runs where your data lives. Your team can watch, approve and roll back at each one.
Where your data lives
Data foundry
Calls, chats, scans and records become training-ready material, with private details removed before anything is touched.
- Arabic OCR for scanned forms and letters
- Personal data removal, logged
- Dialect and code-switch labelling
- Versioned datasets
Guided training
Choose a base model and a target; the platform picks the method, the hardware fit and the schedule.
- Qwen, Llama, Mistral, Falcon and Jais families
- LoRA and full fine-tuning
- Runs on your GPUs or ours, in‑region
- Every run reproducible from its config
Regional eval lab
Judged on the Arabic your customers actually write and say, and on the rules your regulator cares about.
- Gulf, Levantine, Egyptian and Maghrebi suites
- Policy-adherence and safety checks
- Red-team sets in Arabic and English
- A regression gate before every release
Private serving
The finished model runs as an endpoint inside your walls, with an audit trail your governance team can read.
- Your VPC, your racks, or Sharq in‑region
- Model registry with lineage
- Residency attestation per deployment
- Feedback captured for the next refresh
Built for the work that costs you the most.
We start where the volume is high, the language is local and the current tooling is either expensive or not allowed.
Bankingالخدمات المصرفية
Retail and corporate banks with Arabic-speaking customers and strict residency rules.
- Collections conversations
- KYC document review
- Complaint triage and response
- Credit policy assistant
Telecomالاتصالات
Contact centres handling millions of code-switched conversations a month.
- Agent assist in dialect
- Call summarisation and QA
- Churn-risk conversation flags
- Self-service chat
Governmentالجهات الحكومية
Entities that cannot send a citizen’s record to a foreign cloud, full stop.
- Citizen-service case handling
- Arabic form and letter processing
- Policy question answering
- Bilingual document drafting
Real estateالعقارات
Developers and brokerages answering buyers and tenants in Arabic and English, on every channel.
- Enquiry qualification and follow-up
- Listing and brochure drafting
- Sale and lease agreement review
- Buyer and tenant service chat
Legalالخدمات القانونية
Law firms and in-house teams working across Arabic and English documents, in confidence.
- Contract review and comparison
- Arabic and English legal translation
- Case and precedent research
- Drafting from your own templates
Insuranceالتأمين
Insurers handling claims and policy questions in dialect, under local regulators.
- Claims intake and triage
- Policy question answering
- Claim document checks
- Renewal and collections calls
Healthcareالرعاية الصحية
Hospitals and clinics whose patient records have to stay inside the country.
- Patient scheduling and follow-up
- Clinical note summarisation
- Arabic medical form processing
- Insurance pre-approval drafting
Energyالطاقة
Operators with decades of technical records and crews who work in two languages.
- Maintenance report search
- Safety incident summarisation
- Procedure and manual assistant
- Bilingual contract drafting
Banking
الخدمات المصرفية
Retail and corporate banks with Arabic-speaking customers and strict residency rules.
- Collections conversations
- KYC document review
- Complaint triage and response
- Credit policy assistant
Telecom
الاتصالات
Contact centres handling millions of code-switched conversations a month.
- Agent assist in dialect
- Call summarisation and QA
- Churn-risk conversation flags
- Self-service chat
Government
الجهات الحكومية
Entities that cannot send a citizen’s record to a foreign cloud, full stop.
- Citizen-service case handling
- Arabic form and letter processing
- Policy question answering
- Bilingual document drafting
Real estate
العقارات
Developers and brokerages answering buyers and tenants in Arabic and English, on every channel.
- Enquiry qualification and follow-up
- Listing and brochure drafting
- Sale and lease agreement review
- Buyer and tenant service chat
Legal
الخدمات القانونية
Law firms and in-house teams working across Arabic and English documents, in confidence.
- Contract review and comparison
- Arabic and English legal translation
- Case and precedent research
- Drafting from your own templates
Insurance
التأمين
Insurers handling claims and policy questions in dialect, under local regulators.
- Claims intake and triage
- Policy question answering
- Claim document checks
- Renewal and collections calls
Healthcare
الرعاية الصحية
Hospitals and clinics whose patient records have to stay inside the country.
- Patient scheduling and follow-up
- Clinical note summarisation
- Arabic medical form processing
- Insurance pre-approval drafting
Energy
الطاقة
Operators with decades of technical records and crews who work in two languages.
- Maintenance report search
- Safety incident summarisation
- Procedure and manual assistant
- Bilingual contract drafting
Questions teams ask before a pilot.
Anything missing, ask us directly. Conversations are confidential and we reply within one business day.
What exactly do we end up owning?
The model weights, the curated dataset behind them, and the evaluation suites used to judge them. You can export all three at any time and run the model without Sharq.
Where do our data and model live?
Wherever you say: your own racks, your cloud account in a UAE or KSA region, or Sharq’s in‑region hosting. Nothing is copied outside the environment you approve.
Do we need our own AI team?
No. Sharq engineers run the pipeline. Your side contributes what only it can: a domain expert for a couple of hours a week to review samples and outcomes.
How do you judge Arabic quality?
Dedicated evaluation suites for Gulf, Levantine, Egyptian and Maghrebi dialects, Arabic–English code-switching, cultural alignment and policy adherence, alongside the business metric the pilot was scoped on.
Which base models do you use?
Open-weight families such as Qwen, Llama, Mistral, Falcon and Jais, sized to the task. Most production pilots land between 7B and 27B parameters, which is what keeps cost per task low.
How does the model keep improving?
Corrections, escalations and outcomes from real work are folded back into the training set on a cadence you approve. Each refresh is re-checked against the same evals before it is promoted.
Tell us about the workflow.
Pick the one where your current stack is too expensive, too inconsistent or not permitted. We will come back with a pilot plan, a data checklist and a number to beat.