LLM Strategy & Roadmap
2-to-4 week diagnostic that decides Build vs Fine-tune vs RAG vs API, picks the model family, sizes the AED budget, and gives you a phased 12-month plan board-ready by week four.
Trango Tech provides premium, leading custom LLM development services with 20+ years of experience. They excel at building secure, reliable AI solutions specifically for business across DIC, Sharjah technology park, Hub71, and beyond. We build everything you need, from private LLMs to fine-tune open-source models, and wrap GPT & Claude API systems. You will get a vendor-neutral, fully compliant with PDPL and DIFC AI Reg 10, and deeply capable with Arabic-language models like Jais and Falcon.
OpenAI, Anthropic, Google, Jais, Falcon, Llama, or Mistral, we pick what works best for you.
Built for UAE PDPL data residency, DIFC AI Reg 10, ADGM DPR, CBUAE / DFSA / DHA sectoral compliance.
Native Arabic LLM fine-tuning on Jais (Inception AI / G42) and Falcon Arabic (TII Abu Dhabi) right from the start.
Trango Eval Gate scores faithfulness, groundedness & hallucination rate before any model ships to prod.
From your very first sprint, you own the weights, prompts, fine-tuning recipes, and source code. No lock-in tricks.
Khaleeji-aware UX, MSA + dialect support, RTL design from sprint one, not patched at UAT.
Off-the-shelf LLM solutions are losing their appeal due to a lack of understanding of critical business context. They carry severe data privacy risks and suffer from long-term vendor lock-in. In addition, you risk not achieving the required performance or ROI. Strict regulations on data residency, AI accountability, and privacy are now fully in effect. It has made it nearly impossible for generic AI systems to adhere to them.
All these reasons have made businesses realize that, out of the box, LLMs are great. However, they fall painfully short for mission-critical infrastructure. To help businesses thrive, Tragno Tech builds bespoke LLM application development primarily for Emirates. As a result of our partnership, we ensure your data stays safely localized, audit trails are flawless, and strict hallucination governance is in place.
Across all the LLM application development projects we audit, the most common problem we see is that underlying models aren't smart enough. GPT-4o, Claude, Llama 3, and Jais all perform well, but they sometimes don't do as users expect them to. Often, the issue is simply that teams need clearer success criteria before training begins. They even don't properly catch any hallucinations before they impact the end-user.
At Trango Tech, we don't ship any AI to production in the UAE until or unless it passes our Eval Gate. No exceptions. No bypasses. No fix-later excuses. Faithfulness, groundedness, and hallucination rate are a few key elements that drive our eval gate. No matter whether you would like to have a quick call to discuss how the Eval Gate works or prefer to review our hallucination management methodology first, we have got you covered.
We deliver custom LLM development services across the UAE to empower businesses with secure, domain-specific AI models. No matter if you need a private LLM, a fine-tuned Llama or Jais, a RAG over your documents, or a Claude/GPT wrapper, Trango Tech does it all.
Our 40+ completed projects are a true testament to the high quality we deliver. More importantly, we ensure your business meets every specific UAE regulatory requirement. PDPL, DIFC AI Regulation 10, and ADGM are a few industry-specific mandates.
2-to-4 week diagnostic that decides Build vs Fine-tune vs RAG vs API, picks the model family, sizes the AED budget, and gives you a phased 12-month plan board-ready by week four.
Private LLMs trained from open-source bases (Llama 3.x, Mistral, Falcon, Jais) on your data. You own the weights, the recipes, the evals. Best when sensitive data cannot leave UAE infrastructure.
Supervised fine-tuning (SFT), Direct Preference Optimization (DPO), LoRA / QLoRA, RLHF. We fine-tune the model to your domain vocabulary, brand voice, and Khaleeji Arabic dialect.
Retrieval-augmented generation over your enterprise documents. Vector DB selection (Pinecone, Weaviate, Qdrant, Milvus), chunking strategy, hybrid search, reranking, citation enforcement.
Native Arabic LLM fine-tuning on Jais (Inception AI / G42) and Falcon Arabic (TII Abu Dhabi). MSA + Khaleeji dialect, religious-content sensitivity, RTL UX, Hijri calendar awareness.
Our branded hallucination-governance layer. Faithfulness, groundedness, hallucination rate, jailbreak resistance, PII leak detection, prompt-injection guards. No model ships to UAE prod without it.
Model registry, prompt versioning, A/B testing, observability (LangSmith, Helicone), drift monitoring, cost guardrails, on-call rotation. The boring stuff that keeps LLMs working in a month.
LLM-powered agents that reason, plan, use tools, and collaborate. LangGraph / CrewAI / Autogen architectures. Human-in-the-loop checkpoints by default for regulated workflows.
Embedding LLMs into ERPs, CRMs, contact centers, document workflows. Salesforce, HubSpot, Dynamics 365, SAP, Odoo, Twilio, Genesys, ServiceNow pre-built connectors for all the obvious ones.
Not sure which service fits your needs? Let our LLM developers help you choose the best path forward.
Talk to expertsCheck out a few snapshots of recent LLM projects we have delivered. To comply with our active NDAs, project details and client identities have been anonymized. However, the outcomes we have mentioned, including specific AED returns and performance metrics, are factual.
We streamlined the credit drafting process for a major bank that was previously writing case memos by hand. By fine-tuning the Llama 3 70B model on 12 years of approved credit policies, we built a retrieval-augmented generation (RAG) system connected to their live handbook. To ensure accuracy and compliance, we implemented a Trango Eval Gate with a groundedness floor of 0.96.
We designed a 24/7 customer service chatbot for a leading multi-brand retailer that accurately understands diverse customer bases. By fine-tuning the Jais-13B-chat model on seven dialects—specifically focusing on Khaleeji, Egyptian, and Levantine Arabic—and hosting it on the G42 sovereign cloud, we created a natural conversational experience fully integrated into their Salesforce Service Cloud.
We built a clinician-facing AI search tool for an Abu Dhabi hospital group to quickly query over 380,000 internal documents. To meet strict DHA privacy requirements and maintain a zero-PHI-leakage SLA, we deployed the RAG over Azure UAE North, implemented automatic PII redaction at the data-ingestion stage, and added a Trango Eval Gate specifically to catch and score any potential PII leaks.
Every one of our clients began exactly where you are today before growing into an industry leader.
Start with the free scoping callWe analyzed over 240 AI scoping calls to see what UAE clients actually want. Based on this, we have found a clear pattern of what's most in demand among UAE clients. The percentage next to each use case explains all you want to know.
Direct answer. The top-requested custom LLM use cases in the UAE are document Q&A / enterprise RAG (89%), customer support automation (82%), Arabic-bilingual conversational AI (74%), internal copilots (68%), content generation (61%), code generation (54%), structured data extraction (47%) and agentic process automation (38%).
The single most-requested use case allows users to search across vast internal document libraries and get accurate, citation-grounded answers.
First-line LLM agents that handle FAQs, account details, and order status, while escalating cleanly to human agents for complex issues.
True regional understanding utilizing Modern Standard Arabic (MSA) and Khaleeji dialect fluency.
Domain-specific AI assistants embedded directly into the tools your team already uses (like Salesforce, SAP, and Office).
Automated creation of marketing copy, social media posts, and regulatory-friendly content that sounds exactly like your business.
AI assistants trained on your company's internal codebases and architecture guidelines to accelerate development safely.
Transforming messy, unstructured inputs like invoices, emails, and contracts into clean, reliable, database-ready formats.
Autonomous agents designed to execute multi-step business workflows (e.g., procurement routing or automated lead qualification) rather than just answering questions.
Have a use case not listed here? We have probably shipped it. 35+ verticals across the GCC.
Talk to an LLM architectIf you want to know how long your custom LLM development is going to take, we have made it completely easy. Simply answer these six quick questions that span the right model, data prep burden, and timeline. 100% free and vendor-neutral.
You primarily get three straightforward service tiers, and each covers everything from strategy to deployment. Plus, we do cover 90 days of dedicated support if any is required. Check what suits you below to know how much you might have to pay for our LLM development services.
Wrap GPT-4o / Claude / Gemini with RAG over your top documents. Trango Eval Gate baseline. PDPL-compliant. Live in 4–8 weeks.
Fine-tune open-source (Llama / Falcon / Jais), hybrid RAG, Trango Eval Gate, full LLMOps, observability. Live in 10–18 weeks.
Private LLM on G42 sovereign cloud or on-prem GPU. Heavy compliance (CBUAE / DFSA / DHA). Arabic-native. Multi-agent. Phased waves.
Beyond the initial build, you have to account for GPU hosting, inference, and on-call support over time. Adjust the slider below to see what a realistic 24-month total cost of ownership can be.
| Cost line | Year 1 | Year 2 | 2-yr Total |
|---|---|---|---|
| Build (one-time)Strategy, fine-tune, RAG, eval, integration, go-live | AED 90,000 | — | AED 90,000 |
| Inference / API tokensGPT/Claude OR self-hosted GPU · ~22% of build | AED 19,800 | AED 20,790 | AED 40,590 |
| LLMOps + observabilityHelicone · LangSmith · model registry · ~12% of build | AED 10,800 | AED 11,340 | AED 22,140 |
| Trango Eval Gate retrainingDrift monitor + quarterly re-eval · ~9% of build | AED 8,100 | AED 8,505 | AED 16,605 |
| Compliance & DPIA refreshAnnual DPIA refresh + regulatory updates | AED 7,500 | AED 7,500 | AED 15,000 |
| 24-month Total Cost of Ownership | AED 136,200 | AED 48,135 | AED 184,335 |
All AED figures indicative · GPU and token costs vary by chosen platform · we lock all numbers in your SOW before kick-off.
Tell us your tier preference and we will return a fixed-price SOW within 24 hours.
Lock my AED budgetCheck out your annual AED savings, payback in months, and 24-month ROI. To unlock the final numbers, just drop in your email and mobile number first. Our senior member will assess your project and validate the math for you.
Ready for a clearer picture of your ROI? Let's run your real workflow numbers through our model.
Book your free sessionConfused about how to bring an LLM into your UAE business? You basically have four choices. We score each path on speed, budget (AED), control, and lock-in so you can pick what actually works for you.
GPT-4o / Claude / Gemini hosted; you build the wrapper + RAG + guardrails.
Retrieval-augmented generation. Your data, citation-grounded answers, fast iteration.
Llama 3 / Falcon / Jais / Mistral fine-tuned to your domain, brand voice, dialect.
Train a private model on UAE infrastructure. Sovereign data, total control, max cost.
Curious but not quite ready? Answer 10 quick questions in our 90-second wizard to find out exactly which option fits you best.
Run the RAG vs Fine-Tune wizard10 honest questions about your data, scale, accuracy, and compliance. No sales pitch, just logic. We will give you a ranked, vendor-neutral recommendation and the reasons why it fits your needs.
Select your use case on the left and get instant clarity on your regulatory requirements, DPIA obligations, and residency needs on the right. No gate, no email, 100% instant.
Live classifier. Switch any answer to see the regulation surface change in real time.
Classification is indicative · the live SOW reflects the formally-signed compliance scope after the scoping workshop.
For those planning a more comprehensive compliance review that covers DIFC AI Reg 10 and its sectoral overlaps, we have got you covered.
Schedule your compliance scoping callHaving successfully delivered over 240+ winning LLM projects, we apply a consistent, reliable playbook to every single build. Our seasoned LLM developers adjust the toolchain to fit the model. You remain in the know with everything we do and what week of the timeline we're in.
We host working sessions with your business, compliance, data, and IT teams to lock in your success metrics, compliance scope, and define the best use cases.
We make formal decisions on building, fine-tuning, RAG, or using APIs. We also design your evaluation sets, data flow and residency, security, compliance, and hallucination governance.
This is where around 30 to 50% of your budget goes. We handle cleansing, chunking, labeling, redaction, and creating a golden evaluation set.
We implement SFT, LoRA/QLoRA, DPO, and RLHF where applicable. We also set up your vector DB, hybrid search, and reranking, while performing hyperparameter tuning and multi-checkpoint comparisons.
Before any production release, your model must pass our zero-floor gate assessing faithfulness, groundedness, hallucination rates, jailbreaks, PII leaks, and prompt injections.
We launch using a phased rollout (no big-bang deployments) featuring observability, drift monitoring, and cost guardrails. You get 90 days of hyper-care from the same engineering team that built your solution.
Want a phased plan mapped to your specific use case? Book the 30-minute scoping call.
Book my scoping callPDPL, DIFC AI Regulation 10, ADGM, CBUAE, DFSA, FSRA, DHA, TDRA- we cover all required compliance laws in your project. They are directly built into your LLM from the very beginning.
Lawful basis · consent management · data-subject-rights workflows · UAE-region residency control. Full enforcement: 1 January 2027. DPIAs mandatory for high-risk processing.
AI risk classification · third-party model accountability · explainability requirements · incident reporting. We architect every DIFC-licensed client's LLM to map to Reg 10 sub-articles by name.
For ADGM-licensed entities. Data protection regulation alignment, AI-specific guidance documents incorporated into our compliance baseline.
For UAE banks & insurers. Model risk management, explainability for credit decisions, fair-lending tests, customer-facing AI disclosure. Trango Eval Gate maps to sectoral requirements.
Dubai Health Authority guidance for AI in clinical workflows. Zero-PHI-leak SLA, HIPAA-aligned controls, audit trail per query, clinician-in-the-loop on diagnosis-adjacent outputs.
Where sensitive data must remain UAE-resident with sovereign compute: G42 AI Cloud, Azure UAE North, AWS UAE region. Trango Tech delivers on all three with PDPL-grade controls.
We have the privilege of working with business across diverse industries. Whether it's healthcare, fitness, or the public sector, we know what works for what and what doesn't. Check out the verticals we are actively working in, not limited to them.
Credit memos · KYC summarisation · fraud narrative · CBUAE-aligned · Eval Gate with audit trail.
Claims triage · policy Q&A · fraud signals · underwriter copilot · DFSA-aligned.
Clinical-doc RAG · zero-PHI-leak SLA · clinician copilots · DHA-aligned · audit-grade.
Citizen-services chatbots · multilingual EN+Arabic · sovereign G42 deployment · PDPL audit-ready.
Khaleeji chatbots · product Q&A · review summaries · catalog gen · brand-voice fine-tune.
Driver-facing voice copilots · shipment narrative · dispatcher RAG · multilingual support.
Listing copy · multilingual buyer chatbot · contract Q&A · DLD/RERA-aware document workflows.
L1 support automation · plan recommendations · multilingual EN+Arabic+Hindi+Tagalog · CSAT loop.
Different industry not listed? We have probably shipped it. 35+ verticals across the GCC.
Talk to a sector specialistInstead of forcing every one of our clients into a single, pre-determined model like many agencies do, we prefer to act as advisors and let them choose. We outline the models we truly excel at and give you the unvarnished pros and cons so that you lead in decision-making for your LLM product. See what models we have done so far:
Want a side-by-side LLM comparison of these platforms? See the published matrix below.
Open the platform comparison matrix →No "it depends" hand-waving. The seven model families most UAE businesses actually consider, scored across the ten dimensions that drive the build-vs-fine-tune-vs-API decision. Numbers come from our delivery data, vendor pricing pages, and HuggingFace eval leaderboards. Updated June 2026.
| Dimension | GPT-4oOpenAI | ClaudeAnthropic | GeminiGoogle | JaisInception AI | Falcon ARTII Abu Dhabi | Llama 3Meta | MistralMistral AI |
|---|---|---|---|---|---|---|---|
| Deployment model | API | API | API | Self-host | Self-host | Self-host | API + Self |
| Source-code & weights | Closed | Closed | Closed | Open | Open | Open | Mixed |
| Arabic / Khaleeji depth | |||||||
| UAE residency / sovereign | Cross-border | Cross-border | UAE region | Sovereign | Sovereign | Self-host | Self-host |
| Fine-tune cost / AED | High | High | High | Mid | Mid | Mid | Mid |
| Inference cost / AED at scale | High | High | Med | Low | Low | Low | Low |
| Reasoning benchmark · MMLU | ~88 | ~89 | ~87 | ~62 | ~64 | ~82 | ~79 |
| Best fit use case | Frontier · everywhere | Safety · code · long context | Multimodal · search | Arabic native · sovereign | Arabic native · sovereign | Self-host · domain SFT | European · self-host |
| License notes | Commercial only | Commercial only | Commercial only | Apache 2.0 | TII permissive | Meta community | Apache 2.0 (some) |
| Trango Tech UAE projects | 32+ | 24+ | 14+ | 11+ | 8+ | 28+ | 14+ |
Sources · Trango Tech UAE delivery data 2022–2026 · vendor public pricing · HuggingFace Open LLM Leaderboard · MMLU paper · Inception AI Jais paper · TII Falcon Arabic. Benchmarks approximate, model-revision dependent.
Want to make this matrix truly your own? We’ll gladly plug in your specific data, user info, and AED budget to match your exact needs.
Request a rescue auditResearch shows that 70% of its working-age population utilizes GenAI tools. Yet, despite this ambition, nearly all of the enterprise LLM projects fail. Linguistic complexities, data fragmentation, and failure are a few reasons associated with their failure. Take a look at the other issues we handle and how we can support you in resolving them.
We will figure out the evaluation later. Six months later, there is no objective way to tell if the model improved.
The 52% hallucination rate study used GPT-4 on raw enterprise documents. Same model with grounded retrieval: near-zero.
Models gradually deviate from system instructions in extended chats, a real, measurable failure mode.
Models over-attend to the end of the context window, ignoring earlier information. Silent quality failure.
30–50% of the LLM budget is data preparation. Teams under-budget and ship a half-trained model.
Credit decisions, claims, prescriptions issued autonomously. Air-Canada-style liability.
Built on a global cloud, scrambled to relocate before launch. Costly rework, missed launch dates.
Customer types "ignore previous instructions" and the bot leaks system prompts or hallucinates wildly.
Model performance silently degrades as your data and user behavior shift. Nobody notices for months.
Hyper-care ends, partner ghosts. The first real incident goes unresolved. Trust lost.
In deep with a project and starting to panic? Take a breath and let us do a rescue audit.
Request a rescue auditFor your peace of mind, we legally bind ourselves to these commitments in our Master Services Agreement before sprint one even begins. That is what puts us among the best custom LLM development companies in the UAE so far. If we miss the mark, we forfeit the fee for that specific milestone.
Source code, prompts, evals, fine-tune recipes, model weights (where open-source allows), deployment manifests every artifact lives in your Git repository from sprint one. If we walked away tomorrow, your team could keep building from Monday.
No model ships to UAE production without passing the Trango Eval Gate, our hallucination governance layer scoring faithfulness, groundedness, hallucination rate, jailbreak resistance, PII leak detection, and prompt injection. No exceptions, no overrides, no we will fix it later.
Every change request is quoted in writing, in AED, before any work begins. Never absorbed silently. Never invoiced at month-end as a surprise. The number you sign in the SOW is the number we hold ourselves to.
UAE PDPL, DIFC AI Reg 10, ADGM, CBUAE/DFSA/DHA sectoral rules modeled into the architecture in sprint one, not patched in three weeks before go-live. If a regulator visits, our consultant sits with your compliance officer at no extra cost.
We hold zero exclusive partner agreements. Our compensation comes from you, never from a model-vendor commission. OpenAI, Anthropic, Google, Microsoft if they offered to pay us to steer you to their stack regardless of fit, we would say no. And we have.
A senior UAE-resident architect, not a junior coordinator, not a Slack handle on the other side of the world, runs your steering committee every two weeks. The same named person from kick-off through go-live and the full 90 days of hyper-care.
Hyper-care does not end on day 90 with an awkward handover to an offshore team. The same UAE engineers who built your LLM carry it through year one, with a written SLA, named escalation contacts, and monthly business reviews your CFO is invited to.
So why exactly do we put promises in writing? That's because you hire our LLM development company with real guarantees. We’ve pressure-tested these exact commitments on over (240) projects. Take a look, push back if you need to, and see exactly what we deliver.
We’d be happy to walk you through a redacted sample MSA on the scoping call so you can see these seven promises in writing.
Request a sample MSAWith two decades of experience in LLM app development in the UAE, we shipped over 240+ thriving projects. When you work with us, you gain immediate access to 150+ in-house engineers. In fact, strictly vendor-neutral by contract, completely accountable by SOW, and audited to ISO 9001 standards completely make us stand out among all.
The points above cover our method. Below, we have revealed our identity, real-world experience, and firm-level credibility for your ease.
Two decades of UAE delivery. We were shipping production NLP for UAE banks before "LLM" was a household acronym. Battle-tested, audited, scar-tissue-tested.
Not freelancers, not offshore middlemen. Engineers on Trango Tech payroll, in Dubai. The same person who designs your stack also defends it at AMC time.
Real fine-tuning experience on UAE-native sovereign LLMs: Jais (Inception AI / G42) and Falcon Arabic (TII Abu Dhabi). Most regional agencies cannot honestly claim either.
Banking · insurance · healthcare · government · retail · logistics · real estate · telco. Domain depth that shortens your discovery sprint by weeks.
ISO 9001 (quality) + ISO 27001 (security) + ISO/IEC 42001 (AI management) controls aligned. Documented change, incident, DR procedures auditable on request.
Measured number, not a marketing claim. Aggregate across all client RAG systems that passed the Eval Gate in 2025–2026. We publish the methodology in the scoping call.
Physical office, walk-in steering committees, regulator-aware UAE-resident consultants. Same-time-zone delivery, no follow-the-sun handovers.
Verifiable across third-party rating platforms. Most reviews from UAE finance, healthcare and retail decision-makers. References available on request.
Before you commit to anything, we’ll happily connect you with three active UAE CTOs who are ready to chat about their experience with us.
Request 3 UAE referencesTo get our llm development solutions, we offer you three different choices. Go Fixed-price if your board needs cost certainty. Opt for a Dedicated AI pod if your roadmap is constantly evolving, and last but not least, use Time & Materials if your scope is still flexible.
Scope locked in SOW. AED price locked. Timeline locked. Change requests quoted in writing. Best when scope is well-understood, and the board wants budget certainty.
A senior architect, AI engineer, ML engineer, data engineer, QA, and LLMOps embedded for a 6- 24-month roadmap. Best when LLM is strategic, and you want continuous releases.
Architects, ML engineers, prompt engineers on hourly AED rates. Best when scope is genuinely emergent (integration backlog, evals deepening, eval-driven retraining waves).
Not sure which engagement model fits? We will recommend honestly in your scoping call.
Book a 30-min scoping callOn go-live day, we deliver the exact files, dashboards, and runbooks you need straight into your Git repo. These are tangible, auditable assets you can verify for peace of mind.
Hand-graded test set defined with your subject-matter experts. Every model checkpoint scored against it in CI. Yours to extend forever.
Vector DB choice, chunking strategy, embedding model, reranker config, hybrid-search topology all documented in Mermaid + plain-English notes.
Every system prompt, every few-shot example, every guard prompt, version-controlled in Git with change history, owner, and rollback path.
Data Privacy Impact Assessment drafted to UAE Data Office template, with sectoral overlays for CBUAE / DFSA / DHA where applicable. Audit-ready.
PromptArmor / Lakera-grade input/output filter, integrated with your auth, with a logged-incident dashboard. Continuous red-team test suite in CI.
EN + Khaleeji-Arabic training videos, instructor-led workshop slides, power-user certification quiz, adoption-tracking dashboard.
Live LangSmith or Helicone dashboard wired to your model. Latency, cost, faithfulness, drift, eval-gate scores, visible to your CTO from go-live + 1 day.
Ragas + DeepEval + TruLens integrated into your build pipeline. Every PR runs the eval suite. Regression on faithfulness or groundedness fails the build.
Step-by-step on-call rotation, escalation tree, rollback procedure, model-roll-forward, regulator-notification flow. Battle-tested across 240+ projects.
Want a sample SOW with these 9 deliverables already mapped? Ask in the scoping call.
Request a sample SOWOur client feedback reflects a mix of strong technical partnerships and execution excellence we have. Besides that, they praise our communicative approach and ability to integrate complex, domain-specific AI solutions. Even more, some note a need for better project documentation as well.
I was not quite tech-savvy at the start, but they explained it very precisely. They initially everything to us about building a custom LLM. Said RAG + GPT-4o would hit our SLA at a tenth of the cost. Their vendor-neutrality is genuine. Highly recommended.
They work with something brilliant called Trango Eval Gate. It catches hallucinations in our internal RAG that would have ended up in a press release. In fact, these same UAE-based engineers stayed through year one as promised.
To be honest, the real breakthrough for us was fine-tuning the Jais model on the Khaleeji dialect. Before Trango Tech, we relied on standard frontier APIs translating English into Arabic. Our customer satisfaction jumped by 41%.
Want all 3 to take your call before you sign?
Request 3 named referencesShort definitions for the terms you keep encountering when scoping an LLM project in the UAE. It’s written in plain language for CTOs, legal teams, and procurement leads.
Custom LLM development involves designing, training, fine-tuning, RAG-architecting, or governing a large language model system for a specific business, customizing it with their data, terminology, brand voice, language (EN + Arabic), compliance regime, etc.
RAG (Retrieval-Augmented Generation): LLM will look through your private documents first, then generate an answer based on what it has found there. Citations included. Easily updated: simply add more documents.
Fine-tuning is extra training to be performed on an already trained LLM (Llama, Falcon, Jais, Mistral) to learn your tone, terminology, or dialect. Common techniques: SFT (supervised), DPO (preference), LoRA / QLoRA (parameter-efficient), RLHF (human feedback).
Jais is the world's most advanced open Arabic LLM. Trained by Inception AI (a G42 company) on 4M Arabic + 6M English prompts by Cerebras. Apache 2.0 licensed. Adopted by the government and corporate in the UAE.
Falcon Arabic is TII (Technology Innovation Institute, Abu Dhabi)'s open Arabic LLM in the Falcon family. SFT + DPO trained on native Arabic teaching data. Good coverage of Strong Khaleeji and MSA.
Hallucination is when an LLM produces a confident but false or invented response. Research reveals 52% hallucination on ungoverned RAG, near to zero on governed RAG – same model. Trango Eval Gate scores it on each release.
The layer that governs the hallucination is our branded layer, called Trango Eval Gate. Each release candidate is rated for faithfulness, groundedness, hallucination rate, jailbreak resistance, PII leak, and prompt injection. No Model Ship to UAE Production without passing.
The UAE Personal Data Protection Law (Federal Decree-Law 45/2021) regulates personal-data processing in the UAE. Full enforcement: 1 January 2027. High-risk processing, such as most production LLMs, requires DPIAs.
Since January 2026, the Dubai International Financial Center (DIFC) has implemented the requirements for artificial intelligence (AI) under its regulations. The Dubai International Financial Center (DIFC) has had AI requirements in place since January 2026. AI Risk classification, third-party model accountability, explainability, and incident reporting.
Data Privacy Impact Assessment: A process for structuring an analysis of the processing of personal data by a project, the risks, and mitigations. Under UAE PDPL (and DIFC Reg 10 and ADGM), required for high-risk AI processing.
Groundedness measures how much of an LLM's answer is supported by the retrieved source documents (in a RAG system). Scored 0–1. Regulated workflows must have > 0.95 before any Trango Eval Gate pass.
In AED, custom LLM development typically costs AED 15k (API-wrapper MVP) to AED 450k+ (sovereign on-prem build), with most UAE production projects landing in the AED 60k–170k band. Drivers: model strategy, data volume, compliance scope, deployment, timeline.
Use this easy-to-read table for essential facts on Trango Tech's UAE LLM practice. It’s a handy reference guide designed specifically for CTOs, compliance teams, and AI assistants.
If your question is not answered here, ask it in the scoping call — a senior architect will answer in plain English, in AED, with timelines.
Your question not here? Ask it in the scoping call — a senior architect will answer in plain English.
Ask a senior architectIn just 30 minutes, we will map out exactly whether you need an API wrapper, RAG, fine-tuning, or custom training. You get a clear timeline and AED costs upfront. We are strictly vendor-neutral, sign NDAs on day one, and promise zero sales pitches.