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Retrieval-Augmented Generation (RAG) Services in Dubai

Turn your organisation’s knowledge into a reliable AI assistant. Stralya designs and operates Retrieval-Augmented Generation (RAG) systems that are cloud-native, secure, and ready for real business stakes in Dubai and across the GCC.
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RAG capabilities

What our RAG service includes

Stralya’s RAG offering covers the full lifecycle: from data ingestion and retrieval logic to LLM orchestration and front-end integration. We treat your AI features as first-class citizens of your digital product, engineered with the same rigor as any core module.

Core RAG components we design and deliver

Data ingestion pipelines for PDFs, web pages, databases, and internal tools, with cleaning, normalisation, and access control.
Chunking and embedding strategies tailored to your domain (real estate, finance, public sector, etc.) for optimal retrieval quality.
Vector database and search layer (including metadata filtering and hybrid search) deployed on your preferred cloud provider.
Prompt templates and orchestration logic that combine retrieved context with user intent, tuned for reliability and clarity.
APIs and microservices exposing RAG capabilities to your web or mobile applications in a secure, scalable way.
Monitoring, logging, and analytics to track performance, usage, and potential failure modes over time.

Optional add-ons for strategic projects

Advanced evaluation frameworks for RAG quality, including domain-specific test suites and human-in-the-loop review.
Multi-language support for English-first experiences with optional Arabic content handling, aligned with UAE market needs.
Custom admin dashboards for content teams to manage data ingestion, re-indexing, and AI behaviour without developer intervention.
Integration with your authentication, CRM, or ERP systems to personalise responses and enforce data access rules.
Performance optimisation and cost control for large-scale deployments with high traffic or heavy data volumes.
Whether you are launching a new AI-native product or enhancing an existing platform, we assemble exactly the RAG components you need – no more, no less. The result is a focused, maintainable solution that can evolve as your digital strategy and the AI ecosystem progress.

Designed for your most demanding stakeholders

Aligned with CTO and CIO expectations
We speak the language of architecture, observability, and risk. Your technical leadership gets a clear picture of how the RAG stack fits into your existing systems, what it costs, and how it will be operated in the long term.
Support for digital transformation leaders
For Digital Transformation Officers and business sponsors, we connect RAG capabilities to measurable outcomes: faster support, better search, higher conversion, or reduced operational load – with a roadmap, not just a demo.
Confidence for regulated and public-sector projects
Governmental and semi-governmental entities in Dubai need predictability, security, and accountability. Our processes, documentation, and fixed-price commitments are designed to meet these expectations.
Acceleration for startups and scale-ups
If you are building a product where AI is a core differentiator, we help you move from concept to robust implementation quickly, without sacrificing quality. Your team can focus on product and growth while we secure the technical foundations.

Delivery approach

How we build and ship your RAG system

Every RAG engagement is treated as a strategic web project, not a lab experiment. We combine solid software engineering, cloud-native architecture, and careful AI evaluation to ensure your solution is robust from day one. Our teams work closely with your CTO, digital leadership, or product owners in Dubai to align on risks, compliance, and long-term maintainability.

We start by clarifying where RAG adds real value: search, support, analytics, content generation, or internal knowledge. Together, we map your data sources, security constraints, target users, and success metrics. If RAG is not the right tool, we say so – and propose alternatives.
We design how your documents, records, and domain knowledge will be ingested, cleaned, chunked, and stored. This includes selecting the right vector database, defining metadata, and planning update workflows so your AI always reflects the latest information.
We architect the full RAG pipeline: retrieval strategies, ranking, prompt templates, and LLM orchestration. Everything is implemented as cloud-native services on your chosen cloud provider, with attention to cost efficiency, latency, and scalability.
We integrate the RAG capabilities into your existing or new web application: APIs, dashboards, chat interfaces, admin tools, and monitoring. The goal is a seamless user experience that feels like a natural extension of your product, not a disconnected chatbot.
Before go-live, we stress-test your RAG system with real scenarios, edge cases, and adversarial prompts. We measure quality, latency, and failure modes, then harden the system with guardrails, logging, and fallbacks. Once stable, we support your production launch and handover.
Post-launch, we can operate and evolve your RAG stack under a maintenance SLA: improving retrieval quality, adjusting prompts, onboarding new data sources, and adopting new LLM models as the ecosystem matures – without breaking your production environment.

Popular Questions

Find Commonly Asked Questions

Retrieval-Augmented Generation (RAG) combines a Large Language Model (LLM) with a search layer that retrieves relevant information from your own data before generating an answer. Instead of relying only on what the model was trained on, RAG grounds responses in your documents, knowledge base, or transaction data. For organisations in Dubai, this means you can build AI features that are more accurate, controllable, and compliant – ideal for real estate platforms, financial services, government portals, and internal knowledge systems.
A basic chatbot integration usually sends user prompts directly to an LLM API. This is fast to prototype but unreliable, hard to govern, and difficult to scale. Stralya’s RAG service, by contrast, builds a full retrieval and orchestration layer around the model: structured data ingestion, vector search, ranking, prompt engineering, guardrails, and monitoring – all deployed as cloud-native services. The result is a system that can be audited, tested, and maintained like any other critical web component.
Yes. Stralya is a cloud-native web development company and we design RAG architectures specifically for AWS, Azure, or GCP. We can deploy in your own cloud account, follow your security baselines, and integrate with your IAM, logging, and compliance tooling. This is particularly important for Dubai-based enterprises and government-related entities that must comply with local and sector-specific regulations.
Our preferred model is fixed-price, project-based delivery with a clearly defined scope, architecture, and acceptance criteria. This aligns with our project-first mindset and our commitment to outcomes. For highly exploratory or complex environments, we may combine a fixed discovery phase with a structured implementation phase, but we avoid open-ended, poorly scoped engagements.
Yes. Project rescue is one of Stralya’s core capabilities. We can audit your current RAG or AI setup, identify architectural and data issues, and propose a realistic recovery plan. Once agreed, we can refactor, stabilise, or rebuild the system under a fixed-price framework, with the goal of getting you to a reliable production state as quickly as possible.
We typically work with startups and scale-ups building AI-native products, SMEs and large enterprises undergoing digital transformation, and governmental or semi-governmental entities with critical digital mandates. The common pattern is a high-stakes digital asset – such as a portal, platform, or internal system – where AI must be reliable, secure, and maintainable, not just experimental.

Case Studies

Real solutions Real impact.

These aren’t just polished visuals they’re real projects solving real problems. Each case study 
apply strategy, design, and development.

View Work

Building a Monolithic Headless CMS with Next.js

A monolithic headless CMS, engineered with React and Next.js App Router to ship high-performance websites and product frontends fast, with clean content operations for non-technical teams.

6

weeks from first commit to production-ready CMS core.

3x

faster time-to-market for new marketing and product pages.

View Project Details
View Work

Mandarin Platform Project Takeover and Recovery

Taking over a third-party Mandarin e-learning platform to secure, stabilise and structure critical cloud-native components for long-term growth.

6

weeks to stabilise and secure the core platform after takeover.

0

critical incidents in production after Stralya’s recovery phase.

View Project Details

Client Testimonials

Projects delivered for ambitious teams

Professional, fast, and ultra-responsive. A company with a top-notch mindset.

Omar Ouhmad

CEO, Growth Hackerz

A company with a true entrepreneurial spirit: fast, professional, and above all, responsive.

Laurent Phillipe

CEO, MandarinMaster

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