MANAGED AND SPECIALIST

AI that runs on your data.

Tailored, deployed and properly integrated.

HEMOdata deploys Claude and ChatGPT inside your enterprise — connected to your data, governed by your policies, and built to drive measurable outcomes.

DOES THIS SOUND FAMILIAR?

You’ve got the AI tools and everyone in the business uses them. But you’re still fragmented

Most GCC organisations have run an AI proof of concept. Few have a deployed, governed AI capability that actually changes how the business operates.

THE DATA PROBLEM

The AI gives confident answers that are wrong

“Generic AI answers from training data, not your data. Without RAG or proper grounding, hallucination is inevitable.”

siloed teams

Everyone is now using AI, on their own terms

“The warehouse says one thing, the CRM says another, and the data lake nobody maintains says something else entirely. AI needs clean, connected data to work from.”

regulatory concerns

We need to move fast with AI. Legal disagrees.

“Where does the data go, who can see it, and can we prove it later? Ungoverned AI deployments are a liability”

How we work

AI that fits your organisation. Not the other way around.

We integrate AI into your existing data stack, governance framework, and workflows, so it gets used effectively.

Systems integration

We connect Claude and ChatGPT to your CRM, ERP, data warehouse, and internal knowledge base — so your AI answers from your data, not generic training.

Governance by design

Every deployment includes data classification, access controls, audit trails, and PDPL/NDMO compliance built in from day one — not bolted on afterwards.

Outcome-led delivery

We measure success by business results — hours saved, accuracy improvements, conversion uplift — not just whether the model is running.
Choosing the right model

Claude or ChatGPT? Our honest answer: it depends

Different AI models have different strengths. We help you select, deploy, and govern the right combination for your specific use cases.

Use case
Anthropic Claude
OpenAI ChatGPT

Compliance & Governance
Regulatory document analysis & gap assessment

Knowledge Management
Internal knowledge assistant (RAG over your documents)

Content & Marketing
Automated marketing copy & multilingual campaigns

Customer Operations
Support automation, triage & customer communications

Finance & Reporting
Executive reporting, board summaries & financial analysis

Developer Productivity
Code assistance, documentation & internal tooling

Data & Analytics
Natural language querying over your data warehouse

HR & Operations
Internal comms, HR documents & process automation

Retrieval-Augmented Generation

Your AI should answer from your data. Not guess.

RAG is the difference between an AI that sounds confident and one that’s actually right. It connects the model to your own documents, databases, and knowledge bases, so every answer is grounded in what your organisation knows.

How RAG works
Grounded answers. Every time.
Instead of relying on what the model learned in training, RAG retrieves the most relevant content from your own knowledge base before generating a response.
1
User asks a question — in natural language, no SQL required
2
System searches your knowledge base — documents, databases, SharePoint, Confluence
3
Relevant content is retrieved — and passed to the AI model as context
4
AI generates an answer — grounded in your data, with source citations

Internal knowledge assistant

Give every employee instant, accurate answers from your internal policies, procedures, and documentation, without digging through SharePoint.

Regulatory intelligence

Query your compliance documents, SAMA/CBUAE filings, and policy library in plain English. Get answers with source citations.

Natural language data querying

Connect Claude to your Databricks or warehouse environment so business users query data in plain language with full lineage and governance.

Support grounded in your product

Connect Claude to your Databricks or warehouse environment so business users query data in plain language with full lineage and governance.

Industry use cases

From proof of concept to production.

Across the GCC and multiple sectors, HEMOdata has implemented AI integrations that solve real operational problems.

Financial Services

Automated regulatory reporting
Connect Claude to your compliance data to auto-draft regulatory reports, flag anomalies, and produce audit-ready documentation aligned with SAMA, CBUAE, and DFSA requirements.

Claude

Retail & E-Commerce

Personalised customer engagement at scale
Integrate ChatGPT with your CDP to generate hyper-personalised recommendations, email campaigns, and real-time support responses in Arabic and English.

ChatGPT

Government & Public Sector

NDMO & PDPL compliance acceleration
Use Claude to analyse your data inventory against NDMO and PDPL frameworks, identify gaps, and generate remediation plans — compressing months of work into weeks.

Claude

Media & Entertainment

Multilingual content operations

Deploy ChatGPT across your content pipeline to localise, reformat, and publish at scale across Arabic and English audiences with consistent brand voice.

ChatGPT

Enterprise Operations

Internal knowledge assistant
Build an AI assistant that searches across SharePoint, Confluence, and internal databases — giving your teams instant, accurate answers from your own documentation.

Claude ChatGPT

Data & Analytics

Natural language data querying
Connect AI to your Databricks or data warehouse so business users query data in plain language — no SQL required — with governed, reliable answers and full lineage.

Claude

OUR PROCESS

How we deploy AI in your enterprise

A structured engagement model, designed for organisations that have tried AI and stalled, and those starting from scratch.

AI readiness assessment

We evaluate your data quality, infrastructure maturity, governance posture, and existing tooling to identify the highest-value AI opportunities and blockers.

Use case prioritisation & model selection

We map your priorities to the right model — Claude, ChatGPT, or a hybrid — and define data connections, access controls, and success metrics.

Governed architecture design

We architect the integration with your data team, covering API design, prompt engineering, data masking, RAG configuration, and compliance documentation.

Pilot build & validation

We build and validate a working pilot in your environment, tested against real business scenarios with your stakeholders — before any broader rollout.

Production deployment & enablement

We deploy to production, train your teams, and hand over with full documentation — governance policies, usage guidelines, and a monitoring dashboard.

DISCOVERY

Understand your situation

Structured conversations before any recommendations. No pitching — just listening and asking the right questions about where you are.

PRIORITISATION

Mapping you to the right model

Whether it’s Claude or ChatGPT, we’re honest about what will work for your use case and business.

support

Ongoing optimisation & support

We provide ongoing support, model updates, and quarterly reviews to ensure your deployment continues to deliver ROI. 

CLIENT RESULTS

AI that actually works in practice.

Most AI consultancies lead with the model. We lead with the data, because that’s where 95% of AI failures actually originate. We won’t recommend an AI solution until we’re confident the foundations underneath it will make it reliable.”

Luke Cann
CEO & Co-founder — HEMOdata
Capability in practice

AI solution built for a leading GCC real estate developer

 

  • 3,500 dashboards compressed into a single LLM-powered interface
  • Drill-down analytics linked to geolocation points, viewable on a live map
  • Digital twin integration for exploring construction sites and completed buildings
Built on live enterprise data. Client name withheld by agreement.
40+
GCC clients across UAE, KSA & Oman
7+
Years operating in the GCC market

IS THIS YOU?

Ready to start, but not sure where?

AI consultancy looks different depending on where you’re starting from. We calibrate every engagement to your actual maturity.

“We’re being asked to deliver AI but don’t know if we’re ready for it yet or where we should start.”

Start with an AI readiness assessment. An honest evaluation of what you have, what’s missing, and what to fix first, before any AI investment is made.

“We’ve launched AI tools but they’re not being adopted and we don’t know why.”

Low adoption is almost always a data trust, change management, or output presentation problem and rarely a model problem. We diagnose and fix the actual issue.

“We want to build a sustainable, organisation-wide AI capability — not just pilot projects.”

An AI Centre of Excellence is the right next step, giving your organisation the structure, governance, and continuous pipeline to deliver AI at scale.