HR managers and business leaders query employee data, payroll reports, attendance patterns, leave balances, and headcount analytics — instantly, in plain English, from their own HRMS database.
Ask Your Database
Anything.
In Plain English.
Your Data Never Leaves Your Server.
DigiSurface's AI Text-to-SQL Chatbot converts plain English (or Arabic) questions into precise SQL queries - returning instant insights from your own database. Built for enterprises in India, UAE, Saudi Arabia, Oman & the entire Middle East that cannot send sensitive data to the cloud.
COUNT(e.employee_id) AS employee_count
FROM employees e
JOIN departments d ON e.dept_id = d.id
WHERE e.employee_id NOT IN (
SELECT DISTINCT employee_id
FROM leave_requests
WHERE request_date >= DATEADD(day,-90,GETDATE())
)
GROUP BY d.department_name
ORDER BY employee_count DESC
Your Data Never Leaves Your Building.
Ever.
Banks, real estate firms, and HR departments in India and the Middle East handle data that legally and ethically cannot go to external cloud servers. DigiSurface's on-premise AI is the only answer.
Your employee data, property records, and banking transactions never touch OpenAI, Google, or any external server. The AI model runs entirely inside your own network perimeter.
India's DPDP Act 2023, Saudi SAMA regulations, UAE Central Bank data residency rules, and Gulf banking compliance all require on-premise or private cloud deployment. eServe AI meets all of these.
We deploy an open-source large language model (LLM) on your private servers, tuned to your specific database schema. No subscription to OpenAI. No ongoing data-sharing agreements.
Business users in HR, sales, finance, or operations type a question in plain English or Arabic. The AI converts it to precise SQL and returns the result in seconds — without writing a single line of code.
No data migration required. The AI maps to your existing SQL Server, Oracle, MySQL, PostgreSQL. It learns your table names, relationships, and business logic automatically.
Users across UAE, Saudi Arabia, Oman, Qatar, and Kuwait can ask questions in Arabic. The AI understands the query, generates the SQL, and returns results — fully bilingual, fully on-premise.
Plain English In.
SQL Out.
Results Instantly.
Five steps. No cloud. No data leaves your premises. The entire pipeline runs inside your own server infrastructure — from the moment a user types a question to the moment results appear on screen.
"What is the total outstanding loan amount for customers in Riyadh with EMI overdue by more than 30 days?" — typed directly into the chat interface on your intranet.
The local language model (running on your server) understands the business intent of the question — customer segment, time condition, aggregation type — using your schema context.
The AI generates an optimised, schema-accurate SQL query mapped to your actual table names, column names, and relationships. No generic query — it knows your database.
The SQL executes against your on-premise SQL Server, Oracle, or other database. No data leaves your network at any point. Results are pulled from your own servers.
The answer appears as a formatted data table with a plain English summary — e.g. "127 customers in Riyadh have overdue EMIs totalling ₹4.8 Cr." Business users get the answer. IT never gets a call.
What Is On-Premise AI?
On-premise AI is the deployment of artificial intelligence models — including large language models (LLMs), document intelligence systems, and predictive analytics engines — entirely on an organisation's own servers or private infrastructure, without sending any data to external cloud providers such as Microsoft Azure, Amazon AWS, or Google Cloud.
At DigiSurface, we deploy on-premise AI for enterprises in the GCC — particularly Oman, Saudi Arabia, and the UAE — where data sovereignty regulations require that sensitive government, banking, and enterprise data must not leave the country. Oman's Central Institution for Technology Assurance (CITA) regulations require that AI systems processing regulated data operate on infrastructure within Oman's borders.
We deploy private LLMs (including Llama 2, Llama 3, and Mistral architectures) on enterprise GPU infrastructure, enabling organisations to run powerful AI capabilities — document summarisation, intelligent search, contract analysis, invoice processing, Text-to-SQL querying — without any internet connectivity for the AI model itself. With on-premise AI, your prompts, documents, and outputs never leave your network. For organisations handling regulated data — banking records, government files, confidential contracts — this is not a choice but a compliance requirement.
Quick Answer — What is On-Premise AI?
On-premise AI deploys large language models and document intelligence on an organisation's own servers — no data sent to cloud providers. DigiSurface deploys private LLMs for GCC enterprises where data sovereignty laws (including Oman CITA regulations) prohibit sensitive data from leaving national borders. Capabilities include Text-to-SQL querying, document processing, intelligent search, and predictive analytics on fully private infrastructure.
On-Premise AI vs Cloud AI — Decision Framework for GCC Enterprises
For regulated sectors in India and the GCC, on-premise is the only compliant option.
| Criteria | On-Premise AI (DigiSurface) ✓ | Cloud AI (Azure/OpenAI/Gemini) |
|---|---|---|
| Data Leaves Country | ❌ Never — stays on your servers | ✅ Yes — processed in cloud datacenters |
| CITA Oman Compliance | ✅ Fully compliant | ❌ May violate residency requirements |
| Internet Dependency | ❌ Zero — air-gapped capable | ✅ Required at all times |
| Model Customisation | ✅ Fine-tune on your data | ⚠️ Limited customisation |
| Ongoing Cost at Scale | ✅ Lower (no per-token charges) | ⚠️ Higher (token-based billing) |
| Best For | Banking, government, regulated GCC sectors | Non-regulated commercial use cases |
| DigiSurface Offering | ✅ Primary AI offering | ❌ Not offered |
GCC Data Sovereignty Laws — Country by Country
On-premise AI is required for regulated data in these jurisdictions.
| Country | Primary Regulation | Key Requirement | On-Premise AI Needed? |
|---|---|---|---|
| 🇴🇲 Oman | CITA IT Regulation | Sensitive data must remain in Oman | ✅ Yes — regulated sectors |
| 🇸🇦 Saudi Arabia | PDPL | Personal data processed locally | ✅ Yes — PDPL scope |
| 🇦🇪 UAE | UAE PDPL + ADGM/DIFC | Data residency for financial services | ✅ Yes — financial data |
| 🇶🇦 Qatar | PDPL 2016 | Personal data of Qatari residents | ✅ Yes — regulated sectors |
| 🇧🇭 Bahrain | PDPL 2018 | Cross-border transfer restrictions | ✅ Yes — regulated sectors |
| 🇰🇼 Kuwait | Data protection guidance | Government data localisation | ✅ Yes — government |
Three Industries. Three Deployments.
All Fully On-Premise.
DigiSurface has already built and deployed the Text-to-SQL chatbot across three enterprise verticals — tested, live, and ready to demonstrate to your team in India or the Middle East.
Real estate companies in India, UAE, and Saudi Arabia query property inventory, sales pipeline, rental yields, broker performance, and customer booking data — without writing a single SQL query.
Bank managers and analysts in India, UAE, Saudi Arabia, and Oman query loan portfolios, customer account data, NPA reports, transaction histories, and branch performance — fully on-premise, fully compliant.
Fully Isolated. Fully Private.
On Your Infrastructure.
Every component — the LLM, the SQL engine, the chat interface — runs inside your own server or private cloud. Nothing is shared. Nothing is external. This is what enterprises in India and the Middle East require.
On-Premise AI Deployment Across India & the Complete Middle East
We deploy on your servers — whether that's a data centre in Gurgaon, Riyadh, Dubai, or Muscat.
Gurgaon, Mumbai, Bangalore, Chennai
Dubai, Abu Dhabi, Sharjah
Riyadh, Jeddah, Dammam
Muscat, Salalah
Doha
Kuwait City
Manama
Private cloud deployments
Common Questions from IT & Business Leaders in India & the Middle East
Is the AI chatbot 100% on-premise? Does any data go to OpenAI or the cloud?
Yes, it is 100% on-premise. The AI model (an open-source LLM like Mistral, LLaMA, or similar) is deployed and runs on your own servers or private cloud. Your database, your questions, your SQL queries, and your results never leave your network. There is no connection to OpenAI, Google, Microsoft Azure OpenAI, or any external AI service. This is the core reason enterprises in India, Saudi Arabia, UAE, and across the Middle East choose our solution.
What databases does the Text-to-SQL AI chatbot support?
The chatbot works with any SQL-compatible database — Microsoft SQL Server, Oracle Database, MySQL, PostgreSQL, MariaDB, and others. It automatically maps your database schema (tables, columns, relationships, foreign keys) and uses this mapping to generate accurate queries. No schema changes are required on your existing database.
What use cases has DigiSurface built for the Text-to-SQL chatbot?
DigiSurface has built live, deployed use cases for three industries: HRMS (employee analytics, payroll queries, leave analysis, headcount reporting), Real Estate (property inventory, sales pipeline, rental yield, broker performance, lease management), and Banking (loan portfolio analysis, NPA reporting, EMI overdue tracking, CASA ratio queries, branch performance). All three run fully on-premise with no cloud dependency.
Does the AI support Arabic queries for our Middle East users?
Yes. The on-premise AI chatbot supports both Arabic and English language queries. Users in UAE, Saudi Arabia, Oman, Qatar, Kuwait, and Bahrain can type their questions in Arabic. The AI understands the query, generates the correct SQL, runs it against your database, and returns results — in Arabic or English as preferred. All of this happens entirely on your servers.
How long does deployment take and what is needed?
A standard on-premise deployment for one use case takes 2-4 weeks. This includes: server setup and LLM installation on your infrastructure, schema mapping and fine-tuning, query accuracy testing on your real data, user interface customisation, and team training. DigiSurface provides a free proof-of-concept (POC) on a sample of your data before you commit to a full deployment.
What hardware is needed for on-premise deployment?
Requirements depend on model size and concurrent users. For a small-medium deployment (up to 50 concurrent users): a server with 32–64GB RAM, a modern multi-core CPU, and optionally a GPU for faster inference. DigiSurface's team will assess your existing server infrastructure and recommend the optimal model size (7B, 13B, or 70B parameter) to balance speed and accuracy within your hardware constraints.
Your Data. Your AI.
Your Servers. Nowhere Else.
We'll deploy a free proof-of-concept on a sample of your data — HRMS, Real Estate, or Banking — and show you live results. For enterprises in India, UAE, Saudi Arabia & the entire Middle East.
Request Your Free POC
WhatsApp us