Your team spends hours every week looking for things they already have.
We build internal AI knowledge assistants over your existing document estate. Enterprise RAG implementation that handles Arabic, English, and the regulations in between.
Saqr Solutions is the AI implementation arm of Saqr Academy, the KHDA-approved applied AI institute in Dubai Media City.
The shift
In most mid-large GCC organisations, knowledge is everywhere and findable nowhere. SharePoint sites that nobody maintains. Policy PDFs in three different folders. Contract repositories no one has access to. CRM notes the wrong people can read and the right people cannot. Teams email each other to find things instead of searching the systems where the things actually live.
Multiple workplace studies put the time lost to searching for internal information at roughly two to three and a half hours per employee per day.
The exact number varies by organisation, but the pattern is consistent: scattered knowledge creates a real productivity tax. The teams that have fixed this are running internal AI assistants that pull from across the document estate and answer in plain language with sources cited.
What's missing for GCC buyers is a knowledge system designed for how regional organisations actually store and access information. Bilingual document estates. Mixed regional and global systems. Data residency requirements under PDPL. Permissions structures inherited from years of organic growth.
What we build
An internal AI knowledge assistant trained on your document estate, integrated with the systems your team uses, and governed for the regulatory regime you operate under.
Common patterns we deploy: a company-wide RAG layer over the document estate; a policy and HR assistant trained on your handbooks and procedures; a contract and legal-review assistant for in-house counsel and finance; a sales and account intelligence layer for client-facing teams.
The system answers in your team's language, cites its sources, and respects the access permissions of the underlying systems.
Where the knowledge lives
The system we build connects to wherever your team's knowledge actually sits:
- 01
SharePoint, OneDrive, Google Drive, Box, Dropbox Business.
- 02
Internal wikis on Notion, Confluence, or custom intranets.
- 03
CRMs (Salesforce, HubSpot, Microsoft Dynamics) for account intelligence.
- 04
HRMS systems (Workday, BambooHR, regional providers) for policy and people data.
- 05
Contract repositories (Ironclad, DocuSign, regional alternatives) for legal and finance.
- 06
ERP and operations systems where structured data complements the document estate.
The discovery phase confirms which sources matter most and the order to integrate them.
What's included
A discovery of your document estate, access systems, and the use cases your team would adopt fastest.
The full RAG and assistant stack set up inside your environment, with the right access controls and audit trails.
Integration with the systems of record listed above.
Governance posture aligned with PDPL and any sector-specific data regulations.
Training sessions for the teams that will use the system daily, plus a separate session for IT and the data owners, drawn from Saqr Academy's AI for Operations & Business program.
A documented playbook with the patterns your team can extend on their own.
How the engagement runs
- 01
Weeks 1 to 2
Discovery and design.
We map your document estate, identify the highest-value use cases, and design the system architecture around your access and governance requirements.
- 02
Weeks 3 to 7
Build and integrate.
Vector layer, retrieval pipeline, assistant interface, source citations, access controls, and audit trail. Tested against your real documents.
- 03
Weeks 7 to 10
Train and embed.
Pilot users work inside the system on real questions. We tune retrieval against the gaps that surface. By the end, the system is ready for broader rollout.
- Next
After launch.
The natural continuation is an ongoing Fractional Chief AI Officer arrangement, extending the system into new functions, holding AI strategy at the executive level, and governing the knowledge estate as it grows.
Who this is for
Mid-large GCC organisations of 500 to 10,000 employees with significant document estates and a clear use case the system should serve first. Professional services, banks, insurance, family-owned groups, government-adjacent organisations, large retail and hospitality.
You'll get the most value if you have a clear sponsor at COO, CIO, or CHRO level, and an IT team willing to give us the access we need to integrate properly.
What makes this different
- 01
We design for bilingual GCC content from the start.
Arabic, English, and the mixed-language documents in between.
- 02
The system is built around your governance regime, not retrofitted to it.
PDPL, DIFC Regulation 10, and ADGM requirements are mapped in week one, not bolted on at the end.
- 03
Training built on KHDA-approved curriculum.
The training inside the engagement runs on the same curriculum that powers Saqr Academy's corporate programs. Your team learns how RAG works, what good retrieval looks like, and how to add new document sources without our help.
Frequently asked questions
RAG stands for retrieval-augmented generation. In plain language, it's how an AI assistant can answer questions based on your company's actual documents, with sources cited, instead of making things up. Your team asks "what's our policy on remote working?" and the system pulls the answer from your HR handbook, citing the page. That's RAG. Most modern enterprise AI assistants are built on this pattern.
Microsoft 365 Copilot can be useful when the document estate is clean, permissions are reliable, and most of the work happens inside Microsoft 365. Glean and similar tools work well for organisations with mature document hygiene and predominantly single-language estates. Many GCC organisations have a more mixed reality: bilingual document estates, regional systems alongside global ones, inherited folder structures, and permissions that don't always reflect how teams work today. We're built for that messier implementation layer.
Yes. Arabic, English, and the mixed-language documents in between. The retrieval layer is configured for both languages, and the assistant answers in whatever language the user asks the question in. This matters for regional banks, family-owned groups, and government-adjacent businesses where document estates are genuinely bilingual.
Three layers. First, the retrieval pipeline only returns content from your actual documents, with sources cited on every answer. Second, the prompt architecture instructs the model to say "I don't know" when retrieval doesn't find a clear answer. Third, the system logs every question and answer for review, so your team can identify where retrieval is weak and improve it over time. Hallucination management is an ongoing discipline, not a one-time setup.
The system respects the access permissions of the underlying source systems. If a finance document is restricted to the finance team in SharePoint, the AI assistant will not surface that document to anyone outside the finance team. Access is enforced at the retrieval layer, not just the interface.
Yes. SharePoint, Google Drive, Box, Dropbox Business, Notion, Confluence, plus integration with HRMS systems (Workday, BambooHR, regional systems), CRMs (Salesforce, HubSpot), and contract repositories (Ironclad, DocuSign, regional alternatives). The discovery phase confirms which sources to integrate first.
Data residency, encryption, access controls, and audit logging are all mapped in week one and built into the architecture, not bolted on later. Data flows are decided during architecture. For regulated use cases, the system can be deployed inside your cloud or a regional environment with private inference where required. Where approved external AI providers are used, every data flow is documented, permissioned, and governed before launch.
Yes. The assistant interface can sit inside Microsoft Teams, Slack, your intranet, or as a standalone web application. Most clients deploy it where their team already works, which improves adoption significantly.
Tell us where your team is losing the most time.
Send us a short note. We'll read it, get back to you within two business days, and arrange a call to talk through it.