Capability
Generative AI
Custom AI assistants, document intelligence, content generation and enterprise copilots, grounded in your own data. Retrieval, evaluation and guardrails are built in from the start, so the output can be checked and trusted in daily work.
Tailored generative systems grounded in your data, built with retrieval, evaluation and guardrails so the output is trustworthy in production.
01Architecture
Reference architecture
A typical arrangement of the components. Every implementation is adapted to your systems, data-residency and security requirements.
Knowledge sources
- Documents and policies
- Databases and APIsREST · SQL
Retrieval
- Search indexpgvector · Qdrant
- Access control per user
Generation
- Language modelOpenAI · Anthropic
- Guardrails and validation
Channels
- Assistant interface
- Business applicationsAPI
02Components
What this capability covers
01
Domain-grounded RAG
Retrieval pipelines over your documents, databases and APIs, with citations and access control.
02
AI copilots
Internal assistants that support research, drafting and decision support for operational teams.
03
Structured generation
Reliable JSON and schema outputs, function calling and tool use, with validation gates.
04
Evaluation harnesses
Continuous test suites that track factuality, safety and regressions across model versions.
03Implementation
How we implement it
Model choice follows the requirements, not the other way round: data residency, language quality in Arabic and English, cost per request and latency are weighed per use case, including hosted and self-hosted options.
- Prompts, retrieval settings and model versions are configuration, reviewed and versioned like code.
- Every release is tested against an evaluation set for factuality, safety and regressions.
- Guardrails validate inputs and outputs, and sensitive actions require human confirmation.
04Deliverables
What you receive
Use-case specification and evaluation set
Retrieval and generation pipeline
Guardrail and access design
Evaluation report per release
Technology
Technologies we work with
- OpenAI
- Anthropic
- LangChain
- LlamaIndex
- pgvector
- Qdrant
- Redis
- FastAPI
Chosen per project and aligned with your existing standards. Listed as technologies we use, not as partnerships or endorsements.
05Use cases
Typical applications
Patterns this capability is designed for, not a list of delivered projects.
01
Internal knowledge copilot
Conversational access to policies, contracts and operational runbooks, with verified citations.
02
Customer onboarding agent
A multi-step assistant that collects, validates and personalises onboarding information.
03
Regulated document drafting
Templated, reviewable drafts for legal, finance and compliance teams.
06Related
Where to go next
Industry contexts
More in Intelligent Systems & Automation
- AI Systems Engineering
Computer vision, natural language, deep learning, multi-modal and predictive systems engineered for real-world deployment, not demonstrations.
- Enterprise AI Agents
AI agents that plan and complete multi-step tasks across your systems: gathering information, preparing work and taking actions through approved tools.
- Knowledge & RAG Systems
Enterprise knowledge systems that answer questions from your own policies, procedures and documents, with citations to the source.
- Document Intelligence
Arabic and English documents — forms, invoices, contracts, certificates and correspondence — turned into validated, structured data.
- Intelligent Automation
RPA, workflow automation, decision engines and intelligent document processing for operational efficiency.
- AI Customer Experience
Smart chat and voice assistants, conversation analytics and agent-assist tools for customer service.
Next step
Scope Generative AI for your organisation
Share your process, data and constraints. We will propose an approach, the evidence to collect first and a realistic plan.