🤖 Custom AI · Pro S;

AI Built on Your Data,
Deployed Inside Your Walls

We design and ship custom AI systems trained on your organization's specific knowledge — internal assistants, document intelligence, predictive models, and automation. Generic AI doesn't know your business. Ours does.

RAG Fine-tuning Local LLMs Vector DBs On-premise Arabic NLP Computer Vision
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Why Custom AI

Generic AI Doesn't Know Your Business

Public LLMs are powerful, but they're trained on the open internet — not on your contracts, policies, customers, or workflows. The gap shows up the moment your team asks a real question.

Generic ChatGPT / Copilot

Smart, but doesn't know you

Trained on public data. Doesn't know your suppliers, project history, internal codes, or compliance requirements. Hallucinates with confidence.

  • Generic answers — no business context
  • Your data sent to third parties
  • Cannot be deeply customized
  • Limited Arabic/RTL handling
  • Locked into vendor pricing
Pro S; Custom AI

Trained on your data, working for your team

Built around your documents, processes, and history. Understands your terminology. Cites real internal sources. Stays inside your infrastructure.

  • Grounded in your actual organizational knowledge
  • Data stays on your servers (on-premise option)
  • Tuned to your workflows and policies
  • Native Arabic + bilingual support
  • Open-source models — no vendor lock-in
Our AI Solutions

Six Ways We Put AI to Work for You

Each solution is custom-built for your organization. We don't sell off-the-shelf AI — we engineer systems that fit your data, your workflows, and your security requirements.

🧠

Custom AI on Your Data

RAG (Retrieval-Augmented Generation) systems and fine-tuned models that ground every answer in your organization's actual knowledge — manuals, contracts, historical decisions, internal wikis.

  • Document ingestion pipelines
  • Vector database (your servers)
  • Fine-tuned domain models
  • Source citation in every answer
  • Continuous knowledge updates
  • Permission-aware retrieval
💬

Internal AI Assistants

Private AI assistants for your teams — answering policy questions, summarizing meetings, drafting correspondence in your style, and surfacing institutional knowledge 24/7.

  • Department-specific assistants
  • Voice + text interfaces
  • Slack / Teams / Web integration
  • Conversation memory & context
  • Role-based access control
  • Usage analytics & insights
📄

Document Intelligence

Turn unstructured documents — PDFs, scans, emails, contracts — into queryable structured data. Extract entities, dates, amounts, clauses, signatures, and route them automatically.

  • OCR with Arabic + English support
  • Contract clause extraction
  • Invoice & receipt parsing
  • Form field recognition
  • Automatic categorization
  • Anomaly detection in documents
📈

Predictive Analytics

Forecasting and predictive models trained on your historical data — sales, demand, inventory, customer churn, employee attrition, project risks. See what's coming before it arrives.

  • Time-series forecasting
  • Customer churn prediction
  • Demand & inventory planning
  • Risk & anomaly scoring
  • What-if scenario simulation
  • Live dashboards with predictions
⚙️

AI-Powered Automation

Intelligent workflows that don't just follow rules — they understand context, classify ambiguous cases, and decide. Replaces the "if-then" rules that always break on edge cases.

  • Smart email triage & routing
  • Ticket classification & priority
  • Approval workflow assistance
  • Data validation & enrichment
  • Multi-step agent workflows
  • Human-in-the-loop checkpoints
👁️

Computer Vision

Visual AI tailored to your specific use case — quality inspection, security analytics, object detection, OCR. Pairs naturally with our Camera Planner platform for end-to-end deployments.

  • Quality / defect detection
  • Person / vehicle / object tracking
  • Security event recognition
  • Plate & document OCR
  • Custom-trained classifiers
  • Real-time camera integration
Industries We Serve

AI for the Sectors We Know

We've built systems for these sectors and understand their data, regulations, and operational realities — so the AI we ship fits the work, not the demo.

🤝

NGOs & Humanitarian

Beneficiary records, donor reporting, multilingual document processing, and program analytics.

Privacy-first
🏛️

Government

Correspondence intelligence, citizen services, compliance automation, and on-premise deployments.

On-premise
🏢

Commercial

Sales forecasting, customer support automation, document processing, and operational dashboards.

ROI-focused
🏗️

Engineering & Construction

Project document mining, drawings analysis, RFI assistance, and predictive scheduling.

Domain-tuned
How We Build AI

From Discovery to Production in Weeks

A pragmatic 5-stage process — heavy on understanding your problem first, light on bureaucracy. Most engagements deliver a working pilot in 8–12 weeks.

1

Discover

Understand the problem, the data, the users. Define success metrics.

1–2 weeks
2

Design

Choose architecture (RAG vs fine-tune), models, infrastructure. Data prep plan.

2–3 weeks
3

Build & Train

Engineer the pipelines, train models, set up evaluation harnesses.

4–8 weeks
4

Pilot

Deploy to a real team. Measure outcomes against baseline. Iterate fast.

2–4 weeks
5

Scale

Expand to more teams/use cases. Continuous learning + monitoring.

Ongoing
Our AI Tech Stack

Modern Open-Source Foundations

We favor open-source models and stacks so you own your AI — no vendor lock-in, no surprise pricing, full transparency over what's running on your data.

🧠 Models

Llama 3 Mistral Qwen DeepSeek Claude API GPT-4 Embedding models Whisper (STT) YOLO (vision)

🛠️ AI Frameworks

PyTorch Transformers LangChain LlamaIndex vLLM Ollama LoRA / QLoRA Unsloth

💾 Infrastructure

Qdrant Pinecone PostgreSQL + pgvector Docker Kubernetes FastAPI .NET Core Redis
Security & Privacy

Your Data Stays Yours

Enterprise AI demands enterprise security. Every Pro S; AI engagement starts with a privacy and deployment plan tailored to your compliance needs.

🏢

On-Premise Deployment

Run entirely inside your infrastructure using local open-source models. Your sensitive data never leaves your network.

🔐

Encryption End-to-End

Data encrypted in transit (TLS) and at rest. Vector embeddings encrypted. Access controls auditable.

👥

Role-Based Access

Permission-aware retrieval — the AI only surfaces information the asking user is allowed to see.

📜

Source Citations

Every AI answer cites the source documents — no hallucinations passing as fact, full transparency for auditors.

🔍

Audit Logs

Every prompt and response logged. Track usage patterns, detect misuse, prove compliance to regulators.

🚫

No Training on Your Data

When using cloud APIs, we configure them to never train on your prompts. Your IP stays your IP.

Common Questions

Answers Before You Even Ask

How is custom AI different from just using ChatGPT?
Generic LLMs don't know your business. We train AI on your specific documents, processes, and history — so it understands your terminology, follows your policies, and produces outputs grounded in your actual data. Plus, your data stays under your control.
Does my data leave our infrastructure?
You choose. We support fully on-premise deployments using local open-source models (Llama, Mistral, Qwen) or hybrid setups where only non-sensitive operations use cloud APIs. For organizations with strict compliance requirements (government, finance, healthcare), we build entirely air-gapped systems.
What does an AI engagement typically look like?
Discovery (1–2 weeks) → Design & data prep (2–3 weeks) → Build & train (4–8 weeks) → Pilot deployment (2–4 weeks) → Iterate & scale (ongoing). Most engagements deliver a working pilot in 8–12 weeks. We prefer iterative delivery over big-bang launches.
What if our data is messy, incomplete, or in Arabic?
Both are common. We handle data cleaning and structuring as part of the engagement, and our systems support Arabic NLP, RTL documents, mixed Arabic/English content, and bilingual workflows natively. Data quality work is often where 50% of AI value comes from.
How do you measure if AI is actually working?
We define success metrics in the discovery phase — accuracy targets, time saved per task, error reduction, user adoption rates. Every model we ship has an evaluation harness and dashboards so you see real impact, not vibes. If something doesn't move the metric, we change it.
What does it cost?
Engagements vary by scope — a focused internal assistant might be in the low five figures, while a full document intelligence platform with predictive analytics is more substantial. We offer fixed-price pilots so you can validate ROI before committing to a full build. Reach out for a tailored estimate.

Let's Build AI That Actually Knows Your Business

Tell us about your problem in a 30-minute discovery call. We'll come back with a concrete AI architecture, a phased plan, and a fixed-price pilot proposal — no marketing fluff.

📅 Book a Discovery Call → 📧 Email Us Directly