For Learners
Build an Applied AI Portfolio
- Mentored diploma cohorts
- Architecture and code reviews
- Deployment-focused capstones
- Mock interviews and readiness support
- Clear technical progression by track
Automation Systems ยท Applied AI Training
Automation & Knowledge Systems for Real Operations.
Deploy automation and knowledge systems for operations, or build a production-ready AI portfolio through premium applied diploma tracks.
Workflow automation
Internal assistants
Knowledge operations
Bilingual delivery
Egypt & MENA
For Companies
Deploy Operational AI Systems
- Workflow automation and lead routing
- Internal assistants and support copilots
- RAG and knowledge systems
- Implementation roadmap and rollout support
- Team enablement and adoption guidance
Automation & Knowledge Systems
We design and deploy operational AI systems around customer service, analytics, ERP guidance, and CRM workflows so teams can run faster with controlled implementation.
Customer Service Automation & Action Agents
Problem: Customer email queues slow down when teams must manually classify intent and route every request.
System: AI email workflows detect request type, draft accurate replies, and trigger connected system agents when action is required.
Outcome: Supervised rollout first, then stable automation coverage with human control for edge cases.
Discuss a Use CaseNatural-Language Analytics for Oracle / SQL Data
Problem: Non-technical teams and leadership depend on analysts for basic reporting questions.
System: Plain-language analytics copilots generate Oracle / SQL queries against live company data and return usable answers and dashboards.
Outcome: Decision-makers access live business insight directly without waiting for manual query cycles.
Discuss a Use CaseERP Workflow Support Copilot
Problem: ERP users rely on manual support and tribal knowledge to execute routine operational tasks.
System: An ERP guidance assistant provides step-by-step workflow support aligned to real tasks inside the ERP environment.
Outcome: Support load is reduced while users complete ERP workflows with clearer execution guidance.
Discuss a Use CaseCRM & Lead Automation Systems
Problem: Lead capture, qualification, and routing often break across forms, inboxes, and CRM stages.
System: Automated pipelines handle lead intake, qualification logic, assignment, and CRM state movement.
Outcome: Sales and operations teams run a consistent lead flow instead of fragmented manual handoffs.
Discuss a Use CaseProof Built Around Delivery
Signals that matter to operational teams: scoped pilots, cited knowledge outputs, live implementation review, and deployment-first learning outcomes.
Pilot-first implementation
Cited knowledge responses
Live mentor review model
Deployment-oriented capstones
Bilingual technical delivery
Egypt & MENA execution
Deployment-First
Every diploma requires a demonstrable system, not only theory completion.
Live Mentoring
Architecture and implementation reviews are delivered in live sessions.
Pilot-Oriented
Company engagements start with scoped operational pilots before scaling.
Bilingual Delivery
Technical delivery and support for Egypt and MENA teams in Arabic and English.
Operational Systems We've Built
Delivery proof across two lanes: business systems already operating in companies, and academy systems deployed as applied learning products.
AI Customer Service Automation & Action Agents
Problem: Support teams were overloaded by repetitive email triage and delayed responses.
System: AI intent detection with automated replies plus connected action agents for requests that require in-system execution.
Outcome: Routine requests are handled automatically while complex cases stay in controlled human review.
Deployment status: Already working in companies, launched with supervised rollout before wider automation trust.
Deployment: Operating in companies
Natural-Language Analytics Copilot for Oracle / SQL
Problem: Business questions depended on manual SQL support and slowed decision cycles.
System: Natural-language interface that generates Oracle / SQL queries and returns answers from live company databases.
Outcome: Non-technical staff and leadership can query live data directly and access dashboard-ready responses.
Deployment status: Already working in companies as a decision-support analytics layer.
Deployment: Operating in companies
ERP Workflow Support Copilot
Problem: Users needed repeated manual support to complete frequent ERP workflows correctly.
System: ERP support assistant that provides guided, step-by-step operational help mapped to real tasks.
Outcome: Teams execute workflows faster with fewer escalations to manual support channels.
Deployment status: Already working in companies as an ERP guidance layer.
Deployment: Operating in companies
CRM & Lead Automation System
Problem: Lead qualification and routing workflows were inconsistent across channels and ownership teams.
System: Workflow automations for lead capture, qualification logic, routing rules, and CRM stage transitions.
Outcome: Operational lead flow became standardized with fewer manual handoffs and clearer accountability.
Deployment status: Delivered as a live business automation capability.
Deployment: Operating in companies
Student Buddy: Lecture-Grounded Learning Copilot
Problem: Students needed one reliable system for revision, questioning, and exam readiness based only on approved course material.
System: Deployed RAG platform that ingests lectures, answers only from lecture content, and combines summarization, question generation, and exam analysis.
Outcome: Learners use one grounded academic intelligence workspace instead of fragmented study tools.
Deployment status: Deployed as a production-minded student system.
Deployment: Deployed academy product
Advanced Student Document Intelligence Assistant
Problem: Students struggled to interrogate dense domain materials with reliable grounding and structured understanding.
System: Document intelligence assistant built on retrieval, citation control, and guided learning prompts across selected academic sources.
Outcome: Learners can explore domain documents with clearer context, grounded answers, and structured follow-up paths.
Deployment status: Applied academy system used for production-minded learning workflows.
Deployment: Academy applied system
Academy Diploma Tracks
The academy side of Elevorix includes three premium applied pathways. Computer vision is offered as a specialized learning track only.
AI Automation Practitioner Diploma
Who it is for: Operators and career starters building business automation foundations.
- What you build: Practical no-code and API-integrated workflow systems.
- Time commitment: 11 weeks with live delivery.
- Support model: Mentor feedback and logic review.
- Portfolio outcome: Deployable automation capstone.
- Admission requirement: No coding prerequisite.
AI Systems Engineering Diploma
Who it is for: Engineers targeting production NLP, RAG, and agent systems.
- What you build: Retrieval systems, agents, and production API deployments.
- Time commitment: 24 weeks with advanced-entry option.
- Support model: Live architecture and debugging reviews.
- Portfolio outcome: Defensible deployed AI system.
- Admission requirement: Python readiness expected.
Computer Vision Systems Engineering Diploma
Who it is for: Learners specializing in visual AI pipelines as an academy track.
- What you build: Detection, segmentation, and inference workflows for portfolio projects.
- Time commitment: 22 weeks with advanced-entry option.
- Support model: Model review and deployment coaching.
- Portfolio outcome: Specialized CV capstone demo.
- Admission requirement: Python and ML fundamentals.
Frequently Asked Questions
Do you support both companies and learners?
Yes. Elevorix has two clear lanes: operational AI systems for companies, and applied AI diploma tracks for learners.
Do you provide computer vision services for companies?
No. Computer vision is part of our academy specialization track, not part of our company services.
How do we start a company engagement?
Book a strategy call to map workflow bottlenecks, knowledge constraints, and pilot scope before implementation.