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RED WINGSS TECHVERSE

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RED WINGSSTechverse

Capabilities

Intelligent Capabilities for Enterprise Transformation

From applied AI to secure infrastructure and custom software engineering, our capabilities support product delivery and digital modernisation.

01

AI & Machine Learning

AI and machine learning capability focused on designing, training and deploying models that support classification, prediction, recommendation and natural language understanding within business workflows.

Business challenges addressed

  • · Unclear use cases and misaligned expectations for AI adoption
  • · Fragmented or insufficient data for model training and validation
  • · Difficulty integrating AI outputs into existing operational systems
  • · Concerns around model accuracy, bias and governance

Solution approach

  • · Start with well-defined business problems and measurable success criteria
  • · Assess data readiness, quality and access requirements early
  • · Build modular AI services designed for integration via APIs
  • · Implement monitoring, feedback loops and human oversight for production models

Typical deliverables

  • · Use case assessment and feasibility analysis
  • · Data pipeline design and model development
  • · API-ready AI services and inference endpoints
  • · Model documentation, evaluation reports and governance guidelines

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02

ERP Solutions

ERP capability focused on modular enterprise platforms that connect core business functions — from shop-floor operations to financial administration — into a cohesive system with role-based access and reporting.

Business challenges addressed

  • · Disconnected systems for production, inventory and finance
  • · Manual data entry and reconciliation across departments
  • · Limited real-time visibility into operational performance
  • · Difficulty adapting legacy processes to digital workflows

Solution approach

  • · Map existing processes and identify priority modules for phased deployment
  • · Configure workflows aligned to organizational structure and roles
  • · Integrate with existing tools through APIs and data connectors
  • · Provide training support and iterative optimization after go-live

Typical deliverables

  • · Process mapping and module configuration
  • · ERP deployment with role-based access setup
  • · Integration with accounting, IoT and third-party systems
  • · Dashboard, report and workflow customization

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03

Cybersecurity

Cybersecurity capability encompassing threat detection, identity governance, security monitoring and incident response workflows designed to reduce risk and support compliance-oriented operations.

Business challenges addressed

  • · Expanding attack surfaces across cloud and on-premises systems
  • · Inconsistent access control and privilege management
  • · Alert fatigue from fragmented security tools
  • · Limited visibility into security events and audit trails

Solution approach

  • · Conduct security assessments to establish baseline visibility
  • · Implement layered controls across identity, network and application tiers
  • · Centralize logging and alert management for operational clarity
  • · Define incident response playbooks and escalation procedures

Typical deliverables

  • · Security assessment and risk mapping
  • · VISECURE platform deployment and configuration
  • · Access control policy design and implementation
  • · Monitoring dashboards, audit logs and incident response workflows

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04

Networking & IT Infrastructure

Networking and IT capability focused on designing, deploying and maintaining the infrastructure layer — including networks, servers, endpoints and connectivity — that underpins business applications and digital services.

Business challenges addressed

  • · Unreliable connectivity affecting business continuity
  • · Complex network topologies difficult to monitor and maintain
  • · Endpoint and device management across multiple locations
  • · Infrastructure scaling lagging behind business growth

Solution approach

  • · Assess current infrastructure and identify reliability gaps
  • · Design network architecture with redundancy and segmentation
  • · Implement monitoring and remote management tools
  • · Plan capacity and upgrade paths aligned to business requirements

Typical deliverables

  • · Network topology design and documentation
  • · Infrastructure deployment and configuration
  • · Monitoring and alerting setup for network and systems health
  • · Maintenance plans and support procedures

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05

IoT & Connected Systems

IoT capability focused on device connectivity, telemetry collection, edge processing and integration with enterprise platforms for manufacturing, retail, logistics and smart infrastructure use cases.

Business challenges addressed

  • · Siloed device data with no central visibility
  • · Connectivity reliability in industrial and field environments
  • · Security risks from unmanaged connected devices
  • · Difficulty translating sensor data into actionable insights

Solution approach

  • · Identify devices, protocols and data requirements for each use case
  • · Design edge and gateway architecture for reliable data collection
  • · Integrate telemetry with ERP, analytics and alerting platforms
  • · Implement device security, firmware management and monitoring

Typical deliverables

  • · IoT architecture design and device integration plan
  • · Gateway deployment and telemetry pipeline setup
  • · Dashboard and alert configuration for operational data
  • · Device management and security policy documentation

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06

Cloud Engineering

Cloud capability encompassing infrastructure design, containerization, CI/CD pipelines and cloud-native service integration designed to support production-grade application deployment and operations.

Business challenges addressed

  • · On-premises infrastructure limiting scalability and flexibility
  • · Inconsistent deployment processes across environments
  • · Cloud cost management without proper architecture planning
  • · Security and compliance requirements in cloud migrations

Solution approach

  • · Evaluate workload requirements and cloud readiness
  • · Design infrastructure with scalability, redundancy and observability
  • · Implement automated deployment pipelines and environment management
  • · Apply security controls and cost monitoring from the start

Typical deliverables

  • · Cloud architecture design and migration planning
  • · Infrastructure-as-code templates and environment setup
  • · CI/CD pipeline configuration and deployment automation
  • · Monitoring, logging and cost management dashboards

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07

AI Automation

AI automation capability focused on combining conversational AI, rule engines and API integrations to automate repetitive tasks, route requests and support decision-making within enterprise operations.

Business challenges addressed

  • · High volume of repetitive manual tasks across departments
  • · Slow request routing and approval cycles
  • · Knowledge trapped in documents and unstructured formats
  • · Difficulty scaling support without proportional headcount growth

Solution approach

  • · Identify high-frequency workflows suitable for automation
  • · Connect AI assistants to approved knowledge sources and business systems
  • · Design automation triggers with human escalation paths
  • · Measure adoption, accuracy and time savings iteratively

Typical deliverables

  • · Workflow automation assessment and use case prioritization
  • · AI assistant configuration and system integration
  • · Automation rule design and approval flow setup
  • · Usage analytics and continuous improvement reports

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08

SaaS Product Engineering

SaaS capability focused on designing and building cloud-hosted products with tenant isolation, subscription management, API access and operational tooling required for product-led growth.

Business challenges addressed

  • · Building products that scale from early adopters to broad user bases
  • · Multi-tenant architecture with data isolation and performance requirements
  • · Subscription billing, onboarding and customer lifecycle management
  • · Maintaining uptime, security and feature velocity simultaneously

Solution approach

  • · Define product architecture with multi-tenancy and API-first design
  • · Implement core platform services including auth, billing and monitoring
  • · Build modular feature sets designed for incremental release
  • · Establish DevOps practices for reliable deployment and incident response

Typical deliverables

  • · SaaS architecture design and technical roadmap
  • · Multi-tenant application development and API layer
  • · Subscription and user management module implementation
  • · Deployment infrastructure and operational runbooks

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09

Custom Software Development

Custom software capability focused on building tailored web, mobile and backend applications that address unique business processes not fully covered by off-the-shelf products.

Business challenges addressed

  • · Off-the-shelf tools that do not fit specialized workflows
  • · Legacy systems lacking modern interfaces and integration options
  • · Need for rapid prototyping before full product investment
  • · Maintaining custom software alongside evolving business requirements

Solution approach

  • · Conduct discovery sessions to define requirements and constraints
  • · Design modular architecture that supports future extension
  • · Deliver iteratively with regular review and feedback cycles
  • · Provide documentation and handover for long-term maintainability

Typical deliverables

  • · Requirements specification and technical design documents
  • · Custom web, mobile or backend application development
  • · Integration with existing ERP, security and analytics systems
  • · Testing, deployment and maintenance documentation

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10

Research & Development

R&D capability focused on exploring enterprise AI, computer vision, secure systems, edge intelligence and data analytics through structured research programs, proof-of-concept builds and technology validation.

Business challenges addressed

  • · Rapid technology change outpacing internal experimentation capacity
  • · Uncertainty about feasibility and ROI of emerging solutions
  • · Difficulty bridging research prototypes and production-ready products
  • · Need for ethical and secure approaches to experimental AI systems

Solution approach

  • · Define research themes aligned to product roadmap and market needs
  • · Build focused prototypes to validate technical and business assumptions
  • · Document findings, limitations and production readiness assessments
  • · Transfer validated concepts into product engineering pipelines

Typical deliverables

  • · Research briefs and feasibility studies
  • · Proof-of-concept prototypes and evaluation reports
  • · Technical papers and internal knowledge documentation
  • · Productization roadmaps for validated research outcomes

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