Define, implement and integrate a scalable, secure and highly scalable WebRTC-based communication platform into the existing Messaging platform.

• Defining a generic, universal system platform for XR (AR, VR) use cases as part of the European IPCEI initiative. Evaluation of available options for SSR (Server-Side Rendering) Backend, (WebRTC)-Streaming and Client implementations. Working on PoC implementations and technical evaluation of potential components. Leading the dev team. Working on the target system architecture for complete end-to-end solution.
• Designing and Integrating GenAI PoCs (LLM, time series, Prediction, Object Detection, Image Segmentation, Interactive Agents). Researching topics like NeRFs, Gaussian Splatting for XR content creation and SAM and other techniques for image segmentation for example. 
• Analyzing ways to measure and reduce system latencies. Working on GPU scheduling, CUDA and related topics. Defining and implementing Backoffice- and End User-related Dashboards with Grafana, Superset. Using Jaeger tracing to analyze specific events. Defining a GenAI-based automatic alerting feature for specific Events and related Event-Clusters and KPIs values. Integrating AR/VR/XR IoT devices
• Working with the Business Development, various other stakeholders and UX team to define and implement a well-designed scope for the complete solution with the goal to customer journey starting from the service portal web site to the integration steps of XR/VR/AR solutions. This is a parallel ?design thinking? track, which runs in parallel to the technical track to save time.
• Implementing the complete scalable Backend system (8 microservices) mostly in Golang, two services in Java (Quarkus framework). Using NATS as asynchronous intra-service connect. Supporting the dev team ? besides other topics - in the Unreal, Unity, Linux, GPU realm

Multimodal image-editing inference pipeline (Qwen Image Edit 2511) on NVIDIA DGX Spark

• Ported and stabilized a Diffusers-based image editing workflow (Qwen/Qwen-Image-Edit-2511) on an NVIDIA DGX Spark / GB10 (CUDA capability 12.1 / sm_121) host, with a Mac-based JupyterLab client and a remote Ubuntu kernel execution environment.
• Resolved GPU toolchain incompatibilities by implementing an isolated Python environment and deploying PyTorch nightly (cu130) to support sm_121, addressing NVRTC --gpu-architecture failures and CUDA capability range mismatches.
• Identified and mitigated silent numerical failure modes (all-NaN outputs leading to black images) by systematically validating attention backends and precision; established a stable baseline using bf16 + SDPA and documented that fp16 reintroduces NaNs on the target stack.
• Re-architected the notebook into a production-grade, reusable workflow: one-time model initialization plus a parameterized run_edit() function enabling rapid image/prompt iteration without reloading model weights, reducing OOM risk and iteration latency.
• Implemented operational guardrails for reliability in constrained server environments: Host RAM availability checks via /proc/meminfo (MemAvailable), GPU VRAM monitoring via torch.cuda memory statistics (avoiding NVML dependency issues)
• A ?memory gateway? executed after image load/preprocessing to proactively prevent OOM kills and Jupyter server disconnects.
• Integrated optional LoRA adapter capability for controllable style steering (e.g., resilt aesthetic), including guidance on where/when to load LoRA (post pipeline init and encoder 
• configuration) and operational considerations (VRAM impact, stability regression testing, PEFT dependency).
• Produced technical documentation capturing failure analysis, parameter ladders (resolution/steps/CFG), best-practice defaults, and reproducible troubleshooting steps for remote GPU inference workflows.

• Implemented a full-stack desktop application for documentation collection management. The system implements a multi-stage NLP pipeline: metadata extraction from PDF/EPUB files, LLM-powered semantic enrichment running on a local Nvidia DGX Spark system for privacy reasons, and vector similarity search using transformer-based embeddings. LM Studio as the local inference server, configuring optimized models for different tasks? using Qwen 2.5 for structured metadata extraction and categorization, BGE-Large and Nomic-Embed for high-dimensional vector embeddings.
• RAG architecture with content chunking and hybrid search combining semantic vector similarity (pgvector) with traditional keyword matching. The enrichment pipeline generates AI-driven docs categorization, difficulty assessment, topic tagging, and natural language descriptions with confidence scoring.
• Backend implements repository pattern and parallel processing architecture for batch inference across 6000+ documents. Developed a cross-platform native GUI using Vue 3, TypeScript, and the Wails framework (Go), providing real-time semantic search, collection analytics, and library browsing.
• The local-first architecture ensures complete data privacy while delivering production-grade ML capabilities without cloud dependencies.

• Implementing the second release of the strategic mobile app for a healthcare solution. The app shall enable customers to customize the (complex) behavior of a dedicated hardware system as easy as possible. The solution is based on current Angular 19 and Ionic 8 to be able to use the latest Angular features in specific.
• The UX/UI is designed/optimized especially for the specific needs of the customer base in the healthcare realm. The resulting app is the first part of a broader product portfolio with the goal to provide a consistent UX across the complete line (interior design, web site, apps, special hardware).
• The app connects with a custom embedded system using REST API. The related server has been implemented by me prior to this UI/UX project.

• Leading the development and successful deployment initially of a Proof of Concept (PoC), followed by the launch of the final production-ready IoT solution. The product is consisting of the backend business logic, which is running on an embedded device. The second part is the mobile frontend based on Ionic (Android, iOS), targeting a market entry in Q1, 2025.
• Defined and implemented a mobile application for iOS and Android using Ionic and Angular, integrating the mobile client with the embedded Golang server. Implementing specific system services for IR, BLE (custom communication between embedded devices and the backend) and 433 MHz subsystems. Implementing the backend with IoT and edge computing capabilities for real-time data processing. Starting to analyze different user behavior to provide even better user experience.
• Implemented the automatic generation of credentials (serial number, WLAN details, ansible related details etc.) product generation flow based on n8n and PocketBase. Implemented the automatic image and configuration system for an Ubuntu target based on custom PocketBase (Golang) business logic and Ansible for system setup and configuration.
• Implemented a diverse range of sensor and radar technologies to enhance device interactivity and data accuracy to improve healthcare monitoring and diagnostics use cases.
• Defined three LLM-based use cases and implemented the initial FTI pipeline based on initial MLOps scenarios and current tooling. The first use case uses the customer and internal documentation and uses a local model, Ollama, RAG, a vector database and a dedicated UI to allow users to chat with the AI Agent. Various fine-tuning sessions (LoRa) were part of this task. The second use case will analyze log data to improve the products. The third use case is based on radar technology to analyze user/patient health state etc. with a visual transformer model.
• Planning closely with the startup team to ensure a seamless handover of the current solution, including detailed documentation and user guides created with Figma and wireframing tools.
• Setting up team/company related tools (mailcow, n8n, nextcloud

• Defining and implementing an efficient, scalable backend microservices infrastructure for an AR/VR solution. Enable AR/VR clients to connect to the backend infrastructure including 3rd party APIs. Analyzing/driving requirements and implementing the respective backend features. Preparing the setup for a planned Kubernetes-based deployment.
• Integrating a complex WebRTC microservice to provide real-time audio, video and data connectivity for a significant number of users. Connecting Unity clients with the WebRTC system. Defining and implementing additional microservices to manage users, VR related content, system notifications. Implementing various data translation/marshalling logic. Setting up a complete observability platform managing logs, traces and KPIs/metrics including Dashboards and Event Monitoring.
• Exploring options for a variety of use cases including the usage of AI Agents, LLM models and NLP solutions. Pushing things forward with the small and young team and providing know-how transfer. Analyzing and proposing needed security topics as a preparation steps for the planned integration into LH system environments.

• Lead the design and development of an industrial real-time video analysis infrastructure for a Gigafactory/Battery project with the main target advanced and flexible manufacturing video analytics.
• Pushed the implementation of Proof of Concepts (PoCs) for core software components, serving as foundational blueprints for the development team and ensuring alignment with project specifications. Implementing many PoCs/Modules as "hands-on" Architect myself and then handed over to the team.
• Directed a global remote development team, driving collaboration and knowledge sharing across borders to drive the project towards success.
• Engaged with a wide array of internal stakeholders to gather requirements, refine project objectives, and develop a comprehensive system architecture that addressed key business needs.
• Produced extensive documentation, including system designs, Jira epics, and task outlines, facilitating clear communication and efficient workflow within the development team. Led the deployment phases with a focus on end-to-end (E2E) testing, ensuring the system?s reliability and performance met high standards.
• "Hands-On" developed and demonstrated versatile use case implementations in Golang and Java (Quarkus), focusing on monitoring, data storage (S3, MinIO, SeaweedFS), and event streaming (Kafka) to guide the team?s development efforts.
• Conducted in-depth analysis of cutting-edge machine learning technologies, including convolutional neural networks (CNNs), visual transformers, and localized natural language processing (LLMs), to explore potential enhancements for the video analysis capabilities.
• Defining and implementing the "Observability" platform to manage logs, traces and KPIs/metrics including Dashboards and Event Monitoring.
• Defining the security-related environment based on ISO 27001 and customer-specific rules and setups. Preparing and documenting two Audits runs.

• Worked with a Language Model (LLM) infrastructure, initially created in 2023, transitioning from proprietary OpenAI APIs to a variety of open-source LLM frameworks with the goal to interpret and analyze a large number of scanned and PDF documents for a specific domain.
• Defining the architecture, implemented and integrated some document reader modules and autonomous agents, leveraging the capabilities of the LangChain framework to enhance functionality.
• Implemented and refined relevance and generative adversarial network (RAG) schemes, improving the system's interpretative and responsive capabilities.
• Conducted a assessment of multiple vector databases, identifying optimal solutions for efficient data indexing and retrieval to support sophisticated language models.

• Led the development of a language model (LLM)-based document analysis platform for a pioneering US startup, enhancing the capability to process and understand large volumes of textual data.
• Configured and deployed LLM solutions, utilizing OpenAI's models to create a robust framework for document parsing, analysis, and interpretation.
• Collaborated closely with data scientists to integrate advanced LLM functionalities, including OpenAI's ChatGPT and bespoke open-source models, to tailor the system to the unique analytical needs of the startup.
• Used Langchain to construct dedicated agents, providing seamless interaction and retrieval of information across the platform.
• Investigated and evaluated a suite of vector databases, mainly Weaviate, for optimal data storage and quick querying, significantly improving the initial solution's performance

• Improved Momenta's autonomous vehicle infrastructure, enhancing the system's robustness and introducing advanced features for improved vehicular autonomy.
• Engineered and deployed new functionalities, augmenting the autonomous driving solution's operational capabilities.
• Worked on a detailed assessment of big data architectures, emphasizing scalable and low-latency data pathways to bolster real-time processing and decision-making for autonomous vehicles.
• Explored potential machine learning pipelines for integration into the existing system architecture, facilitating intelligent, data-driven decision-making for vehicle navigation and safety systems.
• Using tools like Jira, Confluence, and Bitbucket for streamlined project tracking, collaboration, and source code management
• Configured and utilized Grafana/Superset and Prometheus for monitoring and observability, ensuring high system performance and quick troubleshooting of the infrastructure.

• Defined and implemented the end-to-end architecture for real-time video and data streaming. The solution was optimized for an autonomous robotic system in the consumer market, enabling advanced automation in smart home environments.
• Helping to integrate the resulting solution within BSH's existing HomeConnect cloud ecosystem, leveraging the platform to extend the system's capabilities.
• Implemented multiple Proof of Concepts (PoCs), each targeting distinct real-time video and data streaming scenarios, setting the stage for a flexible, multi-use architecture. Working on the full-stack development of a WebRTC-based communication layer, enabling real-time interaction between the robotic system and the end-user interface.
• Defined the scope and architecture for and implemented a TypeScript-based WebRTC client for automatic system testing, alongside a Golang/gstreamer powered edge device client for streamlined operations. Added a real-time remote control data channel, coupled with a highly flexible command and control structure, ensuring precise and safe manipulation of the robotic unit.
• Defined and applied a comprehensive suite of metrics and key performance indicators (KPIs), providing a framework for continuous system evaluation and improvement. Developed a suite of flexible diagnostic tools aimed at analyzing video quality, ensuring the highest standards were met for user experience.
• Delivered a strategic approach to incorporating potential machine learning techniques, defining requirements to advance the system's decision-making and predictive capabilities. Leading the development team based in India, managing project deliverables, timelines, and ensuring the adherence to quality and technical standards.

• Developing and implementing the end-to-end real-time video and data streaming architecture and infrastructure for an autonomous robot. Integrating the initial solution into the HomeConnect cloud system. 
• Several PoCs for different levels of real-time video and data channel use cases. Implementing the complete WebRTC-based backend and client infrastructure.
• Implementing a browser based WebRTC client for testing. Implementing an edge device WebRTC client. Implementing a real-time remote control data channel system.

• Worked on proposals and creating Proof of Concepts (PoCs) for a comprehensive system monitoring and alerting mechanism for SmartMeter Gateway (SmGW) applications. Served as the main technical point of contact for multiple development teams, guiding system analysis, outlining future steps, and transitioning systems to updated technologies.
• Analyzed the processing and management of IoT-related data, including measurements and events, to enhance data handling efficiencies within the electrical grid marketplace.
• Evaluated standard data flow scenarios within the electrical grid to optimize the performance and reliability of SmGW use cases. Implemented a complete Monitoring/Observability solution including connecting data feeds, Elasticsearch databases, followed by data normalisation and local database support for better Dashboard performance.

• Kafka
• Docker
• Kubernetes
• MQTT
• Spring Boot
• Quarkus
• Prometheus
• Grafana
• Azure
• InfluxDB
• IEC 101/104
• NestJS
• Test Tools

• The main work for this project ended in December 2014 and will proceed as a small “side project” (weekends) for on-going adaptations of new services.
• Defining the complete technical infrastructure for an international portal in the music marketing business (digital and physical distribution). Responsible for the complete IT infrastructure including site look&feel, security, cloud computing, ecommerce etc.
• Interfaces to music labels and stores using RESTful interfaces, JSON, open APIs, XML. Automating the ecommerce area. Handling large amounts of content including cloud storage and backup. Microsite builder, Communities, Mashups, Data Mining.
• Legal setup, tax optimization, investor documentation and meetings.
• Complete project management for an international team of developers and designers. Defining the JS libraries and extensions. Defining HTML5 Canvas solutions. Doing mobile apps (Android)

Key Technologies:

Grails, Groovy, XML, JSON, REST, Java, Spring, Hibernate, MySQL, Linux, Tomcat, JavaScript, GWT, jQuery, JQuery Plugins and –UI, CSS, HTML5, Touch Interfaces, mobile and online payment systems, mass data cloud computing, data security, vendor API programming, Wordpress API, Android, iOS, Tablet Systems, Media Converters, Music Fingerprinting, Apache POI, WAV, FLAC, MP3, pub, micro formats, Red Book, etc.

Evaluation of Cloud services (Amazon, Google, Akamei, Edgecast, Contendo, Limewire, HP etc.), implementation of a custom media distribution infrastructure for fast and secure media transcoding (FLAC, WAV, MP3, encryption) and distribution based on a universal cloud storage layer.  Open Source Cloud Storage Solutions. Legal aspects of media distribution. Intellij Idea/Android Studio/WebStorm.

This project is working fine  – I am CTO of this running entity without a significant workload.

Note: I will be working on an Update November 2016.

Defining the migration process and all needed components for an existing “in train” portal to current technologies (frontend, backend). Implementing the migration tools, setting up the new system. Implementing the new portal based on the defined structure and Angular 6 from scratch against the rules of Atomic Design.

Defining UE atoms, molecules,organisms.

Analyzing the current trends and technologies in the Home Appliance and SmartHome markets. Market analysis around IoT and SmartHome Connectivity with the goal to define concepts for the BSH internal innovation network. Connecting projects inside of BSH and Bosch to improve communication and technology exchange.

Defining and implementing PoC solutions for machine learning, deep learning and natural language processing (NLP). Working with BOSCH Corporate Research (Renningen, Sunnyvale USA).

Defining potential content formats for internal, community driven content. Defining a potential CMS for a connected device environment. Analysing add-ons like NLP (Natural Language processing), gestures and other topics.

Demonstrating and architecting browser based App technologies and new UX approaches for embedded solutions based on Angular and Qt 5. Defining upcoming use cases. Abstracting natural language IO and implementing related machine learning use cases. Defining complex CMS structures and a round trip ecosystem.

Implementing a client/server system to develop and run Chatbot use cases.

Defining and implementing PoCs for various technical machine learning topics. Workshops. PoCs. Connecting People. System Architectures

Analysing the current state of all platforms - developing roadmaps and requirements for the future of connected devices. Developing Proof-of-Concept solutions (PoC). System Design and –Architectures for connected devices. Integration into SmartHome environments, Embedded Linux environments, Browser based Apps, Use Cases, Natural Language IO, Workshops. Connecting People.

Key Technologies:

Embedded Linux, IoT, Build systems, Market Research, Zephyr, Node.red, Node.js, Brillo, HomeConnect, AllSeen(AllJoyn, OpenHab, Iotivity, HomeKit, Android, iOS, Google Assistant, Google Home, NLP Technologies, Bot Technologies, Connected Devices, Cloud Environments, Security, Arduino, Raspberry Pi, IFTTT, SmartThings, KNX, HomeKit, AllSeen AllJoyn, OCF, IoTivity, Lora, Yocto, RiOT, FreeRTOS, OSTRO, Linaro, Soletta, Hybrid Apps, Embedded Chromium, UX/UE.

As Co-Founder and CTO played a pivotal role in outlining the scope, defining use cases, and architecting the foundational structure for a startup specializing in location and context-based services for targeted mobile advertising. Directed the development of client-side and all server-side components, including a dynamic dashboard for real-time data monitoring and management.

Deployed in-house location-based and sensor services optimized for energy efficiency, ensuring robust performance for mobile applications. Established a robust big data analysis system designed to manage key performance indicators (KPIs) and intelligent ad targeting scenarios, enhancing the effectiveness of marketing efforts.

Created and launched a custom, scalable, cloud-based push notification service as a major enabler alongside a comprehensive big data analytics infrastructure, to allow for timely and relevant user engagement. Developed the database architecture for both client and server environments, ensuring data integrity and seamless flow between systems.
Implemented the Android Software Development Kit (SDK) and developed Android applications, complemented by an AngularJS-based dashboard and a Grails-based RESTful API, providing a full-stack solution.

Assessed various browser runtime solutions, such as Cordova and Ionic, for their capability to handle background processing tasks effectively. Led and coordinated efforts of a geographically dispersed development team, overseeing multiple sites and ensuring a cohesive development strategy across on-site and offshore units.

Key Technologies:
Android, iOS, Javascript, HTML5, AngularJS, gulp, node.js, grunt, bower, Yeoman, Cordova/Ionic,
Java/Groovy, Grails Backend, Mysql/MongoDB, Hadoop, Cassandra, Aerospike, Apache Spark, Apache
Kafka, RESTful API, Wireframes, User Stories, CSS, Touch Interfaces, Touch UE Design, iBeacon, BLE,
WLAN, Bluetooth, Sensors, NFC, ARM, embedded Linux. RxJava on Android, Google Play Services, native
Android, statistics. Various Cloud environments and Push services, Intellij Idea. WebStorm and
Android Studio. Jira, Confluence, Stash, BitBucket. IoT and Sensors.

Extending/finalizing an Android app for an in-car Entertainment solution.

Key Technologies:

Android, Media streaming, Background Services, XML, Notifications, Power Management. Tablet/Smartphone layout rewrites, adaptations and optimizations. Device specific fixes. Custom Theming. Wireframes.

IntelliJ Idea, git, embedded.

Implementing a Location Based Services scheme for iBeacons on Android.

Key Technologies:

Android, iBeacons, BLE, Bluetooth, Background Services, JSON, RESTful interfaces, Notifications, Power Management, GSON. Workshops explaining iBeacon Technology. Handling iBeacon hardware selection.

Defining and implementing the mobile client for a complex use case for BMW Motorrad.

Key Technologies:

Android, Wireframes, UX Design, RESTful interfaces. Custom UE components, Tablet UE, QR Scanner, Camera, Jackson, JSON, Encryption, Authentication.

Developing/implementing/improving the strategy and architecture of a portable mobile platform solution. Implementation of the specific the Android release. The solution is the strategic, portable and modular mobile platform of a worldwide insurance company.

Key Technologies:

Android, Phonegap/Cordova, iOS, Javascript, jQuery, HTML5, AngularJS, Java, Wireframes, CSS, Touch Interfaces, Touch UE Design, Backend, Browser based Apps, Portable Apps, Webkit, native Interfaces, Tablet, Smartphone. Android libraries like ActionbarSherlock, Maven, git, SVN, Testing, Documentation. Modular build concept based on Maven. Migration to Gradle. Yeoman, grunt, bower, node.js. Intellij Idea/Android Studio, WebStorm.

• Developing and implementing the touch UE for an industrial system based on GWT and browser based technologies. Defining and building up the general System Architecture for the Client, Documentation based an message events, custom UI Widgets and WebSocket communications.
• Managing the UI definition process (System analysis, defining Requirements, producing the Wireframes, briefing visual design teams, refining wireframes and visuals, implementing final visual design)

• Small parallel project: Developing/implementing the potential architecture for a tablet device content application.

• Analyzing the requirements and technology for ongoing and future Android projects regarding changes imposed by Android ICS. Developing a strategy for UE, testing etc.

• Developing the future architecture for a platform-independent mobile application suite. Taking over the further development of an existing Android system analysis application. Customizing this application. Extending a market research application, which gathers all the available information about activities on the phone of Market research Panel users for market research analysis.

• Analyzing the requirements and technology for a broad VoIP-Solution for Android and iOS-Devices. Project management tasks Telekom-internally and as a peer to an international software development company. Discussing and defining use cases for the application and test teams.
• Providing solutions for the integration into the Telekom network.

• Developing the system architecture, the user interface design and implementing a touch user interface based solution for a mobile network analyzer. The solution runs on Linux in an embedded environment (OMAP) and on Android. The user interface runs as compiled JavaScript in a browser object while the control logic is implemented as a Python module.

• Developing a concept for a iPad-specific transformation of Desktop web content of a larger newspaper.  Stopped because of time constraints.

• Technical consultancy and workshops regarding Android, general mobile platforms, appstores and browser based applications. Discussing and developing solutions with the Scrum team.
• VoIP feasibility study based on native applications and browser based frameworks

• Designing a new VoIP-based communication suite for Android handsets based on LTE (transport) and IMS (media session management) as the lead system design architect (technical project management). Defining the system design for the application CPU (not the transport layer) including RIL and the general app design (wireframes, technical architecture etc.) for VoIP and Video calls.
• Integrating into Android address book and other native apps. Android, Java, C, LTE, IMS, Radio, RIL, Android telephony, UX (User Experience). Working in an international and mixed Agile/Scrum vs. classic Waterfall environment.
• This project has migrated to VoLTE on IMS

• Driving the OMTP BONDI standard for browser based applications. Defining new requirements and specifications for BONDI APIs. Driving native ports. Implementing selected APIs. Defining technical architectures for potential ports. Face2 Face meetings, phone conferences

• Developing a completely new browser based application framework including the UE concept for platform independent browser based applications. Definition of a mobile platform, all interfaces to a real mobile platform (LTE, EMP), inter application communication, fundamental Widgets and User Experience. Definition of important use cases for proof-of-concept work. WebKit work.
• Implementation under various platforms including Android.

• Porting Android onto the In-Car-Entertainment System of a car company. Defining the system architecture for an Android based in-car solution. Developing use cases for a “connected car”, presentation of dynamic car parameters (speed, temp, oil pressure, recurring track times etc.) security/sandboxing and app store concepts.

• Developing and improving of a prototype design for multimedia services as part of the Ericsson Mobile Platform (EMP). Integration of the prototype description and design into existing platforms.
• Developing new services based on SIP/IMS-Frameworks and EMP (Audio, Video, Text Messaging, File Transfer, Whiteboarding). Testing. Integration of the new services into the platform as well as other applications. System design, System architecture, International standard requirements.
• Defining the complete UE (GUI/User Experience) of the new application suite including wireframes, screens (managing external graphics department) and defining the system requirements along the way.
• Concepts for future applications based on LTE/WiMax/HSPAe
• Concepts for new UE based on browser based applications, mobile Linux

• Developing, adapting and optimizing of UI flows for a „Streaming Music“-application for mobile devices and desktop PCs. Improving the existing infrastructure based on the user experience view.
• Useability Tests, Analyzing the UE.
• Developing a new solution for Podcasts, Download-Manager etc. Analyzing potential AJAX implementations.

• User Experience Manager for a large international mobile operator.
• Organisation/Management/Optimisation/Implementing of menu structures, the Look&Feel etc. based on the operator specifications for mobile devices. Managing devices from different vendors.
• Practical solutions and implementation of new services. Organisation and managing/running of device tests, fault reports/calls.
• Application Flows, Adaption, Project management, Industrial Design. GUI Design and Optimisation. GUI/HMI/CHI Interface Design, Implementing, Consulting, Mockups.
• This project includes services like MobileTV, streaming Music, PTT, IM.
• Additional activities like technical presentations covering mobile system platforms or explaining upcoming trends in the mobile industry.