Technical Product, Platform & AI Services in Munich

Technical product, platform and AI services from architecture to production. stajic.de combines full-stack engineering, local and cloud AI integration, data architecture, technical SEO, infrastructure and structured delivery into one coherent implementation path.

Based in the Munich area, technical work can cover a focused architecture or integration task, a complete web application, platform modernization, AI-enabled workflows, or an end-to-end product path from requirements through deployment and ongoing operation.

Build the right solution, connect every delivery layer, and prepare it for real-world operation.— stajic.de

Solution Areas

Technical product and solution architecture — requirements, system boundaries, information architecture, data models, APIs, integrations, permissions and operational design.
Full-stack platforms and business applications — portals, internal systems, workflow applications, multi-tenant concepts, dashboards and API-driven digital products.
Local, cloud and hybrid AI solutions — AI application design using hosted APIs, local model runtimes and provider-aware architectures.
RAG, intelligent search and document workflows — ingestion, retrieval, metadata, permissions, search and application-level AI context.
Platform modernization and replatforming — architecture renewal, framework migration, integration cleanup, maintainability improvements and production hardening.
Technical SEO and multilingual publishing — semantic information architecture, structured content, internationalization, canonical strategy, hreflang, sitemaps and structured data.
Infrastructure and production operations — Linux, NGINX, Apache, PM2, Docker, deployment, reverse proxies, troubleshooting, backup and recovery.
Project and delivery structure — scope, requirements, milestones, risks, acceptance criteria, backlog structures, validation, documentation and operational readiness.

Technical Product & Solution Architecture

A strong solution begins with a clear target state. Product goals, users, data, integration points, security boundaries, delivery constraints and operational requirements are translated into a practical architecture that can guide implementation.

Architecture work can include application boundaries, frontend and backend responsibilities, database models, API contracts, authentication and authorization concepts, deployment topology, integration strategy, search architecture and AI-provider boundaries.

Full-Stack Platforms & Business Applications

Implementation work connects user-facing interfaces with backend services, databases, APIs and production infrastructure. Current platform development commonly uses TypeScript, Vue, Nuxt, Node.js, Nitro, Prisma and PostgreSQL, complemented by established technologies where they fit the application.

Customer and partner portals
Internal business applications
Structured publishing and content platforms
Multi-tenant and SaaS-oriented platform concepts
Dashboards and administration interfaces
Workflow and document applications
REST and application APIs
E-commerce and product-oriented platform components

Local, Cloud & Hybrid AI Solutions

AI services cover both hosted model APIs and locally operated models. The architecture can combine strong cloud capabilities with local execution for data control, experimentation, predictable runtime choices and direct model access.

Practical work includes OpenAI and Codex integrations, Ollama, LM Studio, local Qwen-family model workflows, model/provider abstraction, streaming responses, application lifecycle handling, AI-assisted development and structured publishing workflows.

AI Application Capabilities

Local and private AI assistants
Hybrid local/cloud model routing
Document ingestion and retrieval workflows
RAG-oriented application architecture
Intelligent search and semantic retrieval
Structured extraction, classification and summarization
AI-assisted content and publishing workflows
Developer and coding-agent integrations
Desktop AI clients and controlled local runtimes

The application layer remains the center of the design: data access, permissions, retrieval, evaluation, logging, provider selection and user workflows are structured around the required outcome.

Data, Search & RAG Architecture

Data architecture supports both transactional applications and search-oriented platforms. Experience spans PostgreSQL, MySQL, MongoDB, SQLite, Prisma and Solr, together with metadata-driven systems and retrieval-oriented application design.

Relational data modelling and schema design
Application data access with Prisma
Search indexing and metadata structures
Document ingestion pipelines
Retrieval and context preparation for AI applications
Permission-aware access patterns
Data migration and integration planning
Operational data and content workflows

Platform Modernization & Replatforming

Existing platforms can be evolved toward a clearer architecture, current frameworks, stronger data boundaries and more maintainable production operations. Modernization can be incremental or structured as a defined replatforming path.

Architecture and dependency review
Framework and runtime modernization
Database and API restructuring
Frontend migration and component architecture
Deployment and infrastructure renewal
Performance and stability improvements
SEO-preserving URL and content migration
Operational documentation and release readiness

Technical SEO & Multilingual Publishing

Search visibility is designed into the platform architecture. Technical SEO work connects crawlability, page structure, performance, multilingual routing, metadata and semantic publishing with the underlying application and content model.

Information and URL architecture
Canonical and hreflang strategy
Sitemap design
Structured data
Server-side rendering and indexable content
Multilingual content models
Semantic taxonomy and internal linking
EditorJS and structured publishing workflows
Performance-oriented delivery and image handling

Infrastructure & Production Operations

Application delivery continues through the production environment. Linux administration, web servers, deployment workflows, networking and troubleshooting are integrated into the technical design so that implementation and operation remain connected.

Linux server administration
NGINX and Apache
PM2 and Node.js runtime operation
Docker-based environments
Reverse proxies and routing
Git-based deployment workflows
Logging and operational diagnostics
Backup and recovery concepts
Networking and connectivity troubleshooting
Performance and stability optimization

Project, Product & Delivery Services

Technical delivery is supported by formally validated project and Scrum competence: IPMA® Level D – Certified Project Management Associate and Professional Scrum Master I (PSM I). This creates a direct connection between requirements, project structure, implementation and operational readiness.

Requirements and scope structuring
Milestone and roadmap planning
Risk and opportunity management
Stakeholder communication
Acceptance criteria
Backlog and epic structure
Validation and delivery evidence
Architecture decisions
Change coordination
Launch and operational readiness

Jira & Confluence in Delivery Practice

Jira supports backlog, epic, issue, task, workflow and delivery tracking. Confluence provides the structured knowledge layer for requirements, architecture, decisions, roadmaps, traceability and project documentation. Git and GitHub connect the delivery structure with version-controlled implementation.

Flexible Engagement Scope

The scope can be shaped around the required outcome, from focused technical architecture and implementation work to a broader product and platform delivery path.

Solution and platform architecture
Technical concept and implementation roadmap
Full-stack feature or application development
Local or cloud AI integration
RAG and document workflow design
Platform modernization and migration
Technical SEO and multilingual architecture
Infrastructure and production readiness
Delivery documentation and project structuring

Technology in Context

Current work commonly combines JavaScript, TypeScript, Vue, Nuxt, Node.js, Nitro, Prisma, PostgreSQL, Linux, NGINX, Electron, APIs and modern AI runtimes. Complementary experience includes PHP, Python, Django, MySQL, MongoDB, Solr, Apache, Docker, Three.js, OpenSeadragon and TensorFlow.

Practical Platform Evidence

Independent platforms and technical projects provide practical evidence across architecture, implementation, SEO, AI workflows, deployment and ongoing operation.

stajic.de — technical platform, professional portfolio and structured enterprise knowledge architecture.
loving.rocks — multilingual wedding and lifestyle platform with semantic content and SEO Pillars.
figure.rocks — gaming, technology and collectibles platform with structured publishing and technical content.
Aaasaasa AI Client — Electron and TypeScript desktop AI client with local and remote model integration, secure IPC, sidecars and cross-platform packaging.
Enterprise Aaasaasa 0.1 — platform and PoC work connecting software architecture with formal project and delivery methods.

A deeper view of the local-AI application approach is available in Production-Ready Open-LLM Applications.

Technical Services in the Munich Area

stajic.de is based in Taufkirchen near Munich. Project work can be structured for local collaboration in the Munich area as well as distributed technical delivery using modern documentation, communication and version-control workflows.

The complete professional background, certifications, technology profile and selected project work are available in the Curriculum Vitae.

Build the Right Solution

A clear target, suitable architecture and structured delivery path create the foundation for effective implementation. Share the desired outcome, current environment and key requirements to define the next technical step.

Direct contact: info@stajic.de