Drive Innovation with Ease

Practical Azure & AI Application Development

Hands-on design and build of AI-oriented applications on Azure, drawing on 5+ years with Microsoft 365 / SharePoint front-end solutions (state management, UI composition, extensibility) and related cloud services.
Current interests: conversational and multimodal interfaces, retrieval-augmented intelligence, real-time interaction, and secure enterprise data connections.

Flexible Collaboration

Can work independently or alongside existing teams to move architectural choices, prototypes, performance improvements, and deployment setup forward steadily.
Aim: clearer patterns, simpler pipelines, maintainable code, and smooth handover.

Patterns for AI Workloads

Data ingestion, chunking & embeddings, retrieval indexing, prompt / tool flow, caching, guardrails, monitoring, light analytics.
Includes document and image processing workflows (e.g. extracting structured data from payslips) using vision/OCR + post-processing for validation.

Focused Cloud Architecture

Pragmatic Azure (selective AWS when needed): identity, networking, vector/search, event or streaming pieces, basic observability, cost awareness.
Use of Infrastructure as Code (Bicep / Terraform), CI/CD, and consistent environments to reduce friction.

Multimodal Focus Areas

Speech: real-time interaction and transcription alignment.
Vision & Documents: OCR, payslip field extraction, layout-aware parsing, enrichment steps.
Avatars: interactive face + voice layers tied to streaming responses.
Text & Retrieval: hybrid search, embeddings, grounding and guardrails.

Azure OpenAI & Azure AI Foundry Exploration

Conversational, real-time (speech + avatar), multimodal (text, speech, image, document), summarization, and retrieval-augmented reasoning features.
Exploring Azure AI Foundry for model evaluation, safety checks, lifecycle management, and compliant deployment alignment.

Exploring an AI Use Case?

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EaseMe Solutions Kft