Our Blog
Insights, guides, and perspectives on AI, software development, and technology trends from the NEXPATCH team.
Private AI Agent Systems with Orchestrated Specialist Models
How private multi-agent systems combine small specialist models, MCP, A2A and cost-aware routing into secure enterprise AI architectures.
Time Series Forecasting with PatchTST: Why Classical Models Are No Longer Enough
Why modern time series forecasting needs more than ARIMA and Prophet: patch-based Transformers, rigorous benchmarks, and a platform that connects ETL, training, monitoring, and forecast APIs.
Private AI: Running LLMs on Your Own Infrastructure — 60% Cheaper Than OpenAI
European enterprises are bringing AI in-house. Open-source LLMs now match GPT-4-level performance, and self-hosting at scale delivers 40–60% cost savings — with full GDPR and EU AI Act compliance.
ETL Pipelines Reimagined: Visual Pipeline Orchestration with Orpheon
Manual ETL maintenance consumes 60–80% of data engineering time. Visual pipeline orchestration bridges the gap between no-code and code-first — with Orpheon as a visual platform for Parquet, DuckDB, real-time and batch processing.
Agentic AI in Practice: How Specialized Agents Automate Enterprise Processes
How autonomous AI agents with orchestrator architecture automate complex business processes in finance, supply chain, and e-commerce — with practical examples, KPIs, and a decision-maker checklist.
LangGraph Deep Dive: Zyklische Workflows und State Management für AI-Agenten
LangGraph enables complex, stateful agent processes with cyclic workflows, conditional branching, and checkpointing — far beyond linear LangChain chains.
Agentic AI and PatchTST: Why Classical Forecasting Models Are Reaching Their Limits
PatchTST sets new standards in multivariate time series forecasting. Combined with agentic AI orchestration, it enables adaptive forecasting pipelines that systematically outperform ARIMA and Prophet.
Agentic AI in the Enterprise: Architecture, Implementation and the Path to Production
Multi-agent systems with a central orchestrator automate complex business processes. A hands-on guide to architecture, risks, EU AI Act compliance, and the path to a production-ready MVP.
Editor's Choice
Private AI Agent Systems with Orchestrated Specialist Models
How private multi-agent systems combine small specialist models, MCP, A2A and cost-aware routing into secure enterprise AI architectures.
Time Series Forecasting with PatchTST: Why Classical Models Are No Longer Enough
Why modern time series forecasting needs more than ARIMA and Prophet: patch-based Transformers, rigorous benchmarks, and a platform that connects ETL, training, monitoring, and forecast APIs.
Private AI: Running LLMs on Your Own Infrastructure — 60% Cheaper Than OpenAI
European enterprises are bringing AI in-house. Open-source LLMs now match GPT-4-level performance, and self-hosting at scale delivers 40–60% cost savings — with full GDPR and EU AI Act compliance.
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