Multi-Agent AI Architecture: System Design & Implementation
Production-ready multi-agent architecture for enterprise customer support. System design patterns, technology stack selection, and ROI considerations for LLM-based automation.
Read ArticleRAG Implementation: Vector Database & Retrieval Setup
Complete RAG architecture with PostgreSQL, MongoDB, and vector embeddings. Database schema design, chunking strategies, and semantic search implementation for enterprise knowledge bases.
Read ArticleAI Compliance Agent: Policy Enforcement & Guardrails
Building specialised agents for regulatory compliance and policy enforcement. Implementing guardrails, content filtering, and business rule validation in LLM applications.
Read ArticleIntelligent Ticket Routing: LLM-Based Classification
Automated ticket management with AI-powered routing and priority assessment. Intent classification, workflow automation, and helpdesk platform integration patterns.
Read ArticleAgent Orchestration: Coordinating Multi-Agent Systems
Master orchestration patterns for multi-agent LLM systems. Advanced routing logic, context management, conversation state handling, and agent coordination strategies.
Read ArticleLocation-Aware AI: Regional Customisation Patterns
Implementing location intelligence in enterprise AI systems. Multi-region deployment, timezone handling, localisation strategies, and regulatory compliance by geography.
Read ArticleTesting LLM Applications: Strategies & Best Practices
Comprehensive testing for multi-agent AI systems. Unit testing, integration testing, evaluation metrics, CI/CD pipelines, and production deployment strategies.
Read ArticleMeasuring AI ROI: Business Metrics & Optimisation
Quantifying AI investment returns in enterprise deployments. KPI frameworks, cost-benefit analysis, change management strategies, and scaling considerations for production AI.
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