Deep dives, architectural patterns, and real-world playbooks straight from the desks of zCon's senior engineers and architects.
A practical comparison of headcount-led outsourcing and AI-native delivery models built around reusable skills, automation, governance, and faster enterprise software outcomes.
How Micro GCC compares with a traditional global capability center for enterprises that need dedicated AI-native engineering capacity without a long setup cycle.
How reusable delivery skills turn AI-assisted engineering from one-off prompting into a repeatable system for faster planning, implementation, review, testing, and release.
A practical comparison of RAG-only systems and knowledge graph grounded AI for enterprises that need traceability, business rules, context, and reliable answers.
A phased roadmap for using AI to understand, document, stabilize, refactor, test, and modernize legacy systems while controlling production risk.
A deep dive into how we built a scalable Retrieval-Augmented Generation pipeline to unlock siloed document stores for a Fortune 500 financial institution.
How we utilize custom LLMs to accelerate the reverse-engineering and refactoring of legacy monolithic applications into containerized microservices.
Exploring the event-driven architecture required to process thousands of IoT sensor data points per second using Kafka and Azure Databricks.
Why simple vector search isn't enough. We explore how combining semantic search with structural Knowledge Graphs eliminates hallucinations in enterprise chat.
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