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ZigmaNeural articles
Insights, guides and explainers on AI agents, RAG, governance, cost and cloud. Use the filters to switch between analysis for leaders and how-to guides for builders. The Insights page explains what each type is for.
16 articles published
What an LLM Feature Really Costs to Run for a Year
Three worked examples with real per-token prices show what a chatbot, a document Q&A tool and a batch job cost per month and per year.
EU AI Act: What Indian AI Vendors Serving EU Clients Must Do
If your AI system or its output is used in the EU, the AI Act can apply to you. Here is what changed in 2026 and what Indian vendors should do now.
India's DPDP Act and AI Projects: A Practical Checklist
What India's DPDP Act and Rules mean for RAG, chatbots, analytics and model training, with a checklist, penalty figures and questions for your AI vendor.
AI InfrastructureSK hynix Co-Packaged Optics Roadmap: Why Data Movement Matters
SK hynix and university researchers published a co-packaged optics roadmap in Nature Electronics. Here is why data movement, not raw compute, is becoming the binding constraint on AI systems.
AI NewsSamsung Connected Care: What AI in Health Means for Enterprises
Samsung describes a vision of AI-led connected care. The wider lesson for enterprises is about turning continuous real-world sensor data into useful, private, trustworthy insight.
AI NewsOpenAI Keeps Zero Data Retention and Previews Safety Tool
OpenAI has reaffirmed Zero Data Retention for eligible API customers and previewed Private Safety Processing. Here is what that changes for enterprise AI architecture, data privacy, governance and vendor due diligence.
AI NewsAsana Says Codex Did Five Years of Work in Two Weeks
Asana reports it replaced an outdated testing system in about two weeks using OpenAI Codex, work previously estimated at five years and roughly $6M in staffing. Here is what agentic coding realistically changes for enterprise engineering teams.
AI InfrastructureOpenAI Agrees to Secure 8 GW of AI Capacity in Ohio
OpenAI has announced an agreement for approximately 8 gigawatts-IT at the PORTS-Pike Technology Campus in Ohio. The lesson for enterprises is not to copy the scale, but to size their own AI workloads honestly.
AI GovernanceHow Can Enterprises Secure, Govern, and Monitor AI Agents?
A practical enterprise architecture for agentic AI: per-agent identity, action-level policy enforcement, containment, continuous evaluation, and a decision trail auditors accept.
All articles
- What an LLM Feature Really Costs to Run for a Year
- EU AI Act: What Indian AI Vendors Serving EU Clients Must Do
- India's DPDP Act and AI Projects: A Practical Checklist
- SK hynix Co-Packaged Optics Roadmap: Why Data Movement Matters
- Samsung Connected Care: What AI in Health Means for Enterprises
- OpenAI Keeps Zero Data Retention and Previews Safety Tool
- Asana Says Codex Did Five Years of Work in Two Weeks
- OpenAI Agrees to Secure 8 GW of AI Capacity in Ohio
- How Can Enterprises Secure, Govern, and Monitor AI Agents?
- What an AI-First Infrastructure Strategy Means for SaaS
- How to Build a Responsible AI Governance Framework
- RAG vs Fine-Tuning: A Decision Guide for Enterprise LLMs
- AI Readiness Assessment: A Guide for Enterprise Teams
- Cloud-Native Architecture for AI Workloads: A Practical Guide
- Build vs Buy: Enterprise AI Platform Decision Guide
- Evaluating AI Vendors in 2026: An Enterprise Framework