A practical playbook for deploying generative AI at scale, covering governance, security, risk controls, and best practices for safe, compliant production use.
A custom framework testing Oracle 26ai’s ability to convert natural language into SQL using the 22 TPC-H benchmark. With no prompt engineering, it achieves high accuracy.
Securely connect to a MongoDB DocumentDB replica set in Kubernetes using mongosh with credentials retrieved dynamically from Kubernetes secrets for direct access.
Learn the Moment Indexing Pattern to build a Video Evidence Layer using OCR and ASR that provides verifiable, timecoded answers for knowledge management.
Many AI tools fail in production not because of model quality, but due to architectural decisions around retries, cost control, observability, and multi-tenant safety.
AI fails silently in safety-critical systems — classify failures and enforce safety with voting, OOD detection, and a Simplex-style deterministic override.
Discover how GenAI at the edge unlocks real time digital experiences with low latency intelligence, responsive architecture, and next level customer engagement.
Learn a repeatable pattern for safely adding GenAI to existing apps. Choose workflows, define contracts, handle latency, build fallbacks, and roll out with telemetry.
Queues hide overload. Without back-pressure, limits, and scaling, lag just grows until failure. Bound queues, alert on lag, fail fast, and plan capacity.
This guide builds a Strands multi-agent content analysis system — powered by Ollama Llama 3.1 — with LLM-as-judge scoring for correctness and relevance.
Ever wonder what would happen to an open source database project in case its main developers “get hit by a bus?" That’s what the “bus factor” measures.
Transformed 5-hour data loads into 1-2 minutes using Oracle's APPEND+PARALLEL+NOLOGGING, enabling researchers to go from 1-2 experiments/day to 2-3/hour.
LLM advantage is fading. Enterprises must shift to operational maturity with governance, reliability, measurement, and modular architecture to scale AI in production.