Company Brain
The context layer behind enterprise AI agents
Why organizational intelligence requires semantics, memory, permissions, tools, and more than agentic RAG.
Insights
What it takes to run enterprise AI in production.
Technical field notes on AI agents, Company Brain context, infrastructure, data platforms, governance, and physical systems. Written for leaders and builders making architecture and operating decisions.
Latest
Agents, platforms, and physical systems.
Agents & Workflows
How enterprise AI agent loops work
Observe, plan, act, evaluate, escalate, and improve without treating autonomy as the objective.
AI Infrastructure
AI factory architecture: compute, networking, and storage
Why infrastructure decisions must begin with workloads, data movement, service levels, and operations.
Physical AI
The physical AI production loop
Sense, understand, plan, act, verify, and recover across robotics and real-world automation.
Editorial focus
One enterprise AI system, four disciplines.
Enterprise AI agents
Workflow design, tools, orchestration, evaluation, governance, human handoffs, and production operation.
Company Brain and context
Knowledge, semantics, operational state, decision memory, permissions, agentic RAG, and governed tools.
AI factories and data platforms
Compute, networking, storage, serving, pipelines, retrieval, quality, lineage, observability, and economics.
Physical AI
Perception, edge systems, simulation, robotics, safety, teleoperation, and operational integration.
Bring us the workflow or architecture decision.
Email info@svc.group to discuss production constraints, timelines, and measurable outcomes.