What Compliance Teams Actually Need from AI Agent Audit Trails
A look at the gap between what most AI agent logs capture and what a compliance officer needs to answer an access-review question from an auditor.
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Enterprise AI, governed data, and the context layer
Technical writing from the Strattum team on MCP connector architecture, enterprise compliance patterns, and the infrastructure behind governed context delivery.
MCP Connectors for Enterprise: Beyond Simple API Wrappers
Why enterprise data connectors in AI systems require schema negotiation, credential isolation, and audit-capture at the protocol layer, not bolted on afterward.
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Connecting SAP and Salesforce Data to AI Agents Without Breaking Your Schema
A practical walkthrough of the connector patterns that keep SAP and Salesforce integrations stable when source schemas change.
Data Residency Rules and AI Agent Context Access: What Regulated Firms Need to Know
How data residency requirements affect the way AI agents can request and process enterprise context, and the architectural patterns that keep queries compliant.
Your AI Agent Needs a Context Bus, Not Another Vector Database
Vector databases solve a different problem than enterprise context delivery. Here is why the two architectures diverge and when a governed context bus is the right tool.
Access Control Patterns for AI Data Queries in Regulated Sectors
A comparison of three access control models for enterprise AI data access: allowlist-by-field, role-scoped query, and classification-tag filtering.
The Hidden Cost of Hardcoded Data Pipelines in Enterprise AI
When engineers build one-off data connectors per AI agent project, the real cost shows up six months later. Three patterns that compound the maintenance burden.
Explaining the MCP Protocol to Your Engineering Team
A plain-language technical overview of the Model Context Protocol, what problems it was designed to solve, and why it matters for enterprise AI data access in 2026.
Governed Context vs. Raw Access: A Decision Framework
When does a governed context layer add value versus adding friction? A framework for teams deciding between full access delegation and policy-scoped context delivery.
Why Enterprise AI Agents Need a Data Middleware Layer
The foundational case for putting a governed middleware layer between AI agents and enterprise data sources, and the three failure modes that emerge when you skip it.
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New articles on enterprise AI data governance
Practical writing on MCP connector architecture, compliance patterns, and governed context delivery for regulated industries.