AI Strategy
What Is an AI Control Plane?
An AI control plane unifies identity, policy, guardrails, and audit across your entire agent fleet — so you govern every AI interaction from one place.
Blog
Insights & updates
AI agent security, identity, governance, cost, and the engineering behind the control plane.
Identity & Access
How to Implement Least Privilege for AI Agents
Apply least privilege to AI agents with scoped credentials, per-connection policies, and delegation constraints that shrink your blast radius.
AI Strategy
Self-Hosted vs Managed AI Governance
Self-hosted AI governance gives full data residency control; managed shifts operational burden to the vendor. How to choose for your team.
AI Strategy
Choosing an AI Agent Management Platform: A Buyer's Guide
A structured buyer's framework for evaluating AI agent management platforms across identity, governance, cost control, observability, and compliance evidence.
Platform & Operations
How to Monitor MCP Tool Calls
Gain full visibility into every MCP tool call an AI agent makes — with attribution, policy decisions, and cost data needed for security and compliance.
Platform & Operations
Orchestration Patterns for Multi-Agent Systems
Compare pipeline, hub-and-spoke, and blackboard orchestration patterns for multi-agent AI — with security, cost, and auditability trade-offs for each.
AI Agent Security
Agent-to-Agent Protocols and Interoperability
How to design safe A2A interoperability: agent cards, secure discovery, scoped credentials, and cross-org trust — in under 8 minutes.
AI Governance & Compliance
Human-in-the-Loop Approvals for High-Risk Agent Actions
Human-in-the-loop approvals pause AI agents before high-risk actions, preserve throughput with async queues, and build an auditable approval trail.
AI FinOps
Cost Control for LLM Applications
Where LLM costs hide in agentic applications, how to attribute them per agent and run, and the reservation-based enforcement that stops overspend at dispatch.
Platform & Operations
Observability for AI Agents: Logs, Metrics, and Traces
How logs, metrics, and distributed traces apply to AI agents—what to instrument, where costs hide, and how to connect all three for fast incident triage.
Platform & Operations
Rate Limiting and Abuse Prevention for AI APIs
Request counts alone don't protect AI APIs. The layered controls that work: per-connection limits, spend caps, tool allow-lists, and trust gates.
AI Agent Security
Data Exfiltration Risks in Agentic AI
Agentic AI creates novel data exfiltration paths via over-broad tool access, chatty outputs, and prompt injection. Learn how to contain each risk layer.
AI Agent Security
Prompt Injection: Threats and Defenses
Prompt injection hides malicious instructions in content AI agents process. How direct and indirect variants work, and what defenses reduce the risk.
AI Agent Security
Zero Trust for AI Agents
Zero trust for AI agents means verifying every identity, enforcing least-privilege policy at every hop, and using behavioral trust scores at runtime.
AI Governance & Compliance
SOC 2 for AI Platforms: What Auditors Look For
SOC 2 auditors scrutinize AI platforms harder than traditional SaaS—learn which controls matter most, from tamper-evident audit trails to agent access.
AI Governance & Compliance
GDPR for AI Systems: Data Subject Rights and Erasure
How GDPR data subject rights apply to AI pipelines, what Article 17 erasure requires technically, and the design patterns that make compliance tractable.
Platform & Operations
MCP Server Authentication: OAuth 2.1 vs API Keys
OAuth 2.1 vs API keys for MCP servers after the Nov 2025 spec: PKCE, RFC 8707 resource indicators, token lifetimes, revocation, and when each fits.
AI Governance & Compliance
The EU AI Act Explained for Engineering Teams
EU AI Act for engineers after the 2026 Digital Omnibus: Annex III moves to Dec 2027, Art. 49/50 land 2 Aug 2026, plus a concrete readiness path.
AI Agent Security
Why AI Infrastructure Needs a New Security Model
Traditional IAM secures human users, not AI agents making thousands of calls per minute. Why a connection-centric model is the right foundation.
AI Governance & Compliance
Building an AI Agent Inventory
How to discover, register, and maintain every AI agent you deploy — the foundational inventory that access policies, spend caps, and audit trails depend on.
Platform & Operations
Securing MCP Servers: An Authentication Guide
Most MCP servers ship with no authentication. Learn how to add identity verification, per-caller tool scoping, and guardrails to production servers.
AI Agent Security
AI Agent Security: The Complete Guide
The complete guide to AI agent security: identity, authorization, connection policies, content guardrails, monitoring, and incident response in one place.
AI Strategy
Guardrails vs Policies: Understanding AI Infrastructure Controls
Guardrails check content appropriateness; policies enforce rate limits and time windows. Both layers are required — neither substitutes for the other.
AI Governance & Compliance
What Is AI Agent Governance?
AI agent governance defines the runtime controls — identity, authorization, guardrails, budgets, and audit trails — that keep autonomous agents accountable.