What Is AI Observability? A Platform Buyer's Guide
A buyer's guide to AI observability, covering what a platform captures for AI agents and eight criteria for evaluating one.
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Gateway-Level PII Redaction Before Provider Transmission
TL;DR
* Gateway-level PII redaction detects sensitive values in an LLM request and rewrites them before the request leaves your network, so no application has to sanitize its own prompts.
* Bifrost implements this through guardrails: rules written in Common Expression Language decide when to evaluate, and profiles decide how,
Shadow MCP Servers: Visibility and Control at the Gateway
TL;DR
* Shadow MCP servers are Model Context Protocol connections wired into AI apps on employee machines without organizational visibility, and they can read files, call internal APIs, and take actions on the user's behalf.
* The exposure is measured, not theoretical: a July 2025 internet-wide scan by
AI Governance Framework for CISOs: Mapping Controls to Security Frameworks
A guide for CISOs mapping eight AI controls onto SOC 2, ISO 27001, NIST AI RMF, NIST CSF 2.0 and the EU AI Act.
How to Version and Roll Back AI Agent Skills Across a Team
TL;DR
* AI agent skills are reusable SKILL.md folders that give coding agents like Claude Code and Codex domain-specific instructions, and teams accumulate dozens of them fast once more than one person is writing skills.
* Bifrost's Skills Repository lets a team create, publish, and version agent
What Is Adaptive Load Balancing?
TL;DR
* Adaptive load balancing distributes AI traffic across providers and API keys using live performance data instead of a fixed weight or round-robin rule.
* Bifrost Enterprise recalculates route weights every 5 seconds from error rate, latency, and utilization, adding less than 10 microseconds to routing overhead.
* Routes move
Claude Gateway: Route Claude and Claude Code Through One Unified AI Gateway
A guide to routing Anthropic Claude models and Claude Code through one Anthropic-compatible gateway with failover, governance and caching.