AI Management & Security
Adopt AI with confidence. We help you govern AI use, securely enable the tools your teams want, and protect the models, workloads, and data pipelines behind them.
Govern, Enable, and Secure AI
AI adoption is outpacing the controls meant to manage it. Tailwind helps federal agencies and enterprises put AI to work responsibly: establishing governance, rolling out sanctioned tools with guardrails, and protecting the models, workloads, and data pipelines that power them. We combine policy expertise with the security platforms from Palo Alto Networks, Cloudflare, and F5 to turn AI from a source of risk into a managed capability.
AI Governance & Policy
Acceptable-use policies, model and use-case inventories, and risk controls aligned to the NIST AI Risk Management Framework and OMB memos M-24-10 and M-24-18: the governance foundation agencies need before scaling AI.
Secure AI Enablement
Give teams the AI tools they need without the risk. We deploy sanctioned assistants with data-loss controls, prompt inspection, and guardrails using Palo Alto AI Access Security and F5 AI Guardrails.
AI Access & Data Security
Control which generative-AI applications users can reach and stop sensitive data from leaving your environment with Palo Alto Prisma AIRS and Cloudflare Firewall for AI.
Model & Workload Protection
Defend deployed models against prompt injection, jailbreaks, and abuse. We harden AI runtimes and pressure-test them with F5 AI Red Team and Prisma AIRS runtime security.
Data Pipeline Security
Secure the data behind your models (training, fine-tuning, and RAG pipelines) with encrypted ingestion, intelligent traffic control, and reliable inference delivery built on F5 BIG-IP and NGINX.
Monitoring & Compliance
Gain visibility across AI apps, APIs, and third-party services with audit-ready reporting that demonstrates compliance with the NIST AI RMF and FedRAMP requirements.
Our AI Security Approach
We follow a phased approach aligned with the NIST AI Risk Management Framework. First we govern, establishing acceptable-use policies, a model and use-case inventory, and the roles that own AI risk. Next we enable, rolling out sanctioned AI tools with data-loss controls and guardrails so teams gain productivity without exposure. Finally we protect, securing models against prompt injection and abuse, hardening the data pipelines that feed them, and monitoring AI usage continuously. Each phase maps to the framework's Govern, Map, Measure, and Manage functions, giving you a defensible, audit-ready AI program.