Cisco AI Defense vs Prediction Guard

Cisco AI Defense is Cisco's security product for enterprise AI applications, models and agents. Cisco unveiled it on January 15, 2025 and said it would be available that March. It is built on Robust Intelligence, the AI security startup Cisco announced it would acquire on August 26, 2024 and finished acquiring on September 24, 2024; Dark Reading called Robust Intelligence the core component of AI Defense. The product is sold by Cisco Systems, Inc., which was incorporated in 1984 and is based in San Jose; this profile lists Cisco's founding year and headquarters, as the directory does for other big-company products. Cisco's May 2026 data sheet splits the product into four parts. AI Cloud Visibility discovers AI models, applications, connected data sources, MCP servers and agents, including assets in Amazon Bedrock, Google Vertex and Azure AI Foundry. AI Supply Chain Risk Management scans model files, repositories and MCP servers and tools, and gives each asset a risk score. AI Model and Application Validation runs algorithmic red teaming with more than 200 attack techniques and threat subcategories. AI Runtime Protection applies safety, security and privacy guardrails, enforces MCP policies at runtime and protects agent behavior. Runtime checks can run at the network level through Cisco Multicloud Defense, through a gateway, or through an Inspection API. Hybrid deployments (AWS EKS, Azure AKS, GCP and on-premises AI PODs on OpenShift) keep sensitive data in the customer's environment. A separate AI Access module, for employee use of third-party AI apps, comes through Cisco Secure Access and needs its Advantage package. **Agent and MCP security** In February 2026 Cisco added an AI bill of materials, an MCP Catalog, multi-turn red teaming of models and agents, real-time agentic guardrails and an integration with NVIDIA NeMo Guardrails; the release gave no availability dates. In March 2026 it launched AI Defense: Explorer Edition, a self-service red-teaming tool Cisco offers at no upfront cost, and announced an Agent Runtime SDK for Amazon Bedrock AgentCore, Google Vertex Agent Builder, Azure AI Foundry and LangChain, plus DefenseClaw, an open-source agent security framework. **Frameworks** Cisco says AI Defense has mapped to NIST, OWASP and MITRE frameworks since launch. Its data sheet names the NIST AI RMF, MITRE ATLAS and the OWASP Top 10 for LLMs, and red-team reports also map to Cisco's own Integrated AI Security and Safety Framework. We found no documented support for the EU AI Act or ISO 42001. **Who it's for** Large enterprises that already use Cisco security products (Secure Access, Multicloud Defense, Splunk) and want AI discovery, red teaming and runtime guardrails from one vendor. Cisco doesn't publish prices.

Prediction Guard sells a self-hosted "sovereign AI control plane" for regulated organizations. It sits between applications and the models, agents and MCP tools they call, and applies access, safety and policy controls to each request inside the customer's own infrastructure. The company was founded in 2023 in Lafayette, Indiana; CEO Daniel Whitenack is a co-founder. It raised a $3.7 million seed round led by Sovereign Capital in May 2025, and Noblis Ventures made a strategic investment of undisclosed size in July 2025. At the time of the seed round it had eight employees and said it had 18 customers in health care, defense, transportation and manufacturing. The platform registers each agent with an identity and role and limits it to the models and tools that role needs. Runtime controls include PII masking, prompt injection detection, toxicity filtering, input sanitization, MCP tool scoping and human-in-the-loop approval; requests that fail a policy are blocked and logged. It produces an exportable AI bill of materials (CycloneDX) of models, guardrails and MCP servers, runs model security scans and streams security events to SIEM tools such as Splunk, Datadog and Grafana. Applications call it through OpenAI- and Anthropic-compatible APIs. It deploys into a customer VPC on AWS, Azure or Google Cloud, on Kubernetes on premises, or air-gapped. Prediction Guard says its control overhead is under 200 ms per request. **AI compliance coverage** Prediction Guard says its policies align with the NIST AI RMF, NIST AI 600-1, the OWASP Top 10 for LLM and agentic applications, OMB M-26-04 and AIUC-1, with one-click baselines and an exportable "proof of alignment" for the NIST AI RMF. A company blog post (August 2026) adds the EU AI Act and ISO/IEC 42001. The same post labels its OWASP mapping "self-published" and not independently verified, and notes that the audit log records enforcement events rather than full replayable traces. We found no published control-by-control mapping. The homepage shows badges for a SOC 2 Type 2 report by Sensiba and HIPAA compliance; there is no public trust center. **Who it's for** Regulated enterprises and public sector bodies that want AI guardrails and agent controls to run inside their own network, including disconnected environments. It is sold to government through Carahsoft. Its homepage quotes executives at Noblis (also an investor), SimWerx and iBase-t.