F5 AI Guardrails
F5 AI Guardrails is a runtime AI security solution designed to protect AI models, applications, agents, and connected data throughout deployment and operation. The platform helps organizations defend against adversarial threats such as prompt injection, jailbreak attacks, harmful outputs, and unauthorized AI behavior. It provides real-time monitoring and enforcement of security policies to prevent data leakage, compliance violations, and misuse of AI systems. Organizations can implement predefined guardrails or create customized policies tailored to specific business requirements and AI use cases. The platform also delivers observability, auditing, and governance capabilities that help organizations maintain visibility into AI interactions and regulatory compliance. By combining threat protection, data security, and AI governance, F5 AI Guardrails helps enterprises operate AI systems more safely and responsibly.
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asqav
asqav is an AI governance and security platform designed to make AI agents audit-ready by providing real-time monitoring, enforcement, and verifiable proof of every action taken by an agent. It introduces a lightweight SDK that allows developers to integrate governance directly into their agents in just a few lines of code, enabling continuous oversight across the full lifecycle of AI operations. It includes behavioral monitoring to detect issues such as drift, rate limits, and scope violations, along with advanced threat detection that identifies prompt injections, exposure of sensitive data, toxic outputs, and other risks. It enforces policy through configurable “policy gates,” which apply per-agent rules, preflight checks, and dynamic approvals before actions are executed, ensuring that agents operate within defined boundaries. asqav also provides automated incident response capabilities, including the ability to suspend, quarantine, or escalate risky agents.
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Flint AI
Flint AI is a local-first, framework-agnostic AgentOps CLI that helps developers determine whether an AI agent is reliable before it reaches production. One command, flintai scan, analyzes Python source code for security vulnerabilities, misconfigurations, risky tool access, missing guardrails, and quality issues, then uses AI reasoning to triage likely false positives. A second command, flintai eval, sends functional and adversarial prompts to a running agent and scores its responses across more than 35 built-in evaluations, including factual accuracy, instruction adherence, prompt injection resistance, jailbreak resilience, and other runtime behaviors. Each agent receives a reliability score, with findings mapped to OWASP Agentic Security Initiative risks ASI01 through ASI10 and severity scored using CVSS v4.0. Flint AI works with agent frameworks and SDKs including Claude Agents SDK, LangChain, CrewAI, Anthropic SDK, OpenAI SDK, MCP servers, and AutoGen.
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Phinite
Phinite provides shared infrastructure for building, deploying, and governing AI agents across orchestration, security, observability, lifecycle management, and environment promotion — so engineering teams don't rebuild these layers for every new agent use case.
Core capabilities:
Orchestration for multi-agent systems (agent-to-agent, nested calls)
Deep session-level observability: execution timelines, decision variables, tool calls, latency/cost tracking
Private Agent Registry for skill discoverability
Eval suite for accuracy/safety benchmarking
Dev-to-Production workflow with environment promotion
Kubernetes-native deployment, VPC-internal deployability
SOC 2 Type 2 compliance
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