5.0 out of 5 stars
(3 Ratings)
BAND develops comprehensive interaction frameworks tailored for large-scale applications of distributed AI agents. This platform enables real-time, collaborative communication between agents and humans while integrating a runtime control plane that maintains policy adherence, establishes authority boundaries, and guarantees transparency across varied systems.
Moreover, BAND supports developers, engineering teams, and leaders overseeing enterprise platforms that manage multi-agent ecosystems across internal frameworks, SaaS offerings, and collaborative environments with partners. This robust support not only improves operational efficiency but also stimulates innovation within intricate organizational frameworks, ultimately driving progress and adaptability in a rapidly evolving technological landscape.
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4.4 out of 5 stars
(41 Ratings)
Jscrambler is the leader in Client-Side Security, protecting the code, data, and digital interactions that power modern web applications.
As organizations increasingly adopt AI-generated code, third-party software components, and AI-powered agents, more critical application logic and sensitive data are exposed within the browser. Jscrambler provides the security and governance layer for this environment, giving enterprises visibility and control over what happens at runtime.
The Jscrambler Client-Side Security Platform is powered by a Behavioral Enforcement Core that continuously monitors and enforces how application code, including AI-generated code, third-party scripts, AI agents, and sensitive data behave in the browser. By enforcing software integrity and data governance at runtime, Jscrambler helps organizations prevent client-side attacks, protect sensitive data, and maintain control over digital experiences.
Trusted by organizations across financial services, retail, travel, healthcare, and other industries, Jscrambler helps enterprises address client-side security and compliance requirements including PCI DSS, GDPR, HIPAA, CIPA, CCPA, and the EU AI Act.
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CloudEagle.ai
5.0 out of 5 stars
(1 Rating)
CloudEagle.ai is an AI-powered SaaS Management, AI Governance, and Identity Governance platform that helps IT, Security, Procurement, and Finance teams discover, govern, secure, and optimize every SaaS and AI application across the enterprise, including applications operating outside SSO or traditional IT visibility.
As AI tools, Shadow IT, and employee-purchased applications rapidly expand, traditional IAM and SaaS management solutions can no longer provide complete visibility or control. CloudEagle brings SaaS management, AI governance, identity governance, security, and procurement workflows together into one unified platform.
Powered by 500+ integrations and AI-driven contract and usage intelligence, CloudEagle centralizes application usage, access permissions, contracts, renewals, and spend data into a single source of truth, helping organizations reduce waste, strengthen security, improve compliance readiness, and streamline SaaS operations.
Key Features-
• Shadow IT & Shadow AI Discovery
• AI Governance & Policy Enforcement
• AI Usage Visibility & Risk Monitoring
• Automated Provisioning & Deprovisioning
• Identity Governance & Access Controls
• Continuous Access Reviews
• SaaS Management & License Optimization
• SaaS Spend Visibility & Reporting
• Centralized Contract Management
• Renewal Orchestration & Benchmarking Insights
• Audit-Ready Access Logs
• 500+ Integrations
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AgentFox
AgentFox is an open-source control plane tailored for the creation and oversight of AI agents. It methodically organizes agent repositories while establishing a connection between agents, tools, MCP servers, skills, and handoffs, all without executing code. For the frameworks it accommodates, it upholds tool-access policies, verifies tool arguments against set thresholds, and possesses the ability to suspend or reject actions until human review is conducted. Runtime assessments evaluate the interactions between models and tools to identify possible prompt injection threats and the risk of exposing confidential or personal data. Furthermore, AgentFox can function in observation mode before implementing enforcement measures, and it carefully records policy decisions in a hash-linked audit trail. Developers can choose to install AgentFox via Python or deploy it through a Docker Compose stack, making it versatile for different environments. Its target audience comprises engineering and security teams that seek thorough visibility, control mechanisms, and reliable documentation for managing AI agent activities. Released under the Apache-2.0 license, AgentFox also provides a hosted preview for potential users. This feature enhances accessibility for teams striving to improve their AI workflows with effective management solutions, ultimately supporting better collaboration and security in AI development.
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