Lasso AI Security Platform vs Qpoint

Lasso AI Security Platform provides observability, governance and runtime defense for enterprise AI environments. It inventories AI applications, agents, tools, MCP servers and connected resources, then maps relationships among agents, databases and APIs to identify misconfigurations and policy gaps. Automated red teaming tests applications in static, dynamic and high-agency modes. At the gateway, Lasso inspects prompts, responses, tool calls, MCP communications and sub-agent traffic; policies can block, mask or alert on violations with enforcement under 50 milliseconds. Shadow AI monitoring covers more than 8,000 tools, including chatbots, coding assistants and MCP servers. Supported agents include Vertex AI, Microsoft Copilot, AWS Bedrock, Salesforce Agentforce and custom platforms. Activity and audit trails map to listed security and regulatory frameworks. Deployment can use browser extensions, proxy integrations and data integrations in a hybrid model. Pricing is available on request.

Qpoint monitors AI agents and applies policies where they run. It captures file activity, tool calls, outbound network requests and process execution, attributing events to agents and sessions. Policies can block secret reads, reject unapproved endpoints, redact outbound content and deny unapproved tool calls. Qpoint describes its endpoint deployment as a single binary, without gateways, sidecars or SDK integration; it can also run in containers, virtual machines, clusters and CI runners. It supports Linux, macOS, Windows and web, and lists Kubernetes support, network visibility and application tracing. Events can be exported to SIEM and observability systems, with Splunk, Datadog and Elastic named. The free Community plan covers up to 25 endpoints; Team covers up to 500, and Enterprise has unlimited endpoints. Enterprise includes SSO and role-based access control. Qpoint states that it has achieved SOC 2 Type II compliance.