Qpoint

Qpoint is an AI-agent monitoring and policy enforcement product for teams that need visibility into what agents do on their endpoints and control over what they can access or send. It suits security and IT teams overseeing agent use across a fleet, as well as smaller teams that want monitoring without a paid plan.

Overview

Qpoint records agent file activity, tool calls, outbound network requests and process execution, attributing events to agents and sessions. That combination is useful when teams need to investigate behavior and apply restrictions, rather than simply observe infrastructure. Policies can block secret reads, reject unapproved endpoints, redact outbound content and deny unapproved tool calls.

Its single-binary deployment runs directly on endpoints, without gateways, sidecars or SDK integration. Qpoint also supports containers, virtual machines, clusters and CI runners, making it relevant beyond employee workstations. Events can be exported to SIEM and observability systems, including Splunk, Datadog and Elastic.

Key features

• Activity attribution: Captures file, tool, network and process events with agent and session attribution, giving teams a basis for tracing behavior.
• Policy enforcement: Can prevent secret access, unapproved connections and tool calls, and redact outbound content. These controls suit teams that want to limit agent actions, not just review them afterward.
• Endpoint deployment: The single-binary approach avoids gateways, sidecars and SDK integration. Jamf and Intune are named for endpoint rollout.
• Monitoring exports: SIEM and observability exports connect Qpoint events to existing operational workflows; named integrations include Splunk, Datadog and Elastic.

Pricing

Qpoint uses a freemium model. Community costs nothing and covers up to 25 endpoints, with agent discovery and monitoring with attribution, built-in policy plugins and source enforcement, and community support. It is a practical starting point for individuals and small teams, but the endpoint ceiling makes it unsuitable for a larger fleet.

Team has custom pricing and supports up to 500 endpoints. It adds a shared team workspace, custom policy plugins, SIEM and observability export, usage and cost reports, and email and chat support. This is the more relevant tier for IT operations and security teams that need shared workflows and reporting; moving up from Community brings a higher endpoint allowance and broader operational features.

Enterprise also has custom pricing and includes unlimited endpoints, compliance reports, the ability to embed Qpoint in products, SSO and role-based access control, plus 24/7 support with onboarding. It is aimed at organizations that need scale, access controls or product embedding. Qpoint states that it has achieved SOC 2 Type II compliance.

Platforms

Qpoint supports Linux, macOS, Windows and web. Its endpoint solution names macOS, Windows and Linux, while Linux-based systems require kernel 5.10 or later and x86_64 or arm64 architecture. Kubernetes support, network visibility and application tracing are also listed, alongside a hybrid deployment model.

Who it's for

Qpoint is best suited to teams adopting AI agents that need both attributable activity records and enforceable restrictions. Community gives smaller teams a way to start within a 25-endpoint limit; Team is positioned for IT operations and security teams; Enterprise targets organizations with unlimited endpoint needs or requirements such as SSO, RBAC and compliance reports. It is less compelling for buyers seeking only general-purpose infrastructure observability without agent governance.

Pros and cons

• Pro: It combines agent activity monitoring with controls that can block or redact specific actions, supporting both investigation and prevention.
• Pro: A single-binary endpoint deployment avoids gateways, sidecars and SDK integration, and Qpoint also names containers, VMs, clusters and CI runners as environments.
• Pro: SIEM and observability export can feed existing stacks, with Splunk, Datadog and Elastic named.
• Con: Community is limited to 25 endpoints, while Team and Enterprise have custom pricing, so larger deployments require a paid-plan conversation.
• Con: Linux endpoint support has a kernel 5.10+ and architecture requirement, which narrows compatibility for older or other Linux systems.

Alternatives

eBPF Observability Tools is a useful category comparison for readers exploring the broader eBPF space.

• Kubeshark is worth considering for API-focused monitoring; its free Community plan covers up to 3 nodes or 60 pods and has unlimited API call capacity, but requires internet connectivity.
• DeepFlow may suit readers seeking a free, open-source edition for Linux servers and selected Kubernetes, cloud and container environments.
• Coroot offers a free, self-hosted Apache 2.0 Community Edition for buyers prioritizing core observability features.
• groundcover is an option for teams seeking a free-forever BYOC plan, with 12-hour data retention and Slack Community support.
• Inspektor Gadget is a free open-source tools and framework option for Linux 5.10+ systems with BTF support for project gadgets.
• Kindling suits readers who want a free product with no premium tiers, subscriptions or feature gates.
• Odigos is an alternative for teams seeking open-source core OpenTelemetry tracing and community support.
• Parca is a free option for readers looking for Apache 2-licensed profiling components.

Verdict

Choose Qpoint if your team needs to see what AI agents do and enforce limits on their access and outbound activity from the same product. Its strongest case is the combination of attributable monitoring, endpoint-level policy controls and deployment across varied environments. Look elsewhere if you need more than 25 endpoints but cannot move to custom-priced plans, or if your priority is general observability rather than agent governance.