hoop.dev

Hoop is an access gateway for AI agents and humans that controls reads, writes, approvals, masking, and audit trails across production systems. It helps teams let agents use sensitive infrastructure without exposing raw data or relying on separate per-protocol controls.

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What Hoop is

Hoop is an access gateway for AI agents and humans that sits in front of production systems and controls what can be read, changed, or approved. The product is positioned around extending the same governance model used for people to AI agents, so identities, scopes, and audit trails stay centralized across databases, APIs, command-line tools, and other infrastructure.

Its core job is to reduce the risk that keeps agents out of production data. Hoop does that with wire-level masking, command guardrails, session recording, approval workflows, and AI risk analysis. The pricing page shows a single-plan model that scales by identity count, covering engineers, service accounts, and AI agents, with every feature included and no tiers.

Core capabilities

One gateway across protocols

Place Hoop in front of databases, APIs, SSH, kubectl, and other systems so agents and humans use one access layer instead of separate rule sets for each protocol.

Wire-level data masking

Redact PII, PHI, credentials, and financial data in transit before the response reaches the client. The data is masked at the wire, with no schema discovery or application rewrite required.

Preventive guardrails

Block destructive or unauthorized actions such as DROP, DELETE without WHERE, rm -rf, or kubectl delete namespace before they execute. Policies can also limit scope by role, resource, or environment.

AI session analysis

Classify sessions with LLM-based risk analysis, anomaly detection, and behavior detection so unusual or risky activity is surfaced while it is happening rather than inferred later from logs.

Human-in-the-loop approvals

Require human approval for high-risk actions through Slack or Teams, while letting agents continue with allowed work. The source also supports one-action elevated access rather than long privilege windows.

Session recording and audit trails

Record sessions, log masking and blocking events, and support replayable audit trails for compliance review and forensic follow-up.

Practical use cases

Give agents controlled access to sensitive data
Use Hoop when an AI agent needs access to production data that is too sensitive to expose directly. The gateway can mask fields like PII or credentials in transit so the agent receives usable results without seeing raw values.
Prevent risky commands in production
Use Hoop to stop destructive operations before they execute in live systems. Policy rules can block commands such as DROP TABLE, DELETE without WHERE, rm -rf, or namespace deletion at the protocol layer.
Add human approval to critical actions
Use Hoop when a high-risk action should be reviewed by a human instead of blocked outright. The product can pause a command and route approval through Slack or Teams before execution continues.
Capture audit evidence from live sessions
Use Hoop when security and compliance need evidence from actual sessions rather than approximations from downstream logs. Session recording, tamper-resistant audit trails, and masking events provide a reviewable history.
Unify access control across protocols
Use Hoop to consolidate access governance for mixed environments with databases, SSH, Kubernetes, HTTP services, and AI coding tools. The gateway aims to replace separate per-protocol rule sets with one control layer.

Pros and Cons

Pros

Covers masking, guardrails, approvals, auditing, and session analysis in one gateway rather than requiring separate controls for each system.
Works across multiple protocol families, including databases, HTTP APIs, SSH, kubectl, and TCP-style access, with support for both human and machine identities.
Applies masking and blocking in transit, which lets the target action or response be governed before it reaches the client or target system.
Supports team workflows such as Slack and Teams approvals, Jira runbooks, and replayable session logs for review and compliance evidence.
The pricing page says all features are included in one plan, with no feature gating or tier fragmentation.

Cons

The source does not provide a full public integration catalog, so some environment-specific compatibility questions remain unresolved from the pages reviewed.
Setup and onboarding are described at a high level, but the source leaves out detailed implementation steps and operational effort for a typical rollout.
Pricing is described by identity count, but the pages do not publish actual prices or plan-level thresholds.

FAQ

How does Hoop work in a live session?

Hoop sits in front of the target system as a gateway. It parses commands and responses in transit, applies masking or guardrails, and logs the session outcome. For risky actions, it can route a single command for human approval through Slack or Teams.

How is Hoop set up and adopted by teams?

The source shows support for guided onboarding and training, plus a university curriculum with short modules. The pricing page also describes a clientless gateway architecture for web-based access and support for common developer tools such as psql, kubectl, ssh, and other native tools.

What environments does Hoop support?

Hoop emphasizes access governance, data masking, guardrails, AI session analysis, session recording, audit trails, and approvals. The pricing page lists supported platforms such as Kubernetes, AWS ECS, Docker, Linux VM, bare metal, and managed or self-hosted deployment options.

How is Hoop priced?

The pricing page says pricing scales with the number of identities connecting through the gateway, including engineers, service accounts, and AI agents. It also states that every feature is included with no tiers or feature gating.

What integrations are documented in the source?

The source does not show a full published integration catalog beyond items like Slack, Microsoft Teams, Jira runbooks, Google DLP, Microsoft Presidio, Splunk, syslog, and webhook export. Buyers would need to confirm any other system-specific integrations directly with Hoop.

Quick Facts

Category: Developer Tool / AI Infrastructure
Primary use: Govern access for AI agents and humans across production systems
Pricing shape: Single plan; priced by identities connecting through the gateway
Deployment: Managed or self-hosted; supports Docker, Kubernetes, AWS, Linux VM, and bare metal
Source domain: hoop.dev
Notable workflows: Data masking, guardrails, human approval, session recording, and AI risk analysis