An honest evaluation of Holistic AI, Geordie, JetStream, Capsule, and OpenBox across four criteria that determine whether governance actually reaches production systems.

The Real Question: Does Governance Reach Runtime?

The AI governance market has fragmented into two distinct product categories that do not always describe themselves honestly. The first is compliance and audit tooling. It helps organizations document AI risk, map frameworks like the EU AI Act or NIST AI RMF, and generate evidence for regulators. The second is runtime enforcement: governance that operates inside production execution paths and actually stops or approves agent actions before they complete.

Most comparison content treats these as equivalent. They are not. An organization that has mapped its AI systems to ISO 42001 but has no mechanism for blocking a misconfigured agent at execution has audited its risk, not governed it. That distinction shapes this entire evaluation.

We evaluated five platforms that have received significant attention in the enterprise AI governance space in 2025 and 2026: Holistic AI, Geordie, JetStream Security, Capsule Security, and OpenBox. We compared them across four criteria: free tier availability, runtime enforcement capability, cryptographic audit trails, and SDK setup complexity.

Note on methodology:  This comparison was produced by OpenBox. Readers should weigh OpenBox-specific claims accordingly; all competitor claims are sourced from each company's own public documentation. OpenBox feature claims in this piece are drawn directly from the OpenBox documentation at docs.openbox.ai. Competitor feature claims are drawn from each company's published product documentation, press releases, and publicly available product descriptions as of May 2026. Feature claims for platforms that launched or emerged from stealth in 2026 are based on documentation available at time of writing and are subject to rapid change. Where documentation is ambiguous or unavailable, this is stated.

The Evaluation Matrix

Free tier: Whether the platform is accessible without a sales conversation. This affects how quickly a team can evaluate it in a real environment and whether it tolerates experimentation before commitment.

Runtime enforcement: Whether the platform enforces governance decisions during agent execution, not just after the fact. This means the ability to block, halt, require approval, or allow agent actions at the point of execution based on policies and behavioral rules.

Cryptographic audit: Whether the platform produces tamper-evident records of governance events. Logs that can be modified after creation are not audit trails in any meaningful legal or compliance sense.

SDK setup: The integration surface required to connect a new agent to the platform. Lower friction means faster adoption and fewer reasons to exclude production agents from governance coverage.

Platform Profiles

Holistic AI

Full-lifecycle governance with regulatory framework coverage

• Positioning: Holistic AI is a comprehensive AI governance platform targeting organizations that need to satisfy regulatory frameworks including the EU AI Act, NIST AI RMF, ISO 42001, and NYC Local Law 144. Its governance surface spans model inventory, bias testing, compliance documentation, and a Guardian Agent architecture that operates in both monitoring and intervention modes.

• Runtime enforcement: Holistic AI describes Guardian Agents in two roles: Sentinel Agents that monitor continuously and Operative Agents that intervene when risk thresholds are crossed, including kill switches and privilege revocation.

• Audit: Holistic AI generates audit-ready evidence continuously. Public documentation does not describe cryptographic signing of individual governance events.

• Free tier: Not publicly documented. Enterprise pricing only based on scope of AI systems and governance requirements.

• Setup: Integration-focused platform. Setup complexity varies with how broadly the organization's AI estate needs to be covered.

Geordie

Agent-native security and governance with contextual controls

• Positioning: Geordie (geordie.ai) emerged from stealth in September 2025 with $6.5 million in seed funding from Ten Eleven Ventures and General Catalyst. The platform is positioned as agent-native, meaning it is designed specifically around the behavioral and risk characteristics of autonomous agents rather than retrofitted from general IT governance tooling.

• Runtime enforcement: Geordie's core enforcement mechanism is Beam, a contextual engine that applies dynamic controls based on real-time agent context. The platform emphasizes proactive mitigation before risk materializes rather than detection and response after the fact.

• Audit: Geordie describes audit-ready evidence output. Public documentation does not describe cryptographic signing or tamper-proof event records.

• Free tier: Not publicly documented. The platform claims enterprise setup in as little as ten minutes.

• Setup: Vendor-agnostic by design. Geordie claims to identify agents regardless of the underlying framework.

JetStream Security

Blueprint-based control plane with FinOps accountability

• Positioning: JetStream Security launched in March 2026 with $34 million in seed funding led by Redpoint Ventures. Founded by security operators from CrowdStrike, SentinelOne, and Cohesity, JetStream is positioned as a control plane for enterprise AI that connects visibility, identity governance, runtime control, and cost accountability in one system.

• Runtime enforcement: JetStream's AI Blueprints are dynamic, system-generated graphs that map how AI operates across the enterprise in real time, tracing agents, models, data, tools, and identities behind each action. When behavior deviates from expected patterns, the platform flags or blocks the deviation.

• Audit: JetStream describes immutable logging and non-selective observability. Public documentation does not describe cryptographic signing of individual governance event records.

• Free tier: Not publicly documented. JetStream targets enterprise security and IT leaders.

• Setup: Integrates with IdP, CI/CD pipelines, cloud platforms, and LLM providers. VPC-first deployment supported for regulated environments.

Capsule Security

Runtime security layer focused on the enforcement gap between prompt and action

• Positioning: Capsule Security emerged from stealth in April 2026 with $7 million in seed funding. Founded in Tel Aviv by Naor Paz and Lidan Hazout, Capsule is specifically designed to close what it describes as the runtime gap: the window between when an AI agent receives a prompt and when it executes an action. Capsule's focus is security-first rather than compliance-first.

• Runtime enforcement: Capsule monitors agent actions and enforces policies before those actions complete. The platform operates without requiring proxies, gateways, or additional infrastructure. Its open-source ClawGuard project adds a pre-invocation checkpoint before agent tool calls, and is designed for single-click installation.

• Audit: Capsule generates auditable telemetry. Public documentation does not describe cryptographic signing of governance event records.

• Free tier: ClawGuard is open source. The commercial platform pricing is not publicly documented.

• Setup: Capsule supports Cursor, Claude Code, Microsoft Copilot Studio, ServiceNow, and Salesforce Agentforce without SDK or proxy dependencies.

OpenBox

AI agent governance infrastructure with cryptographic audit trails

• Positioning: OpenBox is an AI agent governance platform built specifically for enterprises deploying agents in production. It wraps existing agents, including those built on Temporal, LangChain, LangGraph, Mastra, and DeepAgents, with a Trust Lifecycle: Assess, Authorize, Monitor, Verify, and Adapt.

• Trust Scores: OpenBox quantifies agent trustworthiness using a 0-100 Trust Score calculated from three components: Risk Profile Score (40% weight, based on 14 configurable risk parameters across Base Security, AI-Specific, and Impact categories), Behavioral compliance (35% weight, updated continuously based on runtime violations), and Alignment (25% weight, based on goal consistency across sessions). Source: docs.openbox.ai/core-concepts/trust-scores.

• Runtime enforcement: OpenBox issues four governance decision types at runtime: ALLOW, BLOCK, HALT, and REQUIRE_APPROVAL. Enforcement is delivered through three layered mechanisms: Guardrails (hard constraints on agent actions), Policies (OPA/Rego stateless permission checks), and Behavioral Rules (stateful multi-step pattern detection). Source: docs.openbox.ai/trust-lifecycle/authorize.

• Cryptographic audit: OpenBox cryptographically signs each session's governance events, producing a tamper-proof proof certificate. Every governance event is recorded with full context including timestamp, agent identifier, event type, verdict, reason, workflow ID, and approval metadata. Source: docs.openbox.ai/administration/compliance-and-audit.

• Free tier: Available to all organizations with no usage limits and no credit card required. Source: openbox.ai, G2 (verified May 2026).

• Setup: OpenBox provides SDKs for Temporal Python, LangChain TypeScript, LangGraph Python, Mastra TypeScript, and DeepAgents Python. Each SDK has dedicated configuration, error handling, and integration walkthrough documentation. Source: docs.openbox.ai.

Feature Comparison

The table below reflects documented capabilities as of May 2026. We mark a capability only when it is explicitly described in the vendor’s own published material. Last verified: May 2026.

Key: OSS only = open-source component available, no full commercial free tier. Partial = limited or integration-specific capability documented. All claims verified against public vendor documentation as of May 2026.

What the Matrix Actually Reveals

No one solves for cryptographic audit. Among the five platforms evaluated, only OpenBox publishes documentation describing cryptographically signed governance events producing tamper-proof proof certificates per session. This is not a minor product gap. For organizations that need defensible audit trails in regulated industries, a log that can be modified after creation does not satisfy the requirement. The other four platforms describe audit trails or immutable logging in marketing language, but none of their public documentation describes cryptographic signing of individual event records.

Runtime enforcement is table stakes now. All five platforms claim some form of runtime enforcement. This is progress from two years ago when the market was almost entirely focused on pre-deployment auditing. The meaningful differentiation is no longer whether enforcement happens at runtime but how enforcement is structured: whether it is reactive or proactive, whether it supports HITL approval workflows for sensitive decisions, and whether it is integrated into the orchestration layer or sits as an external security layer.

Orchestration SDK depth matters more than it appears. Capsule's claim of requiring no SDK is compelling for coverage of third-party agents and SaaS platforms. But for teams building custom agents on Temporal, LangGraph, or Mastra, orchestration-native integration means governance state is accessible inside the execution context, not just observable from outside it. OpenBox's documented SDK coverage across Temporal Python, LangChain TypeScript, LangGraph Python, Mastra TypeScript, and DeepAgents Python is the deepest among the five platforms evaluated.

Trust scoring is an underappreciated capability. Most platforms describe risk as binary: an action is permitted or blocked. OpenBox's Trust Score model is different in structure. It produces a continuous 0-100 score from three weighted components: risk profile at 40 percent, behavioral compliance at 35 percent, and goal alignment at 25 percent. This creates an adaptive governance system where an agent that has accumulated minor violations begins to receive more restrictive treatment automatically, and one that has demonstrated sustained compliance can recover toward higher Trust Tiers over time. No other platform in this comparison documents a comparable quantified trust evolution model.

Who Should Use What

Choose Holistic AI if:

• Your primary governance need is regulatory compliance documentation and framework mapping.

• You need pre-built controls for EU AI Act, NIST AI RMF, or ISO 42001 with automated gap analysis.

• Your AI estate spans diverse third-party models and applications, not just custom orchestrated agents.

Choose Geordie if:

• Your primary concern is behavioral observability across a mixed agent ecosystem with diverse frameworks.

• You are a security team that needs context-aware interventions rather than a compliance team mapping frameworks.

• You need fast deployment and vendor-agnostic coverage without deep SDK integration.

Choose JetStream if:

• You need governance that connects agent behavior, identity, and cost accountability in one system.

• Your organization has a CrowdStrike or SentinelOne security stack and values vendors from that ecosystem.

• Blueprint-based behavioral mapping aligns with how your organization wants to monitor, track, and audit AI workflows in real time.

Choose Capsule if:

• You need to govern third-party agent platforms like Copilot Studio, Salesforce Agentforce, or Cursor without SDK dependencies.

• Your primary threat model centers on prompt injection and tool misuse at the execution point.

• You want to pilot governance tooling with the open-source ClawGuard before committing to commercial infrastructure.

Choose OpenBox if:

• Your team is building custom agents on Temporal, LangGraph, LangChain, Mastra, or DeepAgents and needs governance embedded at the orchestration layer.

• Tamper-evident cryptographic audit trails are a requirement, not a preference.

• You need quantified trust evolution across an agent's operational lifetime, not just point-in-time policy checks.

• Human-in-the-loop approval workflows for sensitive operations are a production requirement.

The Honest Bottom Line

The AI governance market is producing genuine differentiation now, but it is not evenly distributed. The platforms that entered from a compliance or risk management background tend to be strong on framework coverage and weak on runtime verification. The platforms that entered from a cybersecurity background tend to be strong on real-time detection and intervention but thin on trust lifecycle management across an agent's operational history.

The sharpest structural difference in this comparison is between platforms that treat governance as an observability and reporting problem and platforms that treat it as an enforcement and evidence problem. Immutable logs matter. Cryptographic proof matters. Governance that cannot be verified after the fact is governance that cannot be trusted.

If you are evaluating platforms at the comparison stage, the right question to ask each vendor is not whether they have runtime enforcement. They all do, or claim to. The right questions are: Can you show me a cryptographically signed audit record from a real governance decision? Can you show me how trust state evolves across an agent's production lifetime? Can you show me what happens when a human-in-the-loop approval is required and what the evidence trail looks like after that approval is granted or denied?

Most vendors will not have complete answers to all three. That gap is where enterprise risk actually lives.