What are the two camps?
Inventory-first platforms begin with discovery: find every model, agent and application, register it, assess its risk and report against frameworks. On this site, Credo AI and Holistic AI fit this pattern. Credo AI adds a regulatory Knowledge Graph, forward-deployed experts and a Third-party AI Registry; Holistic AI connects to AWS, Azure and GitHub, among others, to find what is running.
Enforcement-first platforms begin with a specific system: test it, put a guardrail in front of it, log the guardrail's decisions and map the results to frameworks. Pillar Security, Alice, SPLX and Lasso fit this pattern. Alice's WonderSuite is the clearest example of the full loop for customer-facing AI: WonderBuild before launch, WonderFence at runtime and WonderCheck after launch.
How does the split show in the scores?
On our inventory criterion, the leaders are Credo AI and Holistic AI; Alice scores 2. On runtime enforcement, the leaders are Alice and Pillar Security; Credo AI scores 4 and Holistic AI 5. On third-party AI, Credo AI leads with 10; Alice scores 1.
Because our weights favor enforcement and evidence, enforcement-first platforms rank higher overall. That is a choice about what this site measures, not a claim that inventory does not matter. The readiness score lets you raise the inventory and third-party weights if your program starts there.
Which should you evaluate first?
- Start inventory-first if: you cannot yet list your AI systems; much of your AI comes from vendors; your first deliverable is a register or a framework gap analysis; legal or compliance owns the budget.
- Start enforcement-first if: you have a customer-facing assistant or agent in production or about to launch; your first risk is what it says or does; you need logged evidence of controls; security or trust and safety owns the budget.
If both lists describe you, start with the system that carries the most risk today, usually the one customers already use, and build the register around it. The register can grow one system at a time; a control in front of a live system cannot wait for it.
Can one platform do both?
Some come close. Pillar Security describes discovery, red teaming, runtime guardrails and audit-ready reports on one platform, which is why it ranks first on our weights. SPLX and Lasso both list discovery modules next to red teaming and runtime protection. If you buy one tool from each camp, make sure they share system identifiers so that register entries, controls and evidence link up.
What does each camp's control map look like?
The control maps make the split visible. For Credo AI and Holistic AI, the policy, evidence and report steps are documented and the control step is not described: neither describes how a policy acts on live traffic. For Pillar Security, Alice, SPLX and Lasso, all four steps are documented, but the policy step is narrower: it is the policy for one application or agent, not a register of every AI system in the company.
What does a combined setup look like?
A common pattern for a larger program: an inventory-first platform holds the register, the risk assessments, the third-party AI records and the framework reports; an enforcement-first platform tests each customer-facing system, runs the guardrail and produces logs and test results. The register entry for each system links to its controls and evidence in the second tool. The cost is two contracts and two sets of identifiers to keep in step; the benefit is that each tool does what its public pages describe in most detail.