The short answer
Holistic AI and Credo AI are both AI governance platforms aimed at the same buyer: a risk, compliance, or responsible-AI team that needs to inventory models, run risk assessments, and produce evidence for regulators. Holistic AI leans toward technical risk testing and model assessment, including bias and robustness checks. Credo AI leans toward policy-to-control mapping and governance workflow, translating frameworks like the EU AI Act and NIST AI RMF into review processes. Both are governance-of-record systems. Neither sits in the live path between a user and a model, which is where runtime data control happens.
Where each one is strong
Holistic AI is a good fit when the priority is assessing models themselves: testing for bias, measuring robustness, scoring risk on a model-by-model basis, and documenting that testing for an audit. Credo AI is a good fit when the priority is the governance process: registering AI use cases, mapping them to regulatory requirements, routing them through review and sign-off, and generating policy-aligned reports. A team buying for board-level oversight and regulatory mapping often leans Credo AI. A team buying for model risk and technical assurance often leans Holistic AI.
What both leave open
Both platforms govern AI as a register: a catalogue of systems, assessments, and approvals reviewed on a cycle. That is necessary work. It is also retrospective. When an employee pastes a customer record into a chat tool, or an agent calls a model with a live credential in the prompt, neither platform is on that path to redact, enforce, or log it as it happens. The assessment said the system was acceptable. It cannot see what flows through the system minute to minute. Governance of record and governance at runtime are different jobs, and most regulated teams need both.
Where runtime governance fits
Runtime governance sits in front of the model, on every prompt. It redacts personal data and secrets before they reach the model, enforces policy in real time so a blocked category never leaves the boundary, routes to an approved model, and logs every interaction for audit. Difinity provides this layer. Secure Chat gives a team one governed AI tool they adopt in minutes, with redaction, real-time enforcement, a cost and behavior dashboard, and full observability. It complements a register-style platform rather than replacing it: the register documents what is approved, the gateway enforces it on live traffic.
Frequently asked questions
Is Holistic AI or Credo AI better?
Neither is universally better. Holistic AI is stronger for technical model risk and assessment. Credo AI is stronger for regulatory mapping and governance workflow. Pick by which job is your bigger gap, and check whether you also need runtime control, which both leave open.
Do Holistic AI and Credo AI enforce policy in real time?
Not on live prompts. Both operate as governance-of-record platforms: inventory, assessment, and approval. Real-time redaction and enforcement on each prompt require a gateway in the path between the user and the model.
Can you use a governance platform and a runtime gateway together?
Yes, and many teams do. The register documents approved AI use and assessments. The gateway enforces policy on live traffic and produces the per-prompt audit trail. They cover different parts of the same obligation.