Credo AI governs AI built and run elsewhere. Brine is where the agents actually run, with identity, approval gates, and cost attribution enforced in the execution path. Here is how they compare, and a Credo flagship workflow rebuilt on Brine.
Both give a regulated organization an auditable account of its AI, and both speak EU AI Act, NIST AI RMF, and ISO 42001. The difference is whether the platform reports on the work orruns it.
Credo discovers, inventories, scores, and reports on AI across the entire enterprise, including systems it didn’t build and doesn’t run. The buyer is a governance lead, CDO, or legal/compliance function at a large enterprise or Fortune 500, and the program is fed by data-science and developer teams. It governs the AI you have, wherever it lives.
Brine is built for regulated organizations. You describe a workflow in plain English; Brine assembles governed agents, runs them inside your tenant, and writes a signed, costed record of every action. Governance isn’t a layer beside the work, it’s enforced in the execution path, before each step runs.
Credo leads on enterprise breadth and holds attestations Brine doesn’t yet. Brine leads in the execution path. Both are marked honestly below.
Credo is enterprise-only and sales-led, with no public pricing and no per-action cost signal. Brine publishes its tiers and shows projected-vs-actual on every run.
Credo’s most-marketed workflow is an EU AI Act conformity assessment for a high-risk use case, discover and register the system, assess it against a policy pack, then monitor and report. On Brine you describe the goal once, then watch it parse, run, and account for itself, governed, gated, and costed, inside your tenant.
These often sit side by side rather than head to head. Here is when each is the right call, including when it isn’t us.
More complementary than competitive. Many teams keep Credo as the enterprise-wide AI inventory and reporting layer, and run new agent workloads on Brine, then register the Brine-run agents back into Credo’s registry so the central governance office still sees them. It isn’t a rip-and-replace.
Credo already governs all our AI, including what we didn’t build.
True, and that’s a different layer. Credo watches systems that run elsewhere; Brine runs the agent workforce inside your tenant and enforces scope before each action. Plenty of teams run both: Credo as the enterprise inventory, Brine where the work actually executes.
Credo has SOC 2 Type II; you don’t yet.
Correct, and we won’t pretend otherwise, our SOC 2 Type I target is August 2026, Type II in Q1 2027. What’s technically enforced today is the immutable SHA-256 audit trail, cryptographic agent identity, platform-level scope, tenant isolation, and BYOK. Pre-certification pilots run on non-regulated data.
Credo enforces our policies at runtime.
Credo’s runtime layer ingests traces, evaluates them, and escalates to a human; hard enforcement via CI/CD and API gateways is listed as planned on their own product page. Brine enforces scope and a pre-dispatch spending cap before a step runs, in the execution path.
We can’t tell what our AI is costing us.
That’s the gap a governance suite doesn’t fill, it governs risk and compliance, not spend. Brine costs every action and attributes it to agent, model, and step in the same signed record, with a budget cap that holds steps before they overspend.
Credo is the recognized category leader.
Fairly so, for enterprise AI governance documentation. We’re not competing to be a better document-and-score layer, we run the work and govern it by default in your tenant, at a predictable, published price.
Pick one AI workflow your team needs to govern. Brine builds it from a plain-English description, runs it inside your tenant with identity, gates, a signed trail, and per-action cost, and you measure it against documenting it elsewhere. Minutes, not months.