AI governance infrastructure for the enterprise
Don't waste cycles configuring your own
Production-grade permissioned networks with compliance controls enforced at deploy—managed for you so your team ships product, not infrastructure runbooks.
30-minute call · No commitment · Bring your compliance framework list
Regulators and boards are asking for evidence tied to systems, not narratives. These are the pressure points we see when infrastructure was not designed for inspection.
Hundreds of verified AI agent incidents in production show the gap between logs and proof. The EU AI Act ’s high-risk obligations require technical measures that let you demonstrate what the model did, when, and with what inputs—not a slide deck after the fact.
The GENIUS Act and parallel reporting regimes expect recurring attestations and controls you can inspect, not narrative assurance. Teams still treating compliance as a post-launch documentation exercise carry remediation cost that compounds every quarter.
MiCA , digital asset reporting, and AI governance timelines now land in the same planning horizon as your product roadmap. Waiting for a “phase two” infrastructure pass means betting the business on catch-up projects while regulators publish concrete expectations.
Each item below is something we put in writing, in architecture, and in operations. Expand any card for the technical specifics a solutions architect or security lead will ask for.
A defined pilot → build → validate → deploy sequence with named milestones. Most enterprise teams measure blockchain programs in quarters; we measure them in weeks with acceptance criteria you can show a CFO.
Identity, channel policy, and endorsement rules are part of the topology from the first channel. Auditors inspect live configuration and chaincode policy—not a PDF that claims parity with production.
Patching, availability, and compliance-adjacent operations sit with BlockSkunk. Your internal team integrates at the API and governance boundary instead of owning Fabric expertise headcount.
Decision payloads, model identifiers, input fingerprints, and timestamps can be anchored to transactions your security team already knows how to retain and produce under subpoena or audit.
Organizations, MSPs, and channel membership are explicit in configuration. That is the difference between a shared database and a consortium where competitors can coexist with cryptographic separation.
Query interfaces and read-only views expose transaction history, configuration history, and chaincode version lineage. The goal is independent verification, not a black-box managed service story.
30-minute call · We'll map your framework gaps
For solutions architects, security engineers, and auditors who need to understand how evidence is produced—not how it is described in marketing.
| Attribute | Specification |
|---|---|
| Network type | Hyperledger Fabric 2.5+ permissioned network |
| Consensus | Raft ordering service |
| Throughput (typical) | On the order of 3,000–20,000 TPS depending on chaincode, endorsement policy, and hardware (non-benchmark) |
| Deployment options | Customer cloud, BlockSkunk-managed VPC, or hybrid connectivity per contract |
| Chaincode language | Go (default), Node.js where required by integration |
| Certificate authority | Fabric CA or customer PKI integration with documented enrollment flows |
A short call surfaces whether your current stack can produce the evidence regulators and auditors now expect—or where the gaps are before they become findings.
30-minute call · No commitment · Bring your framework list