Capability inside your environment. Not access to someone else's.
Most AI tools deliver capability through a third-party API. Your data leaves your environment, is processed on overseas servers, and returns with no audit trail you control. For an organisation handling regulated data, that is an unauthorised disclosure waiting to be found.
BlackVault™ inverts the model. We deploy verified open-source large language models inside your own AWS, Azure, GCP, private cloud, or on-premise environment. The model runs where your data lives. Nothing is sent out. Nothing is shared. Every inference is logged, retained, and auditable.
And it does not stand still. We fine-tune the model continuously against your proprietary systems and data, and operate the environment — architecture, security, and monitoring — for as long as you run it. The capability stays current, and stays inside your boundary, permanently.
One architecture, layered from the infrastructure up.
Your environment, locked down
Your own environment — AWS, Azure, GCP, private cloud, or on-premise — region-locked by policy, network-isolated with no outbound path at inference, AES-256 at rest and TLS 1.3 in transit. The verified open-source model runs here, where your data lives.
Twelve documents, kept alive
Twelve version-controlled governance documents — the evidence a regulator asks for, prepared before they ask and kept current by the managed service, not filed away after go-live.
Matched to your regulator
The regulatory obligations specific to your sector — one module matched to your regulator, layered on top of the baseline framework.
Every claim is verifiable.
The controls below are implemented, documented, and maintained on every deployment — for the life of the engagement, not a roadmap.