About Keystone Applied Intelligence

Keystone is governed AI infrastructure that regulated enterprises can actually deploy. It is three extensions running on one shared substrate, with governance, authorization, and evaluation designed in from the first commit rather than bolted on afterward.

The distinction is deliberate. Most LLM-era systems treat governance as a wrapper: a content filter in front of a model, an audit log written after the fact, an access-control check bolted onto retrieval once the product already works. Keystone inverts that. Authorization fails closed at the database layer, tool scopes are enforced before dispatch, irreversible actions gate on human approval, and every action lands in a hash-chained, tamper-evident audit record. The controls are structural, not advisory — which is the precondition for a bank, an insurer, or a legal team to put the system in front of real users and real regulators.

The operational rigor is not new. It is the discipline the contact-center industry already built for compliance reasons over the pre-LLM decades of conversational AI, rebuilt here for the LLM substrate. See the contact-center heritage for the pattern-by-pattern mapping.

How to navigate these docs

Start with Architecture for the layered model and the shared substrate that every extension plugs into. Extensions covers the three capabilities built on that substrate — keystone-engage (governed conversational agent), keystone-counsel (authorization-first retrieval), and keystone-verify (the standalone evaluation harness). Evaluation explains the methodology and the published baselines, including failing runs sealed alongside passing ones. Design traces where the governance decisions come from. Access states plainly what is public, what is proprietary, and how to request read-only repository access for technical review.

Where to go next

For the employer-facing platform narrative and a walkthrough of the extensions in context, see the platform demo at getkeystone.ai/platform/.

Keystone is independent engineering, not a company pitch. For technical review, hiring conversations, or a deeper look at the private implementation, reach the builder at arnaldosepulveda.com or on LinkedIn.