Foundation, Operator, and Enterprise. Every tier runs the same core processing engine. Tiers differ in deployment scale, sector coverage, integration depth, and governance infrastructure.
Core platform deployment with a single sector module. Designed for organizations entering governed AI decision-making for the first time.
Multi-sector deployment with advanced integration. Designed for organizations operating across multiple regulated environments with existing data infrastructure.
Full platform deployment with quantum execution path, unlimited sector modules, and dedicated governance infrastructure. Designed for organizations where decision auditability is a regulatory requirement.
Every engagement follows a five-phase deployment methodology designed to minimize integration risk and maximize time-to-value.
Assess existing infrastructure, data sources, compliance requirements, and decision workflows. Produce a deployment architecture document.
Connect institutional data sources, configure retrieval parameters, and validate evidence quality against the governance framework.
Deploy and calibrate sector-specific modules with domain ontologies, regulatory mappings, and sector-specific quality thresholds.
Integrate with existing workflows, run parallel processing against historical decisions, and validate output quality against institutional standards.
Move to production with monitoring, establish calibration cadence, and configure board-level reporting integration.
The first step in every engagement is an architecture review: an assessment of your existing infrastructure, decision workflows, and compliance requirements against the platform's deployment architecture. Complete the form below and our team will respond within two business days.
Explore the platform architecture, review sector deployment contexts, or scroll up to submit your architecture review request directly.
