STEWARD - 2026 Pricing, Features, Reviews & Alternatives

STEWARD is a cloud-based, governed AI engine built for enterprise institutions that must explain, verify, and defend how AI is used internally. Deployed on AWS and operational in days, it functions as an application and orchestration layer over third-party AI providers, grounding every AI-generated answer exclusively in the institution's own knowledge base. Every answer carries a source citation, and every interaction is written to a permanent, auditable record. Customer data is never used to train underlying AI models, and tenant data isolation is enforced across all deployments.

Access to AI-generated answers is constrained by role-based permissions, binding each user strictly to their clearance level with no master key architecture. A single governed engine scales across multiple industry verticals through configuration alone, pointed at a new knowledge base and bound to each role's access permissions, without rebuilding the core engine. Target industries include asset and fund management, where answers are scoped to fund-specific mandates, restrictions, and reporting rules within each manager's clearance; and healthcare administration, where coverage rules, protocols, and internal policy are bound to each staff role's access level. STEWARD also serves as the governed AI engine underlying human services coordination and supply chain verification deployments, and extends to retail and financial services use cases including product catalogs, eligibility rules, rates, and advisor desk procedures.

For institutions operating under regulatory scrutiny, STEWARD provides the governance infrastructure to adopt AI at scale without unmanaged risk. Auditability, explainability, and access control are built into the architecture rather than added as afterthoughts, making AI use defensible to regulators, auditors, and internal stakeholders across every vertical it serves.