Enterprise decision-making processes are frequently fragmented across disconnected tools, informal communication channels, and manual record-keeping practices, resulting in poor traceability, inconsistent policy enforcement, and weak account-ability. This paper presents Anchora, an AI-assisted enterprise decision governance platform that integrates decision lifecycle management, evidence-grounded AI reasoning, compliance policy gating, workflow orchestration, and immutable audit logging within a unified, API-driven system. Anchora converts unstruc-tured decision requests into fully traceable, policy-evaluated, workflow-driven records. Each decision captures AI-generated reasoning summaries, risk and confidence scores, structured assumptions, policy snapshots, and references to source evidence documents. A hybrid semantic-keyword retrieval mechanism grounds AI outputs in organizational knowledge. Append-only audit logs with cross-entity trace queries enable comprehensive governance. Role-based access controls restrict decision creation, approval, and administration to authorized actors. The system is implemented using a Next.js frontend, FastAPI backend, PostgreSQL with pgvector for vector storage, and Google Gemini for generative and embedding AI. Evaluation demon-strates compliance enforcement, retrieval quality benchmarking, and operational SLO monitoring. Anchora addresses a critical gap in enterprise governance tooling by offering a reproducible, auditable, and AI-augmented decision intelligence platform.

Index Terms—decision governance, audit trail, AI reasoning, workflow orchestration, compliance enforcement, enterprise soft-ware, large language models, retrieval-augmented generation, role-based access control, policy evaluation