Docksmith

Regulated Water Operations Engine

A centralized system for managing regulated water assets and locations, enforcing compliance workflows, and producing audit-ready records on demand.

Outcomes
Audit-ready recordsZero missed deadlinesHigh data confidenceCross-site visibility
Capabilities
State-driven workflowsApproval gatesRole-based accessAudit loggingImmutable recordsInvalid-state prevention
Compliance management architecture
The Problem

Asset lifecycle tracking ran on disconnected spreadsheets across multiple locations. No centralized state management existed. Teams manually coordinated deadlines through email, leading to missed requirements and data fragmentation.

When operational reviews occurred, teams reconstructed timelines from scattered records with no reliable audit trail. Historical changes were untraceable.

The System
  • Centralized asset database with state machine architecture for lifecycle progression
  • State transitions blocked until required documentation and approvals are recorded
  • Immutable modification log—historical records cannot be deleted or altered after creation
  • All state changes, document uploads, and approvals logged with user attribution and timestamp
  • Lifecycle validation enforced at database level preventing invalid state combinations
  • Automated deadline monitoring with scheduled workflow scanning for approaching requirements
  • Notification engine triggering alerts before deadlines escalate to operational issues
  • Role-based state transition permissions requiring specific authorization for progression
  • Multi-location asset visibility with permission-controlled access to sensitive records
Why It Worked

The architecture treats historical data as immutable. Users append new state transitions and documentation but cannot modify or delete past records. This creates an unbroken audit chain from acquisition through disposal.

State transitions are validated against lifecycle rules encoded in the database schema. Assets cannot skip required steps or enter invalid states—progression is blocked at the data layer.

Deadline monitoring runs on scheduled backend workflows rather than user discipline. The system scans for approaching requirements and triggers notifications automatically, eliminating the manual tracking overhead that previously caused missed deadlines.