AquaTwinXMember Portal

ONE WATER SOLUTIONS

From Fragmented Systems
to Coordinated Decisions.

AquaTwinX connects engineering models, utility knowledge, asset intelligence, operations, and capital strategy across drinking water, wastewater, stormwater, and water reuse.
Fragmented utility maps, sensors, models, documents, and work records converge into a connected One Water intelligence layer supporting operations, capital projects, and risk-informed maintenance
01ONE WATER SYSTEM INTELLIGENCE

Digital Twins

Connect drinking-water, wastewater, stormwater, and water-reuse assets, telemetry, operating rules, and engineering models within a living system representation.

The Utility Challenge

Facilities and networks are commonly managed through separate GIS, SCADA, work-management, laboratory, and modeling environments. This limits visibility into how treatment, pumping, storage, collection, detention, control, and reuse decisions interact across the urban water cycle.

AquaTwinX Approach

AquaTwinX organizes approved sources around shared facility, network, and watershed context. The twin supports historical reconstruction, current-condition awareness, and future scenario evaluation while authoritative systems, engineering validation, and operational approval remain intact.

Principal Capabilities

  • Drinking-water, wastewater, stormwater, and reuse integration
  • Treatment, pump, storage, basin, gate, and network interactions
  • Historical reconstruction and current system visibility
  • Hydraulic, hydrologic, operational, and investment scenarios
Discuss Digital Twins
Digital Twin Platform connecting historical events, current utility performance, and future demand, risk, and investment forecasting
EXPECTED DECISION VALUE
01Coordinated system awareness
02Safer scenario evaluation
03Earlier recognition of cross-system risk
02GOVERNED UTILITY KNOWLEDGE

KnowledgeGPT

Provide rapid, traceable answers grounded in approved utility standards, plans, reports, procedures, regulations, and engineering records.

The Utility Challenge

Critical engineering knowledge is dispersed across extensive document collections and often depends on a small number of experienced staff. Conventional search returns files; it does not reliably synthesize applicable requirements or explain their context.

AquaTwinX Approach

KnowledgeGPT retrieves relevant passages from governed sources, distinguishes authoritative requirements from supporting guidance, and presents concise responses with citations. Review controls and source ownership preserve professional accountability.

Principal Capabilities

  • Permission-aware retrieval from approved technical sources
  • Traceable answers with document and section citations
  • Comparison of standards, alternatives, and historical assumptions
  • Knowledge-gap identification and controlled content review
Discuss KnowledgeGPT
KnowledgeGPT workflow connecting governed utility standards, plans, and procedures to grounded retrieval and cited technical guidance
EXPECTED DECISION VALUE
01Reduced research time
02Improved institutional continuity
03More consistent technical interpretation
03RISK-INFORMED CAPITAL STRATEGY

Smart CIP

Translate asset risk, system performance, resilience, equity, cost, and implementation constraints into a transparent capital improvement program.

The Utility Challenge

Capital programs are often assembled from disconnected needs lists, localized complaints, model results, and expert judgment. Without a common decision structure, priorities can be difficult to defend and update.

AquaTwinX Approach

Smart CIP combines likelihood of failure, consequence, hydraulic deficiency, regulatory need, community impact, cost, and project readiness. Scenario controls show how priorities change under alternative budgets and policy objectives.

Principal Capabilities

  • Multi-criteria risk and consequence scoring
  • Project bundling, dependency, and readiness assessment
  • Budget-constrained portfolio optimization
  • Scenario comparison and transparent priority rationale
Discuss Smart CIP
EXPECTED DECISION VALUE
01Defensible investment priorities
02Greater value per capital dollar
03Clearer executive and public communication
04ENGINEERING ANALYSIS IN PLAIN LANGUAGE

Prompt Modeling

Convert structured natural-language requests into repeatable hydraulic, spatial, and asset analyses while retaining engineering governance.

The Utility Challenge

Hydraulic and geospatial models contain substantial decision value, but specialist availability and software complexity can delay routine operational and planning questions.

AquaTwinX Approach

Users describe the required analysis—such as valve isolation, customer impacts, fire flow, pressure, or demand scenarios. AquaTwinX translates the request into controlled model operations, validates required inputs, and returns mapped results with assumptions and limitations.

Principal Capabilities

  • Valve-isolation and affected-customer analysis
  • Fire-flow, pressure, demand, and outage scenarios
  • Automated model input validation and result summarization
  • Reproducible analysis records for professional review
Discuss Prompt Modeling
A water utility field technician asks which valves isolate a main and receives an AI-assisted network-model recommendation
EXPECTED DECISION VALUE
01Shorter analysis turnaround
02Broader access to model intelligence
03Protected engineering quality control
05PREDICTIVE AND PRESCRIPTIVE ASSET INTELLIGENCE

AI-Driven Asset Management

Forecast condition and failure risk for horizontal networks and vertical facilities, then identify the most appropriate intervention and timing.

The Utility Challenge

Age-based replacement programs do not adequately represent actual deterioration, operating stress, environmental exposure, failure history, consequence, or maintenance effectiveness.

AquaTwinX Approach

AquaTwinX integrates condition, inspection, work-order, material, environmental, operational, and consequence data. Predictive models estimate risk; prescriptive logic evaluates inspection, maintenance, rehabilitation, and replacement alternatives.

Principal Capabilities

  • Horizontal assets: mains, sewers, force mains, and appurtenances
  • Vertical assets: pumps, motors, treatment units, electrical and structural systems
  • Condition, failure-probability, remaining-life, and consequence models
  • Risk-based inspection and intervention recommendations
Discuss AI-Driven Asset Management
AI-driven asset management predicts deterioration in a horizontal water main and prescribes intervention for a vertical pump and motor asset
EXPECTED DECISION VALUE
01Fewer avoidable failures
02Targeted maintenance expenditure
03Improved lifecycle planning
06A LIVING INFRASTRUCTURE STRATEGY

Dynamic Master Planning

Continuously update system needs, scenarios, projects, priorities, and investment strategies as growth, climate, assets, operations, and funding conditions change.

The Utility Challenge

A conventional master plan is a periodic snapshot. Its assumptions, projects, and priorities may become outdated well before the next planning cycle, weakening its value for annual capital and operational decisions.

AquaTwinX Approach

Dynamic Master Planning connects demand, hydraulic performance, asset risk, resilience, development, projects, cost, and policy objectives in an updateable decision environment. Changes are evaluated without rebuilding the planning process from the beginning.

Principal Capabilities

  • Living demand, supply, capacity, and risk baselines
  • Growth, drought, outage, climate, and investment scenarios
  • Continuous project need, timing, and dependency evaluation
  • Alignment of master planning, CIP, operations, and performance reporting
Discuss Dynamic Master Planning
Dynamic Master Planning connects a complete water utility system to an Observe, Test, and Adapt cycle across today, 2035, and 2050 planning horizons
EXPECTED DECISION VALUE
01Plans that remain decision-relevant
02Earlier adaptation to changing conditions
03Continuous alignment between strategy and delivery
07GOVERNED AUTONOMOUS UTILITY WORKFLOWS

AI Agents

Coordinate specialized AI agents that monitor information, validate evidence, execute bounded technical tasks, and prepare traceable recommendations for professional review.

The Utility Challenge

Utility decisions often require repetitive coordination across data quality, hydraulic models, technical documents, operational signals, work history, and planning scenarios. Manual handoffs delay analysis, while unconstrained automation introduces unacceptable technical and governance risk.

AquaTwinX Approach

AquaTwinX assigns clearly defined responsibilities to specialized agents operating within approved data, tools, permissions, and decision thresholds. An orchestration layer coordinates their work, records the evidence and assumptions used, and routes consequential recommendations through engineering or operational review before action.

Principal Capabilities

  • Data QA/QC, reconciliation, and exception identification
  • Hydraulic-model calibration, validation, and controlled scenario execution
  • Governed knowledge retrieval with source-grounded technical synthesis
  • Anomaly monitoring, planning analysis, and human-review escalation
Discuss AI Agents
Governed AI agents coordinate water-utility data quality, model validation, knowledge retrieval, operational monitoring, and planning analysis through a professional-review gate
EXPECTED DECISION VALUE
01Reduced repetitive technical effort
02Faster cross-system analysis
03Accountable AI-assisted decisions
IMPLEMENTATION MODEL

Begin With a Decision.
Build the Required Intelligence.

AquaTwinX solutions can be introduced independently and connected progressively. Implementation begins with a defined utility decision, uses the systems and data already available, and expands only where additional capability creates measurable value.

  1. 01Define

    Establish the decision, users, evidence, and performance objective.

  2. 02Connect

    Organize authoritative data, models, documents, and workflows.

  3. 03Demonstrate

    Deliver a focused use case with transparent assumptions and validation.

  4. 04Scale

    Extend the operating model through governance, training, and measured adoption.

BUILD THE NEXT ONE WATER DECISION CAPABILITY

Start With the Problem Your Utility Needs to Solve.

Define a focused utility decision, identify its evidence and governance requirements, and demonstrate measurable value before scaling.

Schedule a strategy discussion ↗