WAsP Interop Hub

Enables standardized interoperability for WAsP ecosystem input and output files, reducing integration friction across wind assessment software, tools, and custom workflows.

The Problem

Standardize WAsP file interoperability across wind assessment tools and workflows

Organizations face these key challenges:

1

Multiple WAsP-related file types with inconsistent structures and versions

2

Custom scripts that break when upstream or downstream tools change

3

Manual metadata cleanup and field mapping between systems

4

Late discovery of invalid or incomplete files during project execution

Impact When Solved

Reduce manual file conversion effort for wind assessment teamsShorten integration time for new software tools and partner workflowsImprove consistency and validation of WAsP ecosystem inputs and outputsLower support burden caused by schema mismatches and version drift

The Shift

Before AI~85% Manual

Human Does

  • Collect WAsP-related files from partners, tools, and internal workflows
  • Manually identify file types, versions, and required metadata
  • Convert and map fields between formats using scripts, spreadsheets, or custom parsers
  • Review validation issues late in the process and correct incomplete or inconsistent files

Automation

  • No AI-driven interoperability support is used
  • No automated file classification or schema inference is available
  • No AI-generated remediation guidance is provided
  • No proactive monitoring of version drift or recurring conversion failures occurs
With AI~75% Automated

Human Does

  • Approve canonical mappings, validation policies, and interoperability rules
  • Review and resolve exceptions for ambiguous files or non-standard variants
  • Decide how to handle high-impact validation failures and partner-specific requirements

AI Handles

  • Classify incoming WAsP ecosystem files by type, version, and likely variant
  • Validate structure, metadata, and semantic consistency against known rules
  • Recommend or execute standardized transformations into approved formats or canonical representations
  • Route files through the correct workflow and summarize failures with next-step guidance

Operating Intelligence

How it works

AI runs the operating engine in real time.

Humans govern policy and overrides.

Measured outcomes feed the optimization loop.

Confidence88%
ArchetypeOptimize & Orchestrate
Shape6-step circular
Human gates1
Autonomy
67%AI controls 4 of 6 steps

Who is in control at each step

Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

Loop shapecircular

Step 1

Sense

Step 2

Optimize

Step 3

Coordinate

Step 4

Govern

Step 5

Execute

Step 6

Measure

AI lead

Autonomous execution

1AI
2AI
3AI
5AI
gate

Human lead

Approval, override, feedback

4Human
6 Loop
AI-led step
Human-controlled step
Feedback loop
TL;DR

AI senses, optimizes, and coordinates in real time. Humans set policy and override when needed. Measurements close the loop.

The Loop

6 steps

1 operating angles mapped

Operational Depth

Free access to this report