HFS

Hybrid Flow System

Compose triggers, data processing, model recommendations, human approval and governed actions into an inspectable operational workflow.

HFS — Hybrid Flow System

The problem

Automation often remains scattered across scripts, schedules and personal judgment. When AI is added without state, permissions and evidence, operational risk grows.

The outcome

Preserve every input, decision, approval, execution and outcome in a node-based workflow so the capability can be repeated and improved.

Hybrid workflow graphic for data, AI, human approval and governed action

Operational context

Make data, models, approvals and controls one inspectable flow.

HFS keeps triggers, evidence, rules, AI options, human approval, controlled execution and outcome learning in one workflow.

  1. 01
    Visual workflowsExpress triggers, conditions, data, algorithms, human approval and outputs through nodes and connections.
  2. 02
    Built-in anomaly detectionEmbed statistical or algorithmic nodes while preserving provenance and downstream handling boundaries.
  3. 03
    Isolated C# scriptingAllow constrained extension while governing execution time, resources, dependencies and callable scope.

Core capabilities

From product module to reusable operational capability.

The codebase includes a workflow engine, anomaly detectors and a script host. The visual designer, node catalog and production isolation must be verified against the released version.

01

Visual workflows

Express triggers, conditions, data, algorithms, human approval and outputs through nodes and connections.

02

Built-in anomaly detection

Embed statistical or algorithmic nodes while preserving provenance and downstream handling boundaries.

03

Isolated C# scripting

Allow constrained extension while governing execution time, resources, dependencies and callable scope.

04

Governed actions

Add allowlists, simulation, dual approval, timeout, recovery and complete records to high-risk actions.

Data and responsibility flow

Every step stays visible, verifiable and governable.

  1. 01Start from an event, schedule or person
  2. 02Collect real-time and historical evidence
  3. 03Use rules, algorithms or AI to form options
  4. 04Execute after human approval and collect the outcome

Use cases

Start with one high-value loop.

  • Anomaly classification and assignment
  • Energy strategy recommendation and approval
  • Quality-event handling
  • Operational orchestration across OT and IT

Responsibility boundary

HFS must not bypass existing control responsibility. Every external write and AI recommendation must distinguish recommendation, approval, dispatch, execution and outcome.

Current technical baseline: The codebase includes a workflow engine, anomaly detectors and a script host. The visual designer, node catalog and production isolation must be verified against the released version.

X·Neurons / HFS

Connect field data to verifiable decisions and actions.

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