Industrial Operator by Cleverdist
Product
  • Protect Dispatch Window
  • Recover Line Speed
  • Catch Transfer Losses
  • Keep Cranes Moving
  • Prevent HVAC Recovery
  • Clear Weak Assets
PricingQ&AAbout
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Industrial Operator

Autonomous AI for industrial operations.

Supervised or Autonomous
On top of existing systems
Built-in governance

IO in the real world

References

Supporting multi-plant combined-cycle operations with IO
Naturgy logo

Naturgy + IO

Supporting multi-plant combined-cycle operations with IO

Centralized operations across combined-cycle power plants, with IO reasoning above existing plant systems.

11combined-cycle sites
17gas turbine units
10-25%hidden capacity identified
+5-15%throughput gain potential
€1.3Min avoided investment
€700k-€1Mannual value potential
10M+I/O parameters
50+More than 50-country collaboration
AllMultilingual shifter support
70%up to 70% fewer expert escalations

Deployed in real industrial environments — not demos. Built on 10+ years of mission-critical automation expertise.

Swiss-tech
Industrial-grade engineering
Vendor-agnostic

Differentiation

We model thinking,
not tasks.

Others chain AI agents in workflows. IO captures how your experts actually reason. That's why it scales where others don't.

Others: Linear Workflow
IO: Industrial Reasoning
STEP 01STEP 02STEP 03
Read our technical approach (PDF)

Governance & Accountability

Your pace. Your policies.

Governance that scales with confidence. Some teams need human-in-the-loop today. Others are ready for delegated execution. IO supports both, with explicit policies, full audit trails, and the flexibility to evolve at your pace.

IO proposal queue — human confirms or rejects each recommendation before execution

Human in the loop

AI thinks. You decide.

Full visibility at all times. IO surfaces recommendations — every action requires a human to approve before anything happens.

Governance policy editor — browse hierarchy and set scoped policies for delegated execution

Delegated Execution

AI acts within your rules.

Delegation is explicit, scoped, and reversible. You define what IO may or may not do — and responsibility always remains human-owned.

  • AI cannot decide or act
  • Every action remains human-validated
  • Full audit trail for regulators
  • Delegation is explicit, scoped, reversible
  • Your rules define what AI may or may not do
  • Responsibility remains human-owned

Architecture

The journey with us is simple.

We model your landscape.

Messy is fine. Our onboarding tools create the context (ontology) AI needs. We work directly with you or with your trusted integrators.

Seamless integration across your ecosystem

SCADA / DCS
Historians
MES
ERP
EAM / CMMS
APM
Quality / LIMS
Planning / APS
Documents
APIs

Examples include

SiemensWinCC OAIgnitionAVEVAABB 800xADeltaVHoneywell ExperionYokogawa CENTUM VPFactoryTalkGE ProficyPI SystemSAPIBM MaximoServiceNow...and more
Download IO Secure Architecture (PDF)

Ready?

Start your pilot.

One mission. Clear success metric. Governed rollout.

Book an intro
IOby Cleverdist

Autonomous AI that operates within your governance, at any scale.

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IO Use Cases

Energy

Protect Dispatch Window

Manufacturing

Recover Line Speed

Logistics

Catch Transfer LossesKeep Cranes Moving

Mobility

Prevent HVAC RecoveryClear Weak Assets

Energy · Renewable Asset Operators

Act on renewable variability before the dispatch window closes

IO follows forecast changes, asset state, storage position, commitments and flexible assets to identify when a dispatch decision must change before the response window closes.

Relevant for renewable portfolios, IPPs and hybrid asset operators where forecast changes, storage, flexible loads and commitments must be coordinated before imbalance, curtailment or late corrective dispatch.

1-6hdispatch response window
5-15%target reduction in imbalance exposure
10-25%fewer late corrective actions
EUR 200k-1Millustrative annual value per portfolio

SEO slug: industrial-ai-agents-renewable-dispatch-window-management

Use-case summary: Protect renewable dispatch response windows before forecast variability becomes imbalance, curtailment, or late corrective action.

Use case context

The problem is not renewable variability. It is losing the option to respond.

Renewable operators already receive forecasts. The hard part is deciding what the forecast change means for dispatch, storage, flexible loads, market commitments and operating constraints while there is still time to act.

A change in wind or solar output may look manageable at first. But if the portfolio keeps following the previous plan, storage may no longer have the right state of charge, flexible loads may become impossible to shift, and dispatch or market windows may close.

By then, the operator is no longer choosing the best response. They are correcting late: accepting imbalance exposure, curtailing production, using storage inefficiently, or applying conservative buffers.

The real IO mission is to protect the response window. IO follows the expected generation story, detects when the operating plan no longer fits the forecast, and identifies the next commitment, reserve, shift or escalation before flexibility disappears.

IO models the reasoning of renewable dispatch operators: which forecast changes matter, which assets are exposed, which options are still open, which constraints block action, and when the plan should no longer be treated as normal.

Concrete trigger

A forecast change indicates lower or higher renewable output within the next dispatch window, but storage position, flexible-load schedule and commitments are still aligned with the previous plan. IO flags the exposure and proposes the next operational adjustment before the response window closes.

Pain points

What the portfolio loses when variability is acted on too late

The cost is not only imbalance. Late response reduces flexibility, forces corrective dispatch, increases curtailment risk and makes operators rely on conservative buffers instead of precise action.

Imbalance exposure

  • Forecast changes are known but not converted into dispatch action early enough.
  • Commitments remain aligned with the previous production expectation.
  • The portfolio enters the operating window with avoidable exposure.

Lost flexibility

  • Storage is not charged or reserved when it could still help.
  • Flexible loads are not shifted before their operating window closes.
  • Response options disappear before the need becomes obvious.

Curtailment and late correction

  • Operators compensate with curtailment or corrective dispatch.
  • Storage is used reactively instead of strategically.
  • Decisions are taken when fewer options remain.

Conservative operation

  • Wider buffers are kept to avoid imbalance risk.
  • Production or flexibility is underused because uncertainty is not translated into a clear action.
  • Similar forecast events create repeated manual intervention.

How IO reasons

IO models the dispatch expert who protects flexibility before it disappears

This mission is not weather forecasting. IO evaluates what a forecast change means operationally and recommends the next useful adjustment, reserve, hold or escalation before the dispatch window closes.

Builds the expected dispatch story

Compares forecast production, asset state, storage SOC, commitments, flexible loads, grid limits, prices and operating constraints.

Detects closing response windows

Identifies when the ability to charge, discharge, shift load, curtail less, renominate or update dispatch is about to disappear.

Evaluates response options

Tests storage use, flexible-load shift, dispatch update, curtailment avoidance, reserve adjustment or escalation as competing response paths.

Recommends the next commitment

Suggests what to adjust, reserve, hold, prepare or escalate based on exposure, available flexibility and remaining time.

IO governance

The user decides how much authority IO has

IO can start as a supervised dispatch advisor, then protect response windows under approved portfolio policies when forecast, commitments and flexibility diverge.

Supervised mode: IO proposes, the dispatch team confirms

  • IO identifies a forecast change likely to affect commitments, imbalance exposure, curtailment risk or asset performance.
  • IO shows which assets, storage positions, flexible loads and operating windows are affected.
  • Dispatch operators confirm the recommendation against commercial, technical, grid and contractual constraints.
  • The team updates dispatch, reserves storage, shifts flexible loads, adjusts curtailment strategy or escalates with a clear reason.

This is the natural starting point when dispatch, storage use, market exposure and contractual commitments require explicit operator validation.

Delegated mode: IO protects the response window under approved dispatch policies

  • Place an asset, site or portfolio segment into dispatch exception status.
  • Block normal-plan status when forecast, commitments and available flexibility no longer match.
  • Prepare an updated dispatch or nomination package for operator review.
  • Escalate directly to the responsible dispatch, trading or asset role when exposure crosses a defined threshold.
Flexibility protection levers
  • Reserve a minimum storage SOC band when a forecast event may require later response.
  • Trigger pre-approved flexible-load shifts within defined operating limits.
  • Hold non-critical flexible loads until renewable output or storage position is clarified.
  • Apply pre-approved storage response rules when exposure and policy thresholds are met.
  • Keep market execution, major dispatch changes and contractual deviations supervised unless explicitly authorised by portfolio policy and existing protections.

Expected benefits

Earlier dispatch decisions, lower imbalance exposure, better flexibility use

Expected value depends on portfolio size, forecast volatility, imbalance pricing, storage capacity, flexible-load availability, market rules and how much authority IO is allowed to exercise.

Lower imbalance exposure

Turn forecast changes into earlier operational decisions before deviations become costly.

Better use of flexibility

Coordinate storage, flexible loads and dispatch options before their response windows close.

Less curtailment and late correction

Reduce avoidable curtailment, reactive storage use and high-cost corrective dispatch.

More precise operating buffers

Distinguish variability that requires action from variability the portfolio can absorb.

Discuss this case

Are forecast changes closing your dispatch options before your team acts?

The first step is to frame the mission: which forecast events matter, which assets and commitments are exposed, which flexibility options exist, and which actions should remain supervised or become delegated under policy.

  • Which forecast, asset, storage, load, dispatch and market signals are already available?
  • Where do late corrections, imbalance exposure or curtailment repeatedly appear?
  • Which response windows close before the team has acted?
  • Which expert checks determine whether the right response is storage, load shift, dispatch update, curtailment reduction or escalation?
  • Which actions can IO recommend, prepare, reserve or trigger under approved operating policy?
  • Which imbalance, curtailment, flexibility-use or corrective-dispatch target would justify the first mission?

Want to map this to your renewable portfolio, commitments and dispatch policies?

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