Industrial Operator by CleverdistIndustrial Operator by Cleverdist
Product
  • Protect Dispatch Window
  • Confirm True Readiness
  • Orchestrate Flexibility
  • Recover Line Speed
  • Catch Transfer Losses
  • Keep Cranes Moving
  • Prevent HVAC Recovery
  • Clear Weak Assets
PricingQ&AAbout
info@cleverdist.com

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 WindowConfirm True ReadinessOrchestrate Flexibility

Manufacturing

Recover Line Speed

Logistics

Catch Transfer LossesKeep Cranes Moving

Mobility

Prevent HVAC RecoveryClear Weak Assets

Energy · Integrated Energy Assets

Orchestrate flexible assets before avoidable energy cost accumulates

IO coordinates batteries, controllable loads, local generation and operating constraints before peaks, imbalance exposure or underused capacity become avoidable cost.

Relevant for energy-intensive operators, IPPs and multi-asset sites where batteries, flexible loads, local generation and operating constraints must be coordinated under changing prices, demand and production conditions.

5-15%energy cost reduction
10-30%peak load reduction
10-25%flexibility utilisation improvement
EUR 200k-1Millustrative annual value per site or portfolio

Use case context

Flexibility exists, but the operating decisions are not synchronized early enough

Many energy-intensive sites and renewable portfolios already have flexibility in the form of batteries, controllable loads, local generation, process scheduling or storage.

The challenge is not simply having flexible assets. It is knowing when to use them, in what sequence, and under which technical and commercial constraints.

When flexibility is coordinated too late or locally, demand peaks remain high, storage is used suboptimally, and load-shifting opportunities are missed.

IO turns available flexibility into a mission: reason across energy, production, storage and commercial signals, then prepare the action before the response window closes.

Concrete trigger

A site is approaching a demand peak while batteries, controllable loads and local generation are available but not coordinated early enough to reduce the peak without disrupting operations.

Pain points

What it costs when flexibility is operated independently

The value is not lost because flexibility is absent. It is lost because decisions are made too locally, too late, or without a shared view of operational constraints.

Visible energy cost pressure

  • Demand peaks remain high even when flexible assets are available.
  • Storage is charged or discharged at suboptimal moments.
  • Load-shifting opportunities are missed because operating constraints are interpreted too late.

Hidden coordination loss

  • Local asset decisions conflict with site-wide energy performance.
  • Operators keep conservative buffers because they cannot see which flexibility actions are safe.
  • Energy, production, storage and commercial signals are treated separately instead of as one decision context.

Response windows close before action

  • Peak exposure is visible but not translated into a coordinated operating plan.
  • The best battery, load or generation action is identified after the value window has passed.
  • Teams diagnose the trade-off while cost is already accumulating.

How IO reasons

IO turns available flexibility into coordinated operating decisions

This mission models the expert reasoning needed to decide which flexible assets can move, when they should move, and how far they can move without breaking operational boundaries.

Maps available flexibility

IO understands which assets can move, how much flexibility they provide, and which production, comfort, asset-health or commercial constraints limit their use.

Anticipates peak and cost exposure

IO identifies when demand, prices or production conditions are likely to create avoidable cost before the response window closes.

Coordinates the response

IO recommends how batteries, controllable loads, local generation and process timing should work together rather than independently.

Keeps the decision inside governance

IO prepares flexibility options with evidence and boundaries, so operators can validate high-impact actions and delegate only the follow-through that policy allows.

IO governance

The user decides how much authority IO has

Flexibility orchestration can start as human-validated decision support, then move toward governed follow-through once operating boundaries are explicit.

Default mode: IO frames flexibility options, operators validate the action

  • Detect: IO identifies upcoming peaks, price exposure or underused flexibility windows.
  • Frame: IO explains which assets can respond, what value is at stake, and which constraints matter.
  • Validate: operators confirm feasibility against production, comfort, asset-health and commercial boundaries.
  • Act: approved storage, load-shifting, generation or scheduling adjustments are executed.

This mission should remain human-validated at first because flexibility actions can affect production, comfort, asset life, contractual commitments and commercial exposure.

Delegated mode: IO follows approved flexibility rules and boundaries

  • Recommend battery charging or discharging ahead of expected peaks.
  • Suggest controllable-load shifts within approved operating windows.
  • Coordinate local generation, storage and load actions against price and demand signals.
  • Trigger alerts when peak exposure or flexibility underuse exceeds approved thresholds.
Governed follow-through
  • Prepare approved action plans while keeping execution inside governance limits.
  • Track whether flexibility actions reduced cost without disrupting operations.
  • Respect operational continuity, asset constraints and commercial commitments.
  • Keep actions that affect production or contractual exposure explicitly operator-approved unless policy authorises delegation.

Expected benefits

Lower energy cost from better-timed flexible actions

The expected value depends on available flexible assets, tariff or market exposure, production constraints, and how much follow-through the operator is ready to delegate.

Lower peak costs

Reduce demand peaks by coordinating flexible assets before the response window closes.

Better asset utilisation

Use batteries, flexible loads and local generation when they create the most operational and economic value.

Clearer operator trade-offs

Show which flexibility actions are safe, valuable and time-critical before operators approve them.

Discuss this case

Do you have flexibility, or are you actually orchestrating it?

This mission is relevant when flexible assets exist, but energy, production, storage and commercial decisions are still coordinated too late or too locally to capture their full value.

  • Which batteries, controllable loads, local generation and process schedules can actually move without disrupting operations?
  • Where do peaks, price exposure or underused flexibility create avoidable cost?
  • Which operating constraints decide whether a flexibility action is safe?
  • Which flexibility actions must remain explicitly operator-approved?
  • Which alerts, plans or follow-up actions could IO prepare under approved rules?
  • Which peak-cost, energy-cost or flexibility-utilisation target would justify the first mission?

Want to map your flexible assets, constraints and value windows?

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