Luma Process Intelligence

Multivariate transmitter data, read like an operator would.

Luma analyzes multivariate transmitter data for plant operators and engineers to detect early deviations and prevent quality, energy, and downtime losses.

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StatusFindingRecommendationImpact

WARNING
TT-401
CW supply +1.4 °C above 14d baseline; co-trends with all E-1xx hot-side outlets
Engage cooling-tower service; check basin makeup, fan pitch, fill condition.
€680/day
WARNING
TT-104
C-104 discharge T drift +1.8 °C / 96h while suction T flat — early valve flutter
Schedule valve-plate borescope on C-104; pre-stage valve kit.
€340/day
WARNING
PT-201
R-201 pressure +0.3 bara / 3d at constant feed — pressure-drop creep across catalyst bed
Run wash-cycle if procedure permits; verify XV-210 quench actuation chain.
€340/day
WARNING
TT-202
TT-202 noise band +180% post 2026-04-29 — channeling/maldistribution emerging in bed
Plan controlled-shutdown wash; book bed inspection in next 14d window.
€420/day
WARNING
TT-304
T-303 high-T trending toward H — composition shift; H₂O fraction up on feed
Sample T-302 bottoms and T-303 feed; verify V-301 level loop.
€310/day
WATCH
TT-203
E-201 hot-side outlet drift +1.1 °C/week with CW return flat — process-side fouling
Schedule E-201 process-side hydroblast at next 12d window.
€175/day
WATCH
TT-301 / TT-303
T-302 top-bottom dT widening +1.2 °C/week — early efficiency creep on column
Check reflux ratio against design; gamma-scan trays at next outage.
€220/day
NORMAL
PT-100
N₂ feed pressure stable within band — no anomaly across 14d window
No action required.
—

5 WARNING · 2 WATCH · 1 NORMAL

€18.900 avoided / mo·early-detection model

How Luma Works

From raw transmitter data to actionable reports in three steps.

Input

Step 01 — Data Collection

Read-only access to selected transmitters plus context (limits, units, setpoints).

Insight

Step 02 — Analysis

Detect subtle drifts and anomalies; cross-check process vs. mechanical context; estimate potential cost exposure.

Delivery

Step 03 — Reporting

Hourly/daily/weekly/monthly digests with findings, likely root causes, mitigation ideas, and cost estimates.

Want to see it run right now?

Open the interactive demo. Luma running on a sample multivariate signal stream, no signup, no install.

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Core Capabilities

Three pillars that turn raw transmitter data into prioritized, cost-aware actions.

Connect the Signals

Signal Correlation

See the connections, find it early

Correlate process, equipment, and energy signals to reveal true drivers. Detect subtle drift in time to prevent waste, downtime, and off-spec.

Know why & what to do

Rank likely causes with confidence and give the next best actions.

Understand the Financial Impact

Cost Intelligence

Calculate cost of drift

Quantify current losses from deviations across energy, yield, and quality — and forecast what it costs if the drift persists.

Track the recovery

Attribute savings to interventions. Before/after trends for each fix.

Harness a Living Memory

Adaptive Learning

Incident correlation

Match current behavior to past events to surface recurring root causes.

Adaptive learning

Use what worked before to sharpen future recommendations automatically. Searchable record of issues, actions, and outcomes.

One Platform, Every Role

All working simultaneously. One Luma, multiple perspectives.

Drift Detected

12:34 UTC

Reactor Temperature (TT-1201)

Current: 187.5°C · Baseline: 185.4°C · Δ +2.1°C

Likely cause: Steam valve CV-301 position drift

Suggested action: Verify CV-301 positioner feedback

Est. impact: €1,200/day if unaddressed

Where Luma operates

The Quiet Zone

Normal Operations

The Quiet Zone

Critical Failure

Luma detects

Traditional alarm

Not Alarming Doesn’t Equal Safe

Luma reveals process drift well before traditional protections step in.

Every Hour Without Luma Can Cost You

Lower yield, excess energy usage, out-of-spec products, and increased equipment stress impact your bottom line every hour.

Luma spots subtle warning signs between “everything’s normal” and “critical failure,” enabling fast, high-value corrective actions.

ROI Estimate

Estimated Drift-Cost Avoidance

Based on earlier detection of process deviations: deviations per month × days saved per deviation × average cost exposure per day.

Your Inputs

Monitored signals

20 signals

Deviations caught per month

3 /month

Avg. cost exposure per deviation

1400 €/day

Days to detect (traditional)

5 days

Days to detect (Luma)

0.5 days

Live estimate

Estimated Savings

18.900

€/month — avoided drift costs

226.800 €/year

annual avoidance

Days saved per deviation4.5 days

Deviations per month3

Avg. cost exposure€1.400/day

Monthly savings€18.900

Annual savings€226.800

Indicative figures — actual values are determined per project during scoping.

You define safe. We map to it.

Before we talk certifications, tell us what your IT, legal, and compliance teams need to see. Common asks we’ve met: EU hosting, zero-retention APIs, self-hosted deployment, per-project data isolation, auditable access logs. The evidence below is what we can already point at.

Zero-Retention APIs

No Training on Your Data

AI processing APIs don’t retain your data for training purposes. Your operational data stays yours.

Data Residency Control

Self-Hosted Options

Self-hosted deployment keeps data inside your network. EU-hosted managed cloud when that fits better.

GDPR & CCPA

Privacy by Default

Data minimization, transparent handling, and rights to portability, deletion, and access by design.

End-to-End Encryption

TLS/SSL & AES-256

Encrypted in transit (TLS/SSL) and at rest (AES-256). Access runs through your existing sign-in with logged actions.

Full security posture, NIS2 control mapping, and subprocessors at /trust.

Why Leading Facilities Trust Luma

Tangible improvements your team will notice from day one.

Cut Energy & Wear

Efficiency Optimization

Trim steam/power use and mechanical load across lines without touching setpoints.

Troubleshoot in Minutes

Rapid Root Cause Analysis

Root cause, € impact, and the next best action in one view.

Fewer Unplanned Stops

Predictive Maintenance

Detect potential failures far in advance and take action before downtime hits.

See three more▾

Asset Health You Can Trust

Condition Monitoring

Monitor critical warning signs like cavitation and vibration to avoid unexpected breakdowns.

Shift & Audit Reports

Automated Documentation

Automatic, export-ready reports on process changes, causes, and the actions taken.

Plug-and-Play, Your Way

Flexible Deployment

Customizable data, alerts, and reports accessible on-premises or in the cloud, tailored to your workflow.

What Luma won’t do

The boundary is as important as the capability. Knowing what Luma stays out of is why operators trust it.

Does not control the plantRecommends, doesn’t execute: Luma recommends. Your team decides and executes through existing MOC.
No training on your dataRead-only, scoped: Read-only access, scoped to the tags you approve. Your operating data never trains our models.
Not an alarm or APC replacementWorks in the quiet zone: Luma operates in the quiet zone between nominal and trip, not where alarms and APC already act.

Mission

Welcome to a Smarter Future: AI-Driven Insights for Your Plant

Luma connects process, equipment, and energy data to find your plant’s real performance baselines, catch subtle drifts before they escalate, and rank savings opportunities by payback. Your team keeps control — Luma just makes the drift visible earlier.

It runs on your historian, read-only, on your cadence. Hourly for operators, weekly for management, audit-ready for everyone. The longer it sees your plant, the sharper the recommendations get.

Nusret Furkan
Co-Founder, ProcessEngineer.io

Frequently Asked Questions

Alarms protect safety when limits are crossed. APC holds targets once set. Dashboards visualize. Luma works in the “quiet zone” between nominal and trip — learning true baselines, correlating many tags at once, forecasting emerging issues, and prescribing actions with expected savings.

Read-only access to your historian/DCS tags (e.g., PI, OPC, MQTT, SQL). Start with a scoped asset/area and the key process, mechanical, and energy signals. More history helps, but Luma can begin learning from current operations and refine as it sees more.

Teams typically start with one line/asset, connect data, and get early savings by recovering small drifts. ROI is tracked transparently: avoided downtime, recovered throughput, reduced utilities, and a before/after trend for each intervention with € estimates.

Throughput slip, energy creep, off-spec product, accelerated wear and more. Luma quantifies impact of each drift, predicts time-to-limit, and ranks fixes by fastest payback so you stop the bleed before it becomes downtime, waste, or a rebuild.

No, not yet. Luma recommends actions and shows the rationale and expected impact. Your team decides and executes through existing procedures and MOC. Every insight is time-stamped and archived for audits and handovers.

Luma can run fully self-hosted on your servers or private cloud so plant data never leaves your network — a managed cloud option is also available. Luma uses read-only access (it never changes controls), you choose exactly which tags it can see, and data is encrypted in transit and at rest. Access runs through your existing sign-in, and every action is logged for audits.

Ready to See What Luma Can Do?

Two ways in. Open the interactive demo and see Luma running on sample transmitter data. Or book a 30-minute intro call, we walk through your process data landscape, identify quick wins, and show you what Luma can realistically deliver today.

Open the live demo Book intro call

No signup, runs in your browser.