Luma Process Intelligence
Luma analyzes multivariate transmitter data for plant operators and engineers to detect early deviations and prevent quality, energy, and downtime losses.
From raw transmitter data to actionable reports in three steps.
Read-only access to selected transmitters plus context (limits, units, setpoints).
Detect subtle drifts and anomalies; cross-check process vs. mechanical context; estimate potential cost exposure.
Hourly/daily/weekly/monthly digests with findings, likely root causes, mitigation ideas, and cost estimates.
Three pillars that turn raw transmitter data into prioritized, cost-aware actions.
Correlate process, equipment, and energy signals to reveal true drivers. Detect subtle drift in time to prevent waste, downtime, and off-spec.
Rank likely causes with confidence and give the next best actions.
Quantify current losses from deviations across energy, yield, and quality — and forecast what it costs if the drift persists.
Attribute savings to interventions. Before/after trends for each fix.
Match current behavior to past events to surface recurring root causes.
Use what worked before to sharpen future recommendations automatically. Searchable record of issues, actions, and outcomes.
All working simultaneously. One Luma, multiple perspectives.
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
Luma reveals process drift well before traditional protections step in.
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
Based on earlier detection of process deviations: deviations per month × days saved per deviation × average cost exposure per day.
18.900
€/month — avoided drift costs
226.800 €/year
annual avoidance
Indicative figures — actual values are determined per project during scoping.
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.
AI processing APIs don’t retain your data for training purposes. Your operational data stays yours.
Self-hosted deployment keeps data inside your network. EU-hosted managed cloud when that fits better.
Data minimization, transparent handling, and rights to portability, deletion, and access by design.
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.
Tangible improvements your team will notice from day one.
Trim steam/power use and mechanical load across lines without touching setpoints.
Root cause, € impact, and the next best action in one view.
Detect potential failures far in advance and take action before downtime hits.
Monitor critical warning signs like cavitation and vibration to avoid unexpected breakdowns.
Automatic, export-ready reports on process changes, causes, and the actions taken.
Customizable data, alerts, and reports accessible on-premises or in the cloud, tailored to your workflow.
The boundary is as important as the capability. Knowing what Luma stays out of is why operators trust it.
Mission
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
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.
Book a 30-minute intro call. We’ll walk through your process data landscape, identify quick wins, and show you what Luma can realistically deliver today.