Industrial enterprises collect more data than ever — and use less of it than they think. Brainwave builds the analytics foundation that turns historian, SCADA, ERP, and spreadsheet data into clear, actionable decisions your operators, engineers, and executives actually trust.
OPERATIONS INTELLIGENCE
Upstream · Q2 2026
DECISION LATENCY
ASSET UPTIME
0.0%COST AVOIDED
DECISION VELOCITY · 30 DAYS
DECISIONS PENDING
Three pains that show up on every shop floor, in every control room, and in every executive review — no matter the industry.
Your historian holds fifteen years of process data. Your engineers can only answer a question if they know which tag to pull and have an afternoon free.
The shift
Contextualized data that engineers, analysts, and executives can actually query — without filing a ticket.
A compressor throws a code at 2:47 AM. By 9 AM the shift report notes it. By noon someone is looking at the trend. By then you have lost the day.
The shift
Anomaly detection that reaches the right person in minutes, not in the morning stand-up.
Your monthly ops review is built from a Power BI deck that pulls from three spreadsheets that pull from two extracts that came out of a report someone ran last week.
The shift
Decision-ready dashboards backed by a trusted data layer — refreshed on the cadence the business actually moves at.
Three different seats at the table. Three different versions of the same pain.
Operations Leadership
“I need to see what's happening across my sites before it becomes a problem.”
Benchmark
Industrial analytics programs typically deliver 30–50% reductions in unplanned downtime and 10–30% throughput gains.
McKinsey
Digital Transformation Leadership
“We have platforms. We have pilots. We do not have scale.”
Benchmark
Roughly 70% of industrial digital pilots never scale past one site.
McKinsey
C-Suite & Owners
“I'm making eight-figure decisions on data that's a week old.”
Benchmark
AI leaders are achieving 2× revenue growth and 40% more cost savings than laggards. Only 5% of companies qualify as "future-built."
BCG, 2025
Five pillars that fit together. Start with one, add the rest as you scale.
Unify historian, SCADA, MES, ERP, and engineering documents into a single contextualized layer your teams can actually query. We read from your existing systems via OPC UA and native APIs — no rip-and-replace.
Decision-ready dashboards that refresh on the cadence the business actually moves at — connected to the same trusted data layer every other downstream tool uses.
Machine learning where it pays — compressor trains, rotating equipment, process anomalies, yield losses. Production-grade, with explainability baked in so operators trust the alerts.
A pragmatic path from on-prem historians and bolt-on spreadsheets to a modern, cloud-or-hybrid data architecture — without disrupting operations mid-campaign.
The piece that keeps the project alive after we leave: decisions surfaced in the tools your teams already use, plus training and documentation so the system belongs to you.
Five questions. One score. Three actions you can take this quarter.
Five phases, honest timelines, scale criteria baked in from day one.
We talk to your ops, maintenance, engineering, IT, and finance teams. We inventory your historian, DCS, SCADA, MES, ERP, and LIMS. We rank use cases by value and feasibility.
You get
We stand up the contextualization layer that unifies your historian, MES, and ERP into a model your teams can actually query. We establish OT-safe read patterns, governance, and lineage.
You get
We build one high-value decision application end to end — predictive alerts on a compressor train, yield-loss attribution on a line, real-time OEE for a plant.
You get
We replicate the pattern across lines and sites. We harden pilots into production. We integrate with ticketing and work-order systems so insights become actions.
You get
We train your analysts, engineers, and BI teams. We document everything. We graduate you to self-sufficiency.
You get
No pilot purgatory. Every phase is scoped with scale criteria baked in from day one.
Platform-agnostic. We meet you at your existing stack.
Historians & Source Systems
Integration & DataOps
Data Platforms & Analytics
BI & Visualization
Three engagement examples drawn from completed project work.
Challenge
Screen-out events during hydraulic fracturing cost an operator $250K+ per incident. They needed real-time early warning from SCADA streams before costly well failures.
Approach
Production ML system using a dual-head LSTM autoencoder with Bahdanau attention. 91% multi-class accuracy across four operational states. Sub-50ms inference. Attention-based explainability so operators trust the alerts.
Outcome
2–5 minute advance warning on screen-out events. 96% recall on the failure class.
Challenge
A 1,500-employee workforce across six departments had no data-driven view of what was driving overtime, attrition, or safety incidents. Reports were manual and quarterly.
Approach
Statistical workforce analytics — ANOVA, correlation analysis, hypothesis testing — across six departments, with executive dashboards and targeted recommendations.
Outcome
$6.5M in potential overtime savings identified. 4.2% attrition improvement opportunity. 296 certification compliance gaps surfaced.
Challenge
Industrial equipment failures were causing unplanned downtime and emergency repairs across a distributed asset base. Operations needed reliable forecasting for proactive maintenance scheduling.
Approach
ML classification on sensor data with single-machine and fleet-wide batch prediction. CLI tool plus web interface for operators. Docker deployment for portability.
Outcome
85% prediction accuracy, 75% recall on failure cases, sub-100ms inference latency. Fleet-wide batch scoring in production.
Engagement details generalized to protect client confidentiality. Methodologies and outcomes drawn from completed project work.
Four things we will not compromise on.
We come from the field, not the boardroom. We know what it looks like when the historian is down and nobody can tell you why.
We meet you at your existing stack — PI, IP.21, Power BI, whatever you already have. No vendor lock-in.
Every engagement ends with training, runbooks, and a system your team owns. No recurring dependency on us.
We scope engagements with scale criteria baked in from day one. If we cannot tie it to EBITDA, we do not build it.
The questions industrial buyers actually raise.
A 30-minute discovery call. No deck, no pitch — we talk through your systems, your pain, and whether we can help.