What you get
SCRAPE turns isolated records from systems that were never designed to talk to each other into a connected picture, with statistically validated cause-and-effect relationships, change-lifecycle tracking, and operational intelligence.
The walkthrough below uses an industrial maintenance deployment as a concrete example. The same engine applies to software operations, IT infrastructure, business processes, supply chain, and any other domain where events in one system change outcomes in another. Every engagement is custom-built for your data sources and the relationships that matter to your business.
Per-event analysis you can defend
Every flagged change is backed by evidence, not a hunch.
A high bar for what gets flagged
SCRAPE only flags a change when it can show the change is real and that it actually matters at an operational scale. Borderline or noisy results are filtered out before they ever reach your team, so the events you see are the ones worth acting on.
Nothing silently dropped
Drill into any flagged event for the full breakdown behind it. When an event cannot be evaluated, SCRAPE reports it as skipped with a reason rather than hiding it. You always know what was considered and what was set aside.
Component generation tracking
Full lifecycle visibility for every replaceable part on every asset.
Every time a component is replaced on an asset, SCRAPE marks that as a generation boundary. Gen 1 runs from the asset's first operational session to the first replacement. Gen 2 from the first replacement to the second. And so on. For each generation, the platform records:
Install & replace dates
Precise generation window boundaries
Operational hours
Total hours within the generation window
Session count
Flights, runs, or cycles per generation
Current status
In-service or replaced
This lets you answer questions like: "Are our Gen 3 motors lasting longer than Gen 2?" or "Which asset is overdue for a component swap based on operational hours?"
Operational dashboards
Pre-built Grafana dashboards, auto-provisioned on deployment.
Fleet Overview
All assets on a unified timeline with event annotations from connected sources
Asset Sessions
Per-asset operational session history with correlated event markers
Telemetry Detail
Deep-dive into any metric with cross-system event overlays
Correlation Detail
Before/after metric comparison per event with full statistical detail
Events by Asset
Filterable event table with component breakdowns and measured impact
Component Lifecycle
State timeline showing generation boundaries and operational hours per generation
Operational Hours
Cumulative hours per asset with component swap markers
All dashboards use template variables — filter by asset, component category, date range, or individual event.
Predictive foundation
A structured, labeled dataset — derived from unstructured records, with no manual labeling required.
The correlated dataset is the base layer for predictive models. With enough history, you can:
Quantify how often issues recur across components, services, or processes
Surface assets or systems that behave unusually compared to peers
Track reliability and longevity trends over time
Feed correlated data into your own ML and predictive models
Fits your stack, not the other way around
Any LLM or ML process
Cloud-hosted, self-hosted, or air-gapped. Bring whichever model fits your security and cost requirements.
Any data source
Pluggable source interfaces for ERP, ticketing, infrastructure metrics, CSV, and custom APIs. If it stores operational data, SCRAPE can read it.
Any operational database
Schema discovered at runtime. No hardcoded column names — add new data sources and they appear automatically.
Any deployment model
On-premises, air-gapped networks, private cloud, or hybrid. Your infrastructure, your rules.
Your data stays yours
All intellectual property and client data remains wholly contained within your infrastructure. SCRAPE reads your data to perform analysis but never modifies it. Your databases, your systems, your results — all under your control.
With a locally deployed LLM, nothing leaves your network. If you choose a cloud LLM provider, only the text needed for extraction is sent — raw operational data never leaves your infrastructure.
Custom-built for your ecosystem
SCRAPE is not a SaaS product. Every deployment is custom-built for your ecosystem by Oberth Systems engineers.
Engagements begin with a discovery phase to map your data sources and define the cause-and-effect relationships that matter to your business.
Ready to deploy on your terms?
Start a discovery call to map your data sources and define the correlations that matter to your business.
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