Surface cause and effect across systems that were never designed to talk to each other.
Every action in your business leaves a trace — in your ERP, your ticketing system, your infrastructure metrics. SCRAPE uses LLMs and ML to correlate those traces, turning isolated records into a connected picture of what actually happened and why.
The problem
Your operational data lives in silos. Events in one system have invisible ripple effects across others — but no single tool connects the dots. A ticket is closed in your project tracker, a metric shifts in your infrastructure, a record changes in your ERP. Are they related? What caused what? Answering these questions manually means cross-referencing timestamps, picking the right data, and running analysis across systems that were never designed to share context. It does not scale.
How it works
Three steps from isolated records to connected insight.
Connect your sources
SCRAPE ingests data from your ERP, ticketing systems, infrastructure metrics, and other operational sources. Pluggable interfaces mean you are not locked to any single vendor.
Correlate with LLMs & ML
Large Language Models and Machine Learning identify relationships between disparate events that no single system could surface on its own.
Surface cause and effect
Your team gets a connected picture of what happened, what triggered it, and what to do next — backed by rigorous statistical validation.
What you can answer
Incident root cause
“Which upstream event or ticket triggered this infrastructure alert?”
Operational impact
“What business processes were affected by this system event?”
Process correlation
“How do changes in one system ripple across teams and tools?”
Historical patterns
“What sequences of events consistently precede the outcomes you care about?”
Built for any operational domain
SCRAPE is system-agnostic. Wherever your operational data lives, and whatever it describes, the correlation engine works on it.
Software and platform operations
Tie deploys, feature flags, and config changes to crash rates, latency shifts, and customer-reported incidents.
IT and cloud infrastructure
Correlate change-management tickets, alerts, and infrastructure metrics so you can see what change moved which number.
Business process and workflow analytics
Connect process events in your ERP, CRM, and ticketing system to downstream outcomes and SLAs.
Industrial operations and asset management
Pair maintenance records, work orders, and inspection forms with sensor telemetry to surface what really changes machine behavior.
Supply chain and logistics
Link supplier events, shipment milestones, and quality data to downstream production and customer impact.
Every deployment is custom-built. The discovery phase maps your specific systems and the relationships that matter to your business.
Built for your environment
No vendor lock-in. No data leaving your network. No compromises.
Any Large Language Model
Bring your own LLM — cloud-hosted or locally deployed. SCRAPE integrates with any large language model and ML process. No vendor lock-in.
Any data source
A pluggable source interface connects to whichever systems your team already uses. ERP, ticketing, infrastructure metrics, CSV exports — if it has operational data, it works.
Any operational database
Schema and column names are discovered at runtime from your database. Add new data sources and they appear in the next analysis — zero reconfiguration.
Your data, your control
Deploy on-premises or in air-gapped environments. All IP and client data remains wholly in your control — never exfiltrated, never modified.
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 connect the dots in your data?
Start a discovery call to map your data sources and define the correlations that matter to your business.
Get in touch