CONNECT. VALIDATE. INTERPRET.
RAUZ Intelligence Platform for Monitoring Data
RAUZ connects monitoring, survey, environmental, agricultural and InSAR data in a vendor-neutral intelligence layer for QA/QC, analytics, alerts, AI-assisted review and engineer-reviewed reporting.
RAUZ Intelligence Platform
One intelligence layer between observation and decision.
The RAUZ Intelligence Platform connects monitoring, survey, environmental, agricultural and remote-sensing evidence in a common review workflow. It is designed to work above existing measurement systems: preserve the source of each observation, check whether the data can be trusted, compare related evidence, identify changes that deserve attention and support engineer-reviewed interpretation and reporting.
Platform Architecture
Connect the evidence without flattening the engineering meaning.
Monitoring integration is not just data aggregation. The platform keeps the relationships needed for interpretation: which instrument produced a value, where it is located, which baseline and units apply, what was happening on the project, and which independent observations can support or challenge the same interpretation.
Measurements & observations
Automated sensors, manual readings, survey, environmental and agricultural observations, project records and satellite-derived ground-motion information.
RAUZ analytical core
Data normalisation, QA/QC, trend and rate analysis, anomaly review, cross-source comparison, InSAR context, alert review and AI-assisted triage.
Decision-ready outputs
Traceable charts, exceptions, technical findings, engineer-reviewed commentary, controlled reports and clearly stated limitations.
FIELD / THIRD-PARTY SOURCES
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├─ Monitoring instruments
├─ Survey / GNSS / total station
├─ Environmental & agricultural sensors
├─ InSAR / remote sensing
└─ Project events, drawings & records
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RAUZ DATA INTEGRATION
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NORMALISATION + PROVENANCE
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DATA QA/QC + CONFIDENCE CHECKS
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ANALYTICS + CROSS-SOURCE REVIEW
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ALERT / ANOMALY / INSAR INTELLIGENCE
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AI-ASSISTED + ENGINEER-REVIEWED INTERPRETATION
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REPORTING / REVIEW / DECISION SUPPORT
RAUZ public technical context: Data Integration, Monitoring Analytics.
Data Inputs
Use the evidence the project already has.
RAUZ is vendor-neutral by design. A review can begin with structured files or reports and move toward recurring integration where that adds value. The practical requirement is not one hardware brand; it is sufficient data, metadata and project context to make comparison technically meaningful.
Geotechnical
Inclinometer, piezometer, settlement, extensometer, load, strain, tilt, crack, groundwater and other suitable time-series records.
Survey & positioning
Total-station observations, levelling, GNSS, deformation survey and other spatial measurements with a controlled reference system.
Environmental
Water, weather, noise, vibration, air, soil and other project-specific environmental observations where the source and units are defined.
Agriculture & natural systems
Soil moisture, temperature, rainfall, humidity, irrigation-related observations and other suitable field or remote data.
Remote sensing
InSAR-derived ground-motion products and other spatial evidence where coverage, geometry, reference and data-quality limitations are understood.
Construction & asset context
Excavation or tunnelling stages, loading changes, dewatering, maintenance, asset geometry and relevant operational events.
Ground & environmental context
Official project GI records, geology, stratigraphy, groundwater, weather and environmental information required to test a physical interpretation.
Existing project systems
CSV/Excel, structured exports, databases, APIs, MQTT, approved file transfer, manual upload or existing platform exports where agreed.
Analytical Workflow
A controlled path from raw evidence to technical interpretation.
The same number can have very different meaning depending on baseline, instrument condition, ground model, weather, groundwater, construction stage and independent evidence. RAUZ therefore separates data processing from interpretation instead of treating an automatic flag as a final engineering conclusion.
Acquire
Receive the agreed data and the metadata needed to understand source, location, time, units and status.
Validate
Screen missing periods, duplicates, jumps, flat-lines, impossible values, baseline changes and known maintenance events.
Normalise
Apply defined units, references, baselines, identifiers and transformations while preserving the raw evidence trail.
Analyse
Review trends, rate of change, change points, thresholds, correlations, spatial patterns and cross-sensor consistency.
Interpret
Test the observed behaviour against geology, groundwater, climate, project events, asset response and plausible mechanisms.
Communicate
Issue prioritised findings, alerts for review, controlled reports, uncertainties, limitations and agreed follow-up actions.
Core Capabilities
Eight connected functions. One review chain.
Each function can support a focused engagement on its own, or the functions can operate together as a recurring monitoring-intelligence workflow.
Data Integration
Connect structured project data without forcing replacement of functioning instruments, loggers or field systems.
Data QA/QC
Screen completeness, continuity, metadata, baseline behaviour, source health and potentially abnormal records before interpretation.
Monitoring Analytics
Review trends, rates, change points, thresholds, spatial relationships and cross-source consistency.
InSAR Intelligence
Add historical or wide-area ground-motion context where satellite geometry, coverage and data quality are suitable.
Alert Intelligence
Review the evidence behind threshold exceedances and anomalous behaviour instead of treating the alarm alone as the conclusion.
AI-Assisted Review
Support anomaly triage, repetitive checks, information organisation and report preparation while keeping consequential interpretation under human review.
Automated Reporting
Standardise charts, checks, calculations and recurring report assembly with a controlled engineering review step.
Independent Review
Add a separate technical layer for owners, consultants or asset teams without requiring RAUZ to become the field-monitoring contractor.
Data Trust
Check whether the evidence is credible before asking what it means.
A dashboard can display a value correctly and the value can still be unsuitable for engineering interpretation. RAUZ treats data provenance, metadata and quality checks as part of the analytical workflow rather than as housekeeping after the analysis.
- Instrument identity, location, orientation and engineering units
- Missing periods, late records and communication gaps
- Duplicate timestamps or duplicated readings
- Step changes, spikes, flat-lines and impossible values
- Baseline, re-zeroing and reference changes
- Calibration, maintenance or sensor replacement history
- Time-zone and timestamp consistency
- Cross-sensor and independent-method consistency
- Threshold source and revision status
- Construction, weather and operational event context
Does an anomaly automatically mean ground or structural movement?
Can RAUZ work from a report or spreadsheet first?
Project Context
The platform is global. The interpretation must stay site-specific.
There is no responsible “default geology” or “default climate” for a global platform page. For a real project, RAUZ expects monitoring data to be interpreted against official or client-controlled information for the actual site. Ground conditions, groundwater, weather, construction sequence and asset behaviour can materially change the meaning of the same numerical trend.
Geology & stratigraphy
Fill, soil and rock sequence, weak layers, discontinuities, cavities, compressible strata or other documented ground features that may govern movement.
Groundwater & water
Pore pressure, groundwater level, dewatering, recharge, rainfall response, seepage and other hydrological factors relevant to the mechanism.
Climate & weather
Rainfall, temperature, humidity, storm events, freeze-thaw or heat effects where they can influence instruments, soil, structures or environmental conditions.
Construction sequence
Excavation stages, tunnelling advance, loading, grouting, ground treatment, drainage changes and adjacent works.
Asset & risk context
Foundation type, structural geometry, operational sensitivity, consequence of movement, tolerances and response responsibilities.
Monitoring design
Instrument type, location, depth, frequency, accuracy, reference system, baseline, trigger framework and reporting route should follow the project question.
Monitoring Domains & Applications
One intelligence architecture across different physical systems.
The measurements change from one sector to another, but the review questions are often similar: what is changing, is the change credible, what evidence supports it, what may be driving it and what deserves attention next?
Movement, water and asset response
Tunnels, excavations, rail, roads, bridges, slopes, dams, mines, buildings and critical facilities where movement or environmental effects require structured review.
Conditions, trends and exceptions
Water, weather, soil, air, noise, vibration and other defined environmental parameters connected to site conditions, project activity and reporting requirements.
Field conditions in context
Soil moisture, temperature, rainfall, humidity, irrigation-related observations and remote data used to understand changing field conditions.
Remote-first, context-led delivery.
RAUZ is operated from Tbilisi and is structured for international technical delivery. Local installation, drilling, regulated field work or site access can remain with qualified local parties while RAUZ provides data integration, diagnostics, analytics, remote sensing, independent review and reporting under an agreed scope.
Integrations & Collaboration
Keep the measurement ecosystem open.
RAUZ is not built around one sensor manufacturer or one field communications architecture. The integration route is selected according to the source system, data ownership, security requirements, update frequency and the engineering value of deeper automation.
Structured files
CSV, Excel and agreed report or table formats can support a focused review or a staged onboarding process.
System exports
Existing project portals, logger software and databases can remain in place where controlled exports provide the required data and metadata.
Recurring interfaces
API, MQTT, database export, approved file transfer or other defined interfaces can support recurring workflows where justified.
Monitoring partners
Local instrumentation, survey, maintenance and field teams can remain responsible for physical delivery while sharing agreed evidence for review.
Remote-sensing partners
Commercial or public satellite-derived products can be incorporated where the product definition, coverage and technical limitations are suitable.
Client & consultant systems
RAUZ can support an independent interpretation layer for owners, consultants or asset teams without taking over the project’s entire digital environment.
Official Industry Context
The market is moving from isolated measurements toward connected monitoring intelligence.
Official product information from established monitoring-technology providers shows a consistent direction: integrate different data sources, make monitoring information easier to analyse, connect alarms and reporting, and give engineering teams a clearer basis for action. RAUZ follows that industry direction while placing stronger emphasis on vendor-neutral interpretation, cross-source validation and an independent engineer-reviewed layer.
iTwin IoT
Bentley describes a cloud-based infrastructure IoT platform that centralises sensor data, analytics, alerts, reporting and sensor-agnostic integration. This demonstrates the established industry need to bring diverse monitoring data into one usable environment.
Beyond Monitoring
Sixense describes a monitoring software platform for integrating data across sources, sensors and formats and using that information for geotechnical, structural and environmental risk management and decision support.
MLWeb / MLSuite
Canary Systems publicly documents web-based imports, data analysis, reporting, manual and automated data workflows, APIs and monitoring without manufacturer or vendor limitations.
CMT Cloud
Worldsensing positions CMT Cloud around centralised network, device and data management, with third-party data exports and workflow automation. It represents the connectivity and field-data layer that an interpretation platform may sit above.
InSAR intelligence
SkyGeo’s official platform material focuses on large InSAR datasets, visualisation, engineering assessment and separating meaningful ground-motion patterns from noise—an important example of specialist spatial intelligence within the wider monitoring ecosystem.
Independent interpretation across systems
RAUZ does not present any third-party platform above as a partnership or endorsement. The comparison is included to explain the industry context. RAUZ’s role is to connect evidence from existing systems, test data credibility and add an independent engineering and environmental interpretation layer.
Technical Boundaries
Automation should shorten repetitive work, not hide professional responsibility.
RAUZ can automate or structure parts of data intake, screening, analysis and reporting. Consequential engineering or environmental conclusions still depend on project context, the quality of the evidence, defined responsibilities and appropriate human review.
| Platform can support | Requires project-specific human judgement or authority |
|---|---|
| Data intake, normalisation and traceability | Whether the available evidence is sufficient for a consequential project decision |
| QA/QC screening and anomaly triage | Whether an apparent anomaly represents real physical behaviour |
| Trend, rate, correlation and threshold checks | Why movement is occurring and whether the proposed mechanism is credible |
| Alert generation or prioritisation for review | Whether work should stop, continue, change sequence or require remedial action |
| Automated charts, tables and report preparation | Final engineering/environmental interpretation, approval and statutory responsibility |
| AI-assisted organisation, screening and drafting | Professional sign-off where project or regulatory responsibility requires it |
Outputs & Demonstration
Show the evidence chain, not just the dashboard.
A platform page should be supported by real first-party examples. RAUZ can use anonymised, public or synthetic demonstration datasets where client information cannot be shown, provided the data type is clearly labelled.
Sample monitoring analysis
Raw versus validated data, trend and rate views, event annotations, cross-sensor comparison and the reason an item was prioritised.
Sample diagnostic review
An example of how an apparent jump, baseline shift, conflicting instrument or trigger exceedance is investigated and documented.
Sample automated report
Executive status, data completeness, trend plots, trigger status, exceptions, technical commentary, limitations and revision history.
InSAR interpretation example
Spatial ground-motion patterns compared with field data, asset context or historical observations where technically suitable.
Platform workflow screenshot
A genuine RAUZ interface view showing how data, QA/QC, analytics or reporting are organised. Client identifiers can be removed.
Traceable output
Show how a conclusion links back to data source, processing step, project context, limitation and reviewer.
Frequently Asked Questions
Questions clients should settle before connecting monitoring data.
What is the RAUZ Intelligence Platform?
Does RAUZ require proprietary sensors?
Can a project start with Excel, CSV or an existing report?
Can InSAR be reviewed together with ground instruments?
How does RAUZ use AI?
Does an automatic alert mean the asset is unsafe?
Can RAUZ work with a local monitoring contractor?
Which regions is the platform intended to support?
Start With the Evidence
Have monitoring data but still need a clearer answer?
A useful first discussion does not require a finished specification. Send the project location, asset or environmental system, monitoring objective, available instruments or data sources, known geology or environmental conditions, current reporting or trigger framework and the question the project team needs to answer.
Useful first information
- Project location and asset or environmental system
- Monitoring objective and current concern
- Existing instruments, survey, InSAR or environmental data
- Available reports, drawings, GI records or baseline information
- Trigger criteria, reporting frequency and decision deadlines
- Any unexplained trend, anomaly or conflicting evidence
Possible first scopes
- Focused monitoring-data diagnostic
- Independent review of an existing monitoring report
- Recurring monitoring-intelligence review
- InSAR-to-ground-data comparison
- Data integration and QA/QC setup
- Automated reporting or platform workflow pilot
Official References
- RAUZ — Environmental & Geotechnical Monitoring Intelligence — official platform positioning and monitoring domains.
- RAUZ — Monitoring Data Integration — data sources, interfaces, normalisation and vendor-neutral integration.
- RAUZ — Monitoring Analytics — QA/QC, trends, rates, anomalies, context and engineer-reviewed analytics.
- RAUZ — Automated Monitoring Reporting — reporting workflow, automation boundaries and human review.
- Bentley Systems — iTwin IoT — official infrastructure IoT monitoring platform information.
- Sixense — Beyond Monitoring — official monitoring software platform information.
- Canary Systems — MLWeb — official monitoring data-management and analysis capabilities.
- Worldsensing — CMT Cloud — official monitoring network, device and data-management information.
- SkyGeo — InSAR Ground-Motion Monitoring — official InSAR platform and assessment information.
External references are included only to describe established monitoring-technology practices and the wider industry context. They do not imply partnership, endorsement or that any third-party project is a RAUZ project.