EDGE COMPUTE UNITSRuggedized local computing for acquisition, preprocessing and mission services.
FROM DATA TO DECISIONS.
EDGE + CLOUD
Process locally. Scale globally. Decide with better context.
RAVAM combines field-ready edge computing with cloud, private or hybrid data services so missions can continue close to the source while larger datasets, analytics and institutional workflows scale beyond the field node.
EXPLORE EDGE + CLOUD →⚡LOCAL
PROCESSING
PROCESSING
◇CONTROLLED
DATA FLOW
DATA FLOW
☁HYBRID
ARCHITECTURE
ARCHITECTURE
AIAI-READY
INFRASTRUCTURE
INFRASTRUCTURE
↔SCALABLE
STORAGE
STORAGE
✓MISSION-ALIGNED
DEPLOYMENT
DEPLOYMENT
▤OPEN
INTEGRATION
INTEGRATION
EDGE SOLUTIONS
Intelligence at the Source.
Process, filter, buffer and coordinate data close to where it is created.
EDGE COMPUTE UNITSRuggedized local computing for acquisition, preprocessing and mission services.
AI ACCELERATIONGPU, TPU or accelerator support where onboard inference is appropriate.
LOCAL DATA STORAGEEncrypted local storage, buffering and synchronization when connectivity becomes available.
NETWORK MANAGEMENTIntegrate cellular, RF, mesh, satellite and wired connectivity at the field node.
POWER OPTIMIZATIONCoordinate computing and communications around available grid, battery, solar or hybrid power.CLOUD SOLUTIONS
Scale Beyond the Field Node.
Aggregate data, support deeper analysis and connect institutional workflows.
CLOUD / PRIVATE INFRASTRUCTUREDeploy services in public cloud, private infrastructure or hybrid environments according to requirements.
AI ANALYTICS & MODELSProcess larger datasets, train or run models and deliver structured analytical outputs.
DATA MANAGEMENTLong-term storage, data fusion, controlled access and API-based integration.DESIGN PRINCIPLE
Not Everything Belongs in the Cloud.
Not Everything Belongs at the Edge.
The right architecture places time-sensitive or connectivity-dependent functions close to the field, while centralized services handle aggregation, deeper analysis, collaboration and long-term records.
HYBRID ARCHITECTURE
Seamless Data Flow. Continuous Intelligence.
Edge and cloud are designed as one operational chain rather than separate technology silos.
01FIELD ASSETSAIR · GROUND · NEST · Sensors · Third-party data
→02EDGEIngest · Filter · Normalize · Buffer · Local analytics
→03MULTI-NETWORK COMMUNICATIONSRF · Cellular · Mesh · Satellite · Fiber
→04CLOUD / PRIVATE PLATFORMStorage · Fusion · AI services · APIs
→05USERS & APPLICATIONSCommand · GIS · Reports · Enterprise systems
ARCHITECTURE CAPABILITIESStore-and-forward operationLocal continuity during connection lossCloud, private or hybrid deploymentOpen API and third-party integrationScale from one field node to distributed networks
DATA WORKFLOW
01INGESTReceive field and enterprise data
→02NORMALIZEStructure data from different sources
→03FUSECombine sensor, spatial and contextual information
→04ANALYZEApply analytics and AI-assisted interpretation
→05DELIVERProvide outputs to operators and systems
REAL-WORLD APPLICATIONS
Distributed Intelligence Across Multiple Missions.
FOREST MONITORING
PIPELINE INTEGRITY
AGRICULTURE
MINING & INDUSTRIAL
DISASTER RESPONSE
ENVIRONMENTAL MONITORING
URBAN & STRATEGIC ASSETSPOWERED BY A CONNECTED ECOSYSTEM
From Field Data to Institutional Intelligence.
RAVAM Edge + Cloud links acquisition, field infrastructure, communications, analytics and operational decision support.
RAVAM AIR™Collect↔RAVAM NEST™Process at the edge↔RAVAM GROUND™Inspect & support↔RAVAM AI PLATFORM™Fuse & analyze↔RAVAM COMMAND™Deliver operational context
Analytics and models support interpretation, prioritization and decision workflows. Outputs remain dependent on source data, model performance, deployment conditions and appropriate human or professional review.
EDGE + CLOUD