Google Cloud provides powerful cloud infrastructure, analytics, and AI services. DeepIQ complements those capabilities by connecting operational technology (OT), engineering technology (ET), and enterprise IT into a unified contextual intelligence layer.

DeepIQ transforms fragmented industrial data into engineering-aware information that helps Google Cloud analytics and AI understand how your operations actually work.

No.

DeepIQ is designed to enhance your Google Cloud investment—not replace it.

Google Cloud provides the infrastructure, data platform, analytics, machine learning, and AI services. DeepIQ provides industrial connectivity, engineering intelligence, business context, and operational knowledge that make those services more valuable in industrial environments.

DeepIQ securely connects operational systems, engineering applications, historians, maintenance platforms, and enterprise systems to your Google Cloud environment.

It then:

• Connects industrial data sources
• Creates reusable industrial data products
• Builds contextual knowledge graphs
• Connects engineering information to operational data
• Delivers trusted data for analytics and AI

Organizations continue using Google Cloud as their preferred cloud platform while DeepIQ provides the contextual intelligence layer.

No.

DeepIQ supports customer-owned data architectures.

Industrial data can remain within your Google Cloud environment, on-premises infrastructure, or hybrid deployments while DeepIQ provides connectivity, orchestration, contextualization, and governance.

There is no requirement to duplicate your industrial data into a proprietary DeepIQ repository.

DeepIQ complements a wide range of Google Cloud services, including:

• BigQuery
• Vertex AI
• Gemini
• Cloud Storage
• Google Kubernetes Engine (GKE)
• Dataflow
• Pub/Sub
• Cloud Run
• Looker
• Identity and Access Management (IAM)
• Security Command Center

DeepIQ integrates with your existing Google Cloud architecture rather than replacing it.

Yes.

DeepIQ helps organizations migrate historian data into Google Cloud while preserving the engineering meaning behind the data.

Capabilities include:

• Historical data migration
• Real-time streaming
• Asset hierarchy preservation
• Metadata enrichment
• Engineering relationships
• Data lineage
• Time-series validation

This creates a stronger foundation for analytics, machine learning, and AI.

DeepIQ supports connectivity to many industrial and enterprise systems, including:

• AVEVA PI System
• AspenTech IP.21
• OPC UA
• PLCs
• SCADA systems
• DCS platforms
• CMMS
• ERP applications
• Engineering databases
• Laboratory systems
• SQL databases
• Cloud storage platforms

DeepIQ Reveal securely connects these environments into one operational intelligence platform.

Yes.

DeepIQ PIDx uses AI to convert engineering drawings into structured, machine-readable intelligence.

Extracted equipment, instrumentation, process relationships, and engineering metadata can then be connected directly to operational and enterprise data within Google Cloud.

Common applications include:

• Process Safety Management
• Management of Change
• Reliability
• Digital Twins
• Engineering Search
• Asset Integrity
• AI Assistants

Absolutely.

DeepIQ is cloud agnostic and supports deployments across Google Cloud, Microsoft Azure, AWS, Databricks, Snowflake, and on-premises environments.

Organizations can modernize their industrial architecture while maintaining flexibility and avoiding cloud lock-in.

Yes.

DeepIQ Biz Context creates industrial knowledge graphs that connect:

• Equipment
• Sensors
• Engineering drawings
• Maintenance records
• Supply chain
• Quality systems
• Operational events
• Enterprise applications