Connect or ingest approved customer data
IAS starts with material and signals the customer authorizes: documentation, records, events, system feeds, interviews, and asset information.
Priority operating model
How IAS Works
IAS turns company documents, records, events, interviews, asset information, and system feeds into practical answers, signals, and workflows.
Keep it inside the customer-controlled environment
Deployment boundaries are selected with customer cybersecurity, infrastructure, and operational requirements.
Organize the operating context
Information is structured by site, equipment, role, event, responsibility, source, and time.
Process with local or controlled AI
AI inference may run on an onsite appliance, customer server, dedicated inference node, or an approved controlled-cloud service.
Present answers, signals, and workflows with visible sources
Users should be able to see where information came from, when it was current, and whether it has been reviewed.
Keep human authority
Authorized people remain responsible for consequential safety, maintenance, production, security, and workforce decisions.
Reference architecture
Every layer has a defined boundary.
The exact systems and connections are selected during discovery. This model shows the responsibility chain, not a promise that every source system will be integrated.
Approved sources
Manuals, interviews, event records, asset data, and approved system feeds
Ingestion
Validate, normalize, index, and preserve source identity
Permissions
Apply site, role, product, document, and record boundaries
Controlled processing
Run application and AI services inside the approved architecture
Evidence layer
Carry citations, timestamps, confidence, status, and review history
Operational delivery
Answers, dashboards, workflows, records, and exports for authorized users
Deployment patterns
Architecture follows the environment.
Options depend on customer cybersecurity, performance, connectivity, and infrastructure requirements.
Onsite IAS appliance
Customer-hosted server
Private-network deployment
Controlled cloud where approved
Split application server and AI inference node
Offline-capable deployment
Review and auditability
People can inspect what the system used.
Where supported by the product and source, IAS preserves citations, record identity, timestamps, refresh status, approvals, and activity logs. Human review remains part of consequential workflows.
Integrations and updates
Controlled change, not silent change.
Optional connectors, content refreshes, model updates, and software patches are planned around customer access, testing, backup, and change-control requirements.
IAS does not remove operational responsibility.
Visible evidence supports judgment; it does not replace site procedures, qualified personnel, or customer approval controls.
Talk with IAS
Review the data, network, and human-review boundary with IAS.
IAS will review the operating need, users, information sources, infrastructure, and a practical starting scope with your team.