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A Fully Isolated, Local AI Agent — Deeply Integrated with Your Infrastructure Data

Your data never leaves. The AI comes to you.

Assetspire's Agentic AI isn't a cloud-based chatbot querying external APIs — it's a fully isolated, locally-deployed large language model with native access to the entire Assetspire platform. Your data never leaves your environment. Ask questions in natural language, and the AI agent queries your infrastructure directly to produce answers, dashboards, renders, and reports.

The AI agent understands the complete Assetspire data model — assets, metrics, connectivity, permissions, capacity, and more. It can generate custom dashboards on demand, produce branded reports for stakeholders, run complex capacity queries across your estate, and automate remediation workflows — all through conversational natural language interaction.

Because it runs locally within your deployment, the AI agent inherits the same security posture as the rest of the platform. It respects user permissions, operates within tenant boundaries, and produces outputs that are fully auditable. There is no external data processing, no third-party model hosting, and no data exfiltration risk. ---

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A Fully Isolated, Local AI Agent — Deeply Integrated with Your Infrastructure Data Dashboard View

Zero Data Leakage. Complete Isolation.

The AI agent is fundamentally different from cloud AI integrations:

  • Fully Local Deployment: The language model runs entirely within your infrastructure — on-premises or in your private cloud. No API calls to external AI services, no data leaving your environment.
  • Self-Contained: The AI agent, its model weights, and all processing happen within the same security boundary as the rest of the Assetspire platform
  • No External Dependencies: The agent doesn't rely on external services to function — it works even in air-gapped environments with no internet access
  • Auditability: Every AI interaction is logged — the query, the data accessed, and the output produced — providing a complete audit trail
  • Permission-Aware: The AI agent operates with the requesting user's permission scope. If a user can't see certain assets, the AI can't access them either. Tenant isolation is preserved through every interaction.

Just Ask.

Query your infrastructure the way you'd ask a colleague:

  • Conversational Interface: Ask questions in plain English — "What's the power utilisation in Data Hall 1?", "Show me all racks with more than 80% capacity in London", "Which circuits are approaching their SLA limits?"
  • Cross-Domain Understanding: The AI understands assets, locations, metrics, connectivity, capacity, and permissions — and can combine them in a single query
  • Context-Aware Follow-Ups: The AI maintains conversation context, so you can refine queries naturally — "Now filter that to just the east wing", "What about the same metric for last month?"
  • Data-Grounded Responses: Every answer is grounded in real platform data, not generated from training patterns. The AI queries live data and presents verifiable results.
  • Tabular & Visual Results: Responses can include tables, charts, and formatted summaries — not just plain text

Generate Dashboards and Reports on Demand

The AI agent can produce visual outputs directly:

  • Dashboard Generation: Ask the AI to create a dashboard — "Build me a dashboard showing carbon emissions by datacenter for Q4" — and it generates a fully functional widgetboard with appropriate charts, metrics, and filters
  • Branded Report Production: Request a report for a specific audience — "Produce a capacity report for Client X with their branding" — and the AI generates a branded document using the customer's theme (logos, colours) from the platform's theme system
  • Server-Side Renders: The AI can trigger server-side rendering of 3D views, component visualisations, and dashboard snapshots for inclusion in reports
  • Export Formats: Generated reports can be exported as images or PDFs, ready for board-level presentation

Native Access to Everything

The AI agent has full parity with the platform's capabilities:

  • Complete Data Access: The agent can query any data the user has permission to access — assets, metrics, connections, audit trails, capacity, and more
  • Operational Actions: Beyond querying, the agent can perform actions — creating assets, updating configurations, triggering workflows — all within the user's permission scope and with full audit logging
  • Metric Analysis: The agent can query historical and real-time metrics, perform trend analysis, and identify anomalies across your infrastructure
  • Capacity Planning: Ask the agent to analyse capacity across sites, forecast growth, and identify stranded resources

From Insight to Action

The AI agent can close the loop between detection and resolution:

  • Alert-Driven Actions: Configure the AI to respond to specific alert conditions with predefined remediation steps
  • Workflow Integration: The agent can trigger approval-gated workflows — proposing actions that require human confirmation before execution
  • Scheduled Analysis: Set up recurring AI queries that run automatically and generate reports or alerts based on the results
  • Full Audit Trail: Every AI-initiated action is logged with the same rigour as manual actions — who requested it, what the AI did, and what changed

Ready to See it in Action?

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