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Agentic AI & Automation June 2026 Proprietary

Mantia — Agentic Industrial-Maintenance Suite

A private suite of agentic assistants for industrial asset maintenance, shaped to enterprise EAM data via OData. A portal hub catalogs three specialist agents — work-order generation, spares planning, and notification triage — all built on one shared agent core with a mock-or-real connector.

Composition
Portal hub + 3 specialist agents
Shared core
OData V2 (+CSRF) connector + agent base + web baseline
Connector mode
Mock (dev) ↔ real (prod), same agent code
Deployment
Live (private); dual-target VPS + Azure Container Apps
Mantia — Agentic Industrial-Maintenance Suite — Architecture
#agentic-ai #maintenance #odata #eam #llm #automation #private

Business Context

Maintenance is where uptime is won or lost, and most of its planning work is structured enough to assist with agents — but only if the assistant speaks the enterprise system's language safely. Mantia's mock-or-real connector lets the agents be developed, demoed, and validated without touching a production backend, then promoted to the real one unchanged.

Strategic Value

Mantia demonstrates a reusable accelerator pattern: a shared agent core (connector + agent base + web baseline) that turns each new use case into a thin, fast-to-build specialist agent. The hub makes the suite legible to a business audience (catalog, lifecycle, business case), and the mock-first connector de-risks integration with heavyweight enterprise systems.

The Challenge

Industrial maintenance planning is repetitive, knowledge-heavy, and bound to enterprise systems whose data is awkward to work with. Each task — raising a work order, planning spare parts, triaging a notification — needs the same enterprise context but is usually done by hand, one transaction at a time.

Our Approach

Mantia is a hub-and-agents suite. A portal hub presents a data-driven catalog of agents with lifecycle tiles and a business case per agent. Three specialist agents sit behind it — one drafts maintenance work orders, one plans spares and reservations against material stock, one triages plant notifications — and all share a single agent core: a generic OData V2 connector (with CSRF), an agent base, and a common web baseline. The connector runs against a faithful mock of the enterprise schema in development and a real backend in production, so the same agent code ships to both.

Key Performance Indicators

KPIBaselineResultImpact
New use case → working agentBespoke build per integrationThin agent on a shared coreFaster, consistent delivery
Integration riskDev against a live backendMock-first connector, real in prodBuild & demo without touching production

Proprietary — source code not publicly available

Architecture

mantia architecture

mantia architecture

A suite, not a one-off

Mantia is a private suite of agentic assistants for industrial maintenance. A portal hub catalogs the agents; each specialist (work-order generation, spares planning, notification triage) is a thin layer on one shared agent core, talking to an enterprise EAM schema through a connector that is a faithful mock in development and the real backend in production.

This is proprietary work; the live deployment is private and behind access control. The card describes the architecture and intent without exposing client data, names, or internal logic.

Technology Stack

Python FastAPI Pydantic-AI LiteLLM HTMX OData Docker Azure Container Apps

Visual assets for this project are not publicly available.