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What is Lingdian AI

Lingdian AI Agents is the AI capability hub for delivery and troubleshooting teams. Turn point-table recognition, expert Q&A, device context, and confirmable memory into governed assets — so every commissioning shift starts from what the team already learned.

This section explains what the agents are, what they solve, and how collaboration and memory work — aligned with first-pass connect, remote clarity, and trustworthy data.

3Narratives: Role · Collaboration · Memory
4+Agent forms: assistant / device / station / expert
1Permission boundary: same as the signed-in user

How one job becomes the next starting point​

ASSET LIFECYCLE · field experience into reusable assets

01

Capture

Point tables / protocol PDFs / samples, device & alarm context, on-call chat enter the system.

02

Process

OCR & protocol parse → thing-model draft; assistant recalls knowledge / Skills; sessions compress by layer.

03

Assetize

Drafts confirmed to store; diagnoses written; memory candidates confirmed and owned by experts.

04

Assemble

Bind knowledge, Skills, tools per tenant / project / agent; inject only what the task needs.

05

Reuse & feedback

Next same-type device needs less mapping; next shift fewer calls; results update memory & eval.

Three capabilities you actually care about​

01 · Role

Role: less debug, just use

AI sits in the delivery path — not a lone chat box. Point tables, troubleshooting, SCADA assist.

  • Point table / protocol → thing-model draft
  • Q&A with device & log context
  • Human confirm for high-risk actions
02 · Collaboration

Collaboration: the right agent

Platform assistant, device / station agents, system experts & Skills — delegate and assemble across sessions.

  • Skills / knowledge by role
  • Expert handoff packages
  • Same permissions as the user
03 · Memory

Memory: evidence → long-term cognition

Sessions compress with provenance; expert memory is confirmable; device / station brains hang on objects.

  • Session: raw → summary → scenario
  • Expert: candidate → confirm → recall
  • Object: device / station memory graph
04 · Guardrails

Boundaries: not a protocol substitute

Protocol gaps stay on hot-pluggable plugins; AI speeds semantics. Memory needs confirm; tenant isolation holds.

  • Humans publish & approve
  • Tenant / project isolation
  • Never put ProductSecret in chat

Start here​

You want…Open
What cost AI removesAI Role
Multi-agent split & handoffAgent Collaboration
How memory growsAgent Memory
Gateway point-table pathMQTT Gateway