TDengine
The install is empty. The plant is the work.
Downloading TDengine gives you a time-series store with nothing in it. LCT models your assets, attaches the manuals and SOPs you already have, and wires PLC, SCADA and telemetry so there is a plant worth reasoning about. Licence comparison and AI features need that context first — they are not the starting point.
Logic Control & Telemetry (Pty) Ltd is a TDengine System Integrator (SI), delivering evaluation, proof-of-concept, production historian/IDMP and integration across South Africa and Africa.
Industrial AI
Context first, then intelligence
The differentiator is not that TDengine has AI features — it is that they run against an asset model and a document set describing your actual plant. Building that context is the engineering we deliver.
Start here
Industrial AI overview
How asset context, TDgpt’s in-database analysis and a language model you control divide the work between them.
Learn moreAI root cause analysis
An eight-step workflow from event to structured report — intent, asset confirmation, data retrieval over a recent window (typically the last ten days), statistical exploration, knowledge lookup, then hypotheses split out and tested against the measurements.
Learn moreAsset context & knowledge
Asset hierarchy, typed equipment relationships, and loading manuals, SOPs and failure history onto assets.
Learn morePlatform
What we deliver
Evaluation, proof-of-concept, and production TSDB + IDMP on PLC/SCADA/telemetry. Sit beside the historian you already run. PI alternative and migration when that is the path.
Historian platform
Understand TSDB + IDMP and where each fits in an OT architecture.
Learn morePI System alternative
How we evaluate PI parity on your tags — storage, assets, dashboards, Excel and events — and where PI is still the right answer.
Learn morePI migration playbook
Real-time streaming, historical backfill and phased cutover while PI stays live.
Learn moreWhat does LCT deliver with TDengine?
Logic Control & Telemetry is a South African industrial automation integrator with a dedicated TDengine Historian capability. We deploy TSDB plus IDMP on PLC, SCADA and telemetry systems — long-term tag storage, asset models, operator panels, events, and a knowledge layer from the manuals and SOPs you already have.
TDengine is AI-native. In practice that means two things sitting above storage. TDgpt runs forecasting, anomaly detection and imputation from SQL so numerical work stays in the database. IDMP adds the asset model, equipment relationships and — when you load them — indexed documents. Everyday chat and panel generation use a language model you choose; root cause analysis needs a separate deep-reasoning model on the same OpenAI-compatible connection. Our work is the context layer: without it the AI features have nothing plant-specific to reason about.
Engagement models typically include discovery workshops, bounded PoCs, asset modelling and knowledge loading, and production historian/IDMP deployment alongside our PLC/SCADA and telemetry services. If you already run a historian, we can sit TDengine beside it, and migrate later if you choose.
Frequently asked questions
Is Logic Control & Telemetry a TDengine partner?
Yes. Logic Control & Telemetry is a TDengine System Integrator (SI). We evaluate, prove and deploy TDengine Historian on South African and African plants — from a first tag ingest through dashboards, asset models and, where you need it, running beside an existing historian.
What is TDengine Historian?
TDengine Historian is an industrial data platform in two layers. TDengine TSDB stores high-frequency plant tags with long retention and ordinary SQL. TDengine IDMP sits on top: asset models, operator dashboards, events, notifications, and — if you load manuals and SOPs — a knowledge base the AI features can actually use.
What makes TDengine AI-native rather than just a database?
Storage is only the first layer. TDgpt (installed as a module) runs forecasting, anomaly detection and imputation from SQL so that numerical work stays in the database. IDMP then gives those numbers meaning: an asset model, how equipment connects, and — if you load them — your own documents attached to the assets they describe. Chat and dashboards-from-language use a language model you choose on your network. Root cause analysis uses a separate deep-reasoning model on the same OpenAI-compatible connection.
Can LCT run a proof of concept on our tags?
Yes. A typical PoC takes a bounded set of tags from PLC, SCADA or an existing historian, then shows ingest, queries, dashboards and the reports you already run. If industrial AI is in scope we also model a small asset group and load its documentation, so you can see the knowledge layer working, not just empty storage.
Book a TDengine discovery call
Share a tag list and the reports operations already run. We scope what it takes to stand up the historian and the asset model on your plant, and whether a bounded PoC comes first.