TwinEdge / Outcome · Keeping what people knowPlatform overview
Outcome · Keeping what people know
Keep the knowledge when the people leave.
When a 30-year operator retires, the plant loses what they "just knew" — which pump runs hot, which valve sticks, what a sound means. TwinEdge captures that behavior in the digital twin and the knowledge graph, then answers plain-language questions with the evidence behind every answer.
- 01TwinEdge OSEdge signals
- 02TwinEdge HistorianOperating history
- 03TwinEdge AIEvidence + decision
- 04TwinEdge AssetOpsPlan + dispatch
- 05TwinEdge FieldWork + verification
- 06TwinEdge Capital PlanningRenew + reinvest
The retirement cliff is a reliability risk
- 01It was never written down
The fixes that work, the machines that misbehave, and the early signs of trouble mostly live in people’s heads rather than in any system.
- 02New people take years
A new operator spends years learning what somebody else knew instantly. Until then the diagnosis is slower and the mistakes cost more.
- 03The answer depends on who is on shift
With nothing shared to refer to, the same symptom gets a different decision depending on who happens to be working.
§ 01
The retirement cliff is a reliability risk
Asset-intensive industries are losing their most experienced operators faster than they can replace them. The institutional knowledge walks out the door, and the new crew starts from a manual that never captured it.
§ 02
How TwinEdge captures and shares it
- 01Write down how it should behave
What an experienced operator learned by feel becomes an explicit model of the machine that anybody can ask questions of.
- 02Join up what is already recorded
Readings, past work, failures, and the equipment manuals are linked to the machine they belong to, so the context is in one place instead of five.
- 03Ask it a question in ordinary words
Ask why blower 2 is running hot and get an answer backed by the readings, the trend, and the section of the manual it came from.
- 04Show where every answer came from
No unexplained guesses. Each answer shows its evidence, so somebody new inherits the reasoning and not just the conclusion.
§ 03
The knowledge impact, modeled
Indicative framing for how a grounded, cited assistant changes onboarding and troubleshooting. The value scales with asset complexity and workforce turnover.1
Cited
Every answer is sourced
Twin, telemetry, history, and manuals — shown, not hidden, so answers are verifiable.
Faster
New-tech ramp
Modeled reduction in time-to-competence when veteran reasoning is captured and queryable.
Consistent
Same answer, every shift
A shared, grounded reference replaces "depends who is on tonight".
§ 04
Related capabilities
- 01Governed AI Agents
- 02API & MCP Data Products
- 03Digital Twin Engine
Capture the knowledge before it walks out the door
Connect your assets, manuals, and operating history through the TwinEdge AI package. Compare subscriptions on the pricing page.
- 1Figures are modeled projections for illustration — not measured customer results. The assistant is read-only and advisory: it explains and recommends, and never takes action without human approval.