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FAQ

1. What kind of product is Prodia?​

Prodia is:

an AI reasoning and decision system for manufacturing operations

Its core value is organizing process, equipment, parameter, indicator, and anomaly context into operational judgment that teams can act on.

2. How is Prodia different from traditional BI?​

Traditional BI is strong at fixed dashboards and reports. Prodia emphasizes:

  • forming operational judgment around site issues
  • organizing coordinated reasoning across rules, knowledge, cases, and models
  • producing suggested actions, priorities, and supporting evidence
  • tracking adoption and outcome improvement

In one line, BI is stronger at “seeing,” while Prodia is stronger at “getting results.”

3. How is Prodia different from general AI or a general Copilot?​

General AI is good at searching, summarizing, and answering general questions. Prodia is built to solve manufacturing-site questions such as:

  • understanding processes
  • understanding equipment
  • understanding parameter shifts
  • understanding indicator fluctuation
  • understanding anomaly impact

Its outputs include:

  • adjustment direction
  • investigation priority
  • optimization guidance
  • handling action
  • result evidence

4. Does Prodia replace AI SCADA, MES, or execution systems?​

Prodia works as a reasoning and decision-support layer above those systems.

Existing systems preserve process flow and operational facts. Prodia turns those facts into more action-oriented judgment and guidance.

5. What kinds of problems fit Prodia best?​

The best-fit scenario groups are:

  • process optimization: stabilize new specifications faster, decide how to set parameters, tune curves, and choose recipes
  • operational efficiency optimization: explain why output, unit consumption, and takt deteriorate and what to optimize first
  • equipment efficiency optimization: interpret fluctuation, investigate alarms, and identify which assets require earlier intervention

Yes. It provides:

  • cause candidates
  • priority judgment
  • recommended actions
  • key evidence
  • applicability conditions and confidence hints

7. Will Prodia replace engineers in decision-making?​

Prodia helps engineers form judgment faster while final execution responsibility remains with engineers.

The normal collaboration model is:

  • the system organizes data, knowledge, cases, and reasoning
  • the system outputs recommended actions and evidence
  • engineers decide whether to adopt, how to execute, and how to validate the result

8. How does Prodia improve the accuracy and trustworthiness of AI results?​

Accuracy does not come from “guessing correctly.” It comes from:

  • structuring the question first
  • decomposing the task before tool invocation
  • using governed MCP-based queries rather than free-form SQL
  • generating conclusions from evidence rather than from free-form guessing
  • recording adoption and outcomes to keep calibrating rules and recommendation logic

In one sentence, accuracy comes from:

asking precisely, querying correctly, grounding in evidence, validating, and feeding results back.

9. Why does the system sometimes ask clarifying questions first?​

Because the same sentence in manufacturing may imply different objects, time definitions, or analytical grain.

For example:

  • are we talking about the entire line, one process, or one piece of equipment
  • does “yesterday” mean calendar day or shift day
  • do you want a summary or a breakdown

The system asks first so it can answer correctly later.

10. What data sources can Prodia work with?​

Typical inputs include:

  • real-time equipment data
  • control and process data
  • quality and inspection data
  • energy and resource data
  • maintenance data
  • business and planning data
  • documents, cases, rules, and review knowledge

The actual scope depends on project boundaries.

11. Is AI SCADA mandatory?​

No. What matters is whether the site already has:

  • object mapping
  • usable core metric definitions
  • key event and parameter data
  • usable knowledge and experience materials

12. Does Prodia support private deployment?​

Yes. Private and intranet deployment are common for manufacturing users.

It also supports:

  • controlled model access
  • data-in-domain deployment
  • role and business-domain isolation
  • logging and governance

13. Why are customers willing to pay for Prodia?​

Because they are buying more stable production results and clearer ROI.

The most direct gains are usually:

  • stabilizing new specifications faster
  • recognizing fluctuation and equipment risk earlier
  • reducing dependency on a small number of experts
  • improving output, takt, OEE, unit consumption, and equipment performance more steadily

14. Where is the value most visible?​

It is most visible in four areas:

  • higher people efficiency and expert capability reuse
  • more stable indicator improvement
  • lower anomaly and operational loss
  • stronger experience replication and organizational compounding

15. Why does Prodia get stronger with use?​

Because it does not only give one-time recommendations. It keeps learning:

  • which issues deserve priority
  • which parameter changes work better
  • which recommendations are adopted
  • which actions actually improve results

As usage deepens, the system becomes more specific to the line, process, and operating condition.

16. What kinds of responsibilities should not be given to Prodia?​

The following are outside its standard responsibility boundary:

  • millisecond-level low-level control
  • safety interlock and shutdown logic
  • high-risk execution without human confirmation

Those responsibilities still belong to PLCs, DCS, equipment controllers, or validated safety systems.

17. Will the Agent access all underlying data arbitrarily?​

No. Prodia emphasizes analysis within authorized governance boundaries through:

  • tool whitelisting
  • parameter constraints
  • permission control
  • output traceability
  • audit logging

This is how it reduces misuse and overreach risk.

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