The datasheet states a maximum operating temperature of 85 °C. The current customer specification says 80 °C. And an internal test report recommends running the component continuously at no more than 75 °C.
Which figure applies?
A quick information search could turn these three values into an answer that looks clear-cut. For a technical approval, that would be dangerous. The discrepancy is not a matter of wording. It can decide whether a product may be operated safely, whether it meets a customer requirement or whether a design has to be reworked.
This is exactly the kind of question High Precision Mode in MAIA is for. It is designed for situations in which an answer must not just sound helpful but must be verifiable against the original documents.
What is High Precision Mode?
High Precision Mode is a dedicated analysis mode for document-based queries in MAIA. While the standard mode brings information together quickly and produces a compact answer, High Precision Mode examines the underlying statements more critically.
To do this, MAIA breaks an answer down into individual verifiable statements and checks them against the selected documents. Relevant passages are referenced directly. If sources contradict each other, the conflict is made visible instead of being smoothed over in a summarising sentence.
The mode combines four functions:
Precise source references. Key statements are linked to specific passages in the original documents. This lets you trace which file, version or passage a piece of information comes from.
Active contradiction detection. Differing values, requirements or assessments are not quietly merged. MAIA shows which documents disagree with each other.
Assessment of the information base. High Precision Mode takes into account how reliable a source appears in the given context. A current, approved specification, for example, carries a different weight from an older presentation or an informal project note.
In-depth analysis. The documents are not simply summarised. MAIA examines the relationships between statements, compares versions and points out gaps or uncertainties.
The result is not an infallible machine decision. It is a transparently prepared basis for decisions that specialists can check much faster.
Why is a standard AI chat often not enough in industry?
Generative AI is trained to produce linguistically coherent answers. That is very useful for drafts, summaries or first ideas. In technical and regulated processes, however, it creates a fundamental problem: an answer that is convincingly worded can still be incomplete, out of date or wrongly weighted.
In industry, the question is often not just what a document says. It is just as important to know:
- Which version says it?
- Is the document still valid?
- Is there a conflicting requirement?
- Is it a binding requirement or a recommendation?
- Which original passage is the statement based on?
- What information is missing for a final assessment?
Anyone who approves a design, assesses a deviation for a customer or prepares audit evidence cannot rely on how plausible an answer sounds. The professional responsibility stays with people. For them to exercise it, the way the answer was derived has to be visible.
High Precision Mode does not replace this responsibility. It does, however, reduce the effort needed to trace a statement back to its source.
A typical case from practice
A project engineer has to check whether a new pump unit meets a customer’s requirements. Several documents are available:
- the customer’s requirements specification,
- the internal product datasheet,
- a design guideline,
- two test reports,
- an older set of approval documentation,
- the current assembly instructions.
In standard mode, MAIA can first produce a quick overview: What requirements does the specification contain? Which product features are relevant? Where might the critical points be?
For the subsequent review, the engineer activates High Precision Mode and asks:
“Compare the permissible pressure and temperature ranges in the customer requirements specification with the current product datasheet and the internal test reports. Show all deviations and give the exact passage for every statement.”
MAIA might now find, for example, that the datasheet specifies an operating pressure of 16 bar, while a test report rates the seal used only up to 14 bar. Instead of producing a supposedly fitting average or a simplified statement, High Precision Mode sets both figures side by side with their sources.
The engineer sees immediately where technical clarification is needed. She does not first have to search through several hundred pages to find the conflicting values.
Why contradictions can be more valuable than a clear-cut answer
In many industrial knowledge bases, there is no single perfect truth. Documentation has grown over years. Product variants have been changed, standards updated and lessons from projects only partly carried over into the official documents.
This leads to differences between:
- old and new document versions,
- sales material and technical specification,
- customer requirement and internal standard,
- test report and product datasheet,
- approved documentation and actual project experience.
A system that insists on giving a clear-cut answer can hide such differences. For industrial decisions, it is often more helpful to know precisely that a conflict exists.
High Precision Mode therefore does not treat a detected contradiction as a failure of the analysis. It makes it the result. Only then can specialists decide which document is authoritative, whether information needs updating or whether an approval must not yet be granted.
Where industry needs High Precision Mode
The mode is particularly valuable where mistakes have high knock-on costs or where decisions have to be explained later.
Technical specification review
Customer requirements specifications, internal standards and product data often contain hundreds of requirements. High Precision Mode helps to compare limit values, tolerances and material requirements and to document deviations together with the relevant passages.
Quality management and approvals
Before a product, process or document is approved, the information has to be consistent. MAIA can compare different documents and point out values or statements that do not match. The final assessment remains with the responsible quality team.
Standards and regulatory requirements
In regulated industries, it must be possible to trace which rule a requirement was derived from. Answers tied to sources make it easier to prepare for audits and to check whether internal documents comply with the relevant regulations.
Research and development
In technical research, findings from papers, patents, test reports and internal projects have to be considered together. How this works with large volumes of documents is also shown in the article AI research for engineers: 200 papers in minutes.
High Precision Mode helps above all with the final review: Which finding is supported by which source? Are there studies or internal results that come to a different assessment?
Quotation and contract review
An overlooked customer requirement can later lead to renegotiations, delays or unplanned development costs. A review across documents makes it possible to check technical commitments against internal specifications and existing evidence.
Preserving experiential knowledge
Industrial knowledge rarely sits in a single, well-maintained handbook. It is spread across test reports, project documents and records of past decisions. The article AI knowledge management in industry describes why this knowledge is at risk of being lost, especially when experienced specialists leave.
Answers tied to sources ensure that this knowledge is not only findable but also remains verifiable in its original context.
Precision takes more time
High Precision Mode deliberately answers more slowly than the standard mode. That is not a drawback but the result of the additional checking.
Not every query needs this effort. For brainstorming, first summaries or quick orientation, the standard mode is usually the better choice. High Precision Mode should be used when the result is meant to serve as the basis for a technical, regulatory or commercially relevant decision.
In practice, a two-step approach works well:
- In standard mode, explore the documents, narrow down the question and create an initial overview.
- In High Precision Mode, check the decisive statements, values and contradictions against the relevant original documents.
This way, not every conversation is slowed down unnecessarily. The additional checking happens exactly where it makes a real difference.
What companies should prepare for reliable results
Even the most precise analysis mode can only work with the documents available to it. If an authoritative specification is missing or an outdated version has been selected, the information base remains incomplete.
Before a critical review, teams should therefore clarify:
- Are all relevant documents available?
- Have the right versions been selected?
- Is it clear which documents are approved or binding?
- Is the question clearly defined in technical scope and time frame?
- Have known reference standards and internal standards been included?
High Precision Mode can make contradictions visible. But it cannot know that a decisive document is missing if that document has neither been selected nor referenced in the existing material.
This also makes one thing clear: good use of AI is not just a question of the model. It depends just as much on the data, processes and responsibilities. Why many AI projects fail at exactly this transition from interesting pilot project to dependable working tool is described in the article AI adoption in mid-sized companies: What happens after the pilot project.
From a quick answer to a verifiable working basis
Industry does not need AI just to produce text faster. It needs systems that can handle technical documents, different versions and conflicting requirements.
High Precision Mode in MAIA is designed for exactly those moments when “sounds right” is not enough. It links statements to their original sources, shows deviations openly and makes uncertainties visible.
This shifts the role of AI: it does not simply deliver a finished decision. It prepares the existing knowledge so that specialists can decide faster, in a more targeted way and with better documentation.
Because in a safety-critical approval, a check against standards or a binding commitment to a customer, the answer alone is not what counts.
What counts is whether it can be backed up.
