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Platform module

AI Modules

Combine document, image, speech, sensor and knowledge processing. Turn different source formats into usable, source-linked data.

AI processing modules

  • Document reading and extraction
  • Image and video review
  • Speech and speaker separation
  • Sensor and time-series processing
  • Enterprise knowledge retrieval

Scope

Its role in the system.

Inside the application

Application workflow

Selected use cases, source information and operational outputs.

Source processing

Documents, images, speech and field data require different processing methods. Components are selected for the source type and application needs.

AI ModulesScenario / 01
Interface conceptSchematic example

Source processing

Schematic field, not a real location
Document
Image
Speech
Field data
Decision boundary

Source access, action scope and human review are configured for the application.

  • Document, image, speech or field source
  • Task definition
OutputResult processed for the source data type

Structured output

Fields extracted from source pages are organized into a usable schema. Their source links are retained for validation and correction.

AI ModulesScenario / 02
Interface conceptSchematic example

Structured output

Text + image
Structured information
Source page
Extracted field
Validation
Source linkage
Decision boundary

Source access, action scope and human review are configured for the application.

  • Source page
  • Field schema and validation rules
OutputStructured fields with source links

Result review

A model result is not a decision by itself. Its source interval and uncertainty provide context for expert review.

AI ModulesScenario / 03
Interface conceptSchematic example

Result review

Model outputSource-linked
Source interval
Review context

Uncertainty

Expert decision

Source and interpretation remain separate.
Decision boundary

Source access, action scope and human review are configured for the application.

  • Model output
  • Source and uncertainty information
OutputEvidence package ready for expert review
01 / INPUT

Documents, images, speech or field data

Source identity and access scope remain part of the work.

02 / PROCESS

Processing matched to the data type

The module operates within the configured application and control boundaries.

03 / OUTPUT

Source-linked structured result

The next step uses the result with its source and execution context.

Control design

Progress, exceptions and decisions.

Reference behavior for implementation; each deployment needs its own configuration and verification.

Result produced

Present a field, event or transcript alongside its source page, frame or time interval.

Insufficient source information

Do not present unreadable or conflicting fields as completed results. Make the relevant source available for review.

Expert review

Separate model output from expert judgment. Select processing according to the data type and application scope.

01

Documents and text

OCR, layout analysis, extraction, classification and cross-checking form a document pipeline. Outputs retain source-page or field references.

02

Media and speech

Visual findings link to frames; transcripts and speakers link to time intervals. Events can be organized into evidence packages for review.

03

Field data and retrieval

Time-series checks, event matching and source-linked enterprise search are configured for the solution. Availability depends on product and pilot scope.

Technical operating model

Different data needs different processing

A scanned document, video segment and sensor reading are not the same kind of input. AI Modules covers processing paths that retain the source markers of each data type. Fields link to pages, statements to time, and measurements to method and location.

Component relationship / schematic

Documents and text

Layout, OCR, field extraction and cross-checking.

Media and speech

Preserve frame, event segment, transcript and speaker relationships.

Field and enterprise information

Time-series validation and source-linked retrieval.

01

Connecting it to an application

Define incoming data, resulting records and the people or systems that use them together. A functioning component alone is not an acceptance criterion for the entire workflow.

02

Checking a change

When a schema, tool or model changes, existing use cases are tested again. Errors, permissions and human-review paths matter as much as successful execution.

Components and operating approach

Different data needs different processing

Select a topic to explore the relationships between information, responsibility and delivery.

01

Documents and text

Layout, OCR, field extraction and cross-checking.

  1. 01Documents and text
  2. 02Media and speech
  3. 03Field and enterprise information
Document trace
Page + field
Media trace
Time + speaker
Measurement trace
Location + method + unit
02

Media and speech

Preserve frame, event segment, transcript and speaker relationships.

  1. 01Documents and text
  2. 02Media and speech
  3. 03Field and enterprise information
Document trace
Page + field
Media trace
Time + speaker
Measurement trace
Location + method + unit
03

Field and enterprise information

Time-series validation and source-linked retrieval.

  1. 01Documents and text
  2. 02Media and speech
  3. 03Field and enterprise information
Document trace
Page + field
Media trace
Time + speaker
Measurement trace
Location + method + unit

An operating-model illustration, not live operations or measured performance results.

Connected modules

Explore the rest of the platform.

Data management

Data House

A shared data foundation for documents, media and enterprise records. Preserve identity, versions and permissions across retrieval and AI operations.

Explore the module ↗Workflow orchestration

Orchestrator

Coordinate models, tools and people within the same operation. Preserve state and manage errors, retries and review across long-running work.

Explore the module ↗Enterprise integration

WebKit

Connect defined operations in ERP, CRM and enterprise applications to AI workflows, with clear input, output and access boundaries.

Explore the module ↗Human review and execution history

Sessions + HITL

Keep sources, processing steps and human decisions together. Give responsible users the context needed to review an outcome.

Explore the module ↗Model evaluation and adaptation

Model Adaptation

Prepare evaluation and training data from verified examples. Compare changes on consistent tasks and track model versions.

Explore the module ↗

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