Fujifilm Data Management Solutions

Fujifilm Content AI

Increase efficiency and reduce operational costs by applying AI assisted capture, classification, extraction and quality control across your document and content workflows.

A practical and governed approach to Content AI

Content AI uses AI‑powered document understanding that combines machine learning, natural language processing and rules‑based logic with confidence scoring to interpret, classify and structure content within governed workflows.

This approach enables increased automation with appropriate oversight while improving accuracy, consistency and throughput with processing steps remaining transparent, controlled and auditable for review and assurance.

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Business Need

When Content AI is needed

Many organisations struggle with high volumes of documents that vary in format, quality and structure. Manual checking, rework and exception handling slow down processing, increase costs and introduce risk.

Content AI addresses these challenges by reducing repetitive manual effort and improving accuracy across large digitisation and document processing programmes while maintaining appropriate control where outcomes matter.

What Content AI means for your organisation

Content AI combines intelligent document processing capabilities with governed workflows, enabling your organisation to move beyond digitisation towards trusted operational use of content and data.

In practice, it can be applied at different depths depending on the outcome required. It may be used to improve text quality, accessibility and searchability in digitisation and preservation work, such as producing high-quality searchable PDF or PDF/A, or to support governed workflows where validation, review and integration into core systems are required.

This flexibility allows organisations to apply AI where it delivers value, while maintaining appropriate control for higher-risk or regulated use cases.


Applied intelligence across the workflow

Content AI is applied across key stages of document processing, supporting the preparation of documents and data for operational use. Capabilities can be applied individually or combined based on document type, process requirements, risk profile and the intended use of the outputs.

This approach allows organisations to scale document handling across high-volume and mixed document environments while maintaining consistency, oversight and control.


Governed automation with operational accountability

Automation is controlled through defined rules, confidence thresholds and review pathways that align processing decisions with operational risk. Outputs can be accepted automatically where confidence is high or routed for validation where risk or variability requires oversight.

This approach supports faster throughput without replacing accountability or introducing excessive automation in sensitive processes.


Designed for scale without loss of control

Content AI is designed to support repeatable, measurable outcomes as processing volumes grow. Controls can be tuned by document type, business rules and risk profile to maintain accuracy and oversight while reducing avoidable manual effort.

This enables scale across large document programs while preserving transparency and traceability.

at a glance

Core Content AI capabilities

Content AI brings together a set of capabilities that support controlled document understanding and processing. Each capability can be applied independently or combined depending on document type, workflow requirements and risk profile.

Intelligent document capture

Capture and ingest content from physical and digital sources, with preparation steps that improve readability and consistency before processing begins. This supports mixed inputs such as scanned records, PDFs, images and legacy files.

AI-powered classification

Automatically identify document types and group content based on structure and patterns. Classification supports routing decisions and ensures different document types follow the right processing and validation path.

Data extraction and validation

Extract fields, identifiers and metadata and normalise outputs into structured formats suitable for indexing and downstream use. Validation controls can be applied at document and field level to reduce errors and exceptions.

Human review and validation

Support structured review where confidence is low or where content carries higher operational or compliance risk. Review workflows allow outcomes to be verified, corrected and approved without disrupting overall throughput.

Workflow automation

Apply rules, routing logic and thresholds to move content through defined steps. This supports consistent handling across large volumes, while allowing exception pathways when outputs fall below required confidence.

PII detection and redaction

Identify sensitive personal information and apply redaction controls where required by policy and use case. This supports safer handling of documents used for sharing, analysis or broader access.

Video and audio content intelligence

Apply AI-assisted transcription, summarisation and language processing to audio and video content, enabling searchability, review and reuse within governed enterprise workflows.

Output preparation and normalisation

Prepare processed content and extracted data into consistent, structured outputs suitable for storage, search, records handling and system integration.

Intelligent Document Processing shows how Content AI is applied across OCR, classification, extraction and validation within governed document workflows.

View Intelligent Document Processing

How Content AI works

Content AI follows a controlled workflow designed to support consistent outcomes at scale. Documents move through capture, classification, extraction and validation with review triggered where required before outputs are prepared for operational use. Governance is applied throughout to manage quality and risk.

From documents to structured outputs

While digitisation focuses on converting content into digital form, Content AI extends this process by applying intelligence, validation and governance to prepare documents and data for operational use.

For a deeper look at how these stages are executed for document-based workflows, see Intelligent Document Processing.

Capture

Documents are ingested from physical and digital sources, including scanned records, PDFs, images and electronic submissions. Basic preparation can be applied to improve readability and ensure content is ready for processing.

Classify

Documents are analysed to identify type, structure and content patterns. Classification supports routing decisions and ensures each document follows the right processing path, including when mixed document batches are handled together.

Extract

Relevant text, fields, identifiers and metadata are extracted based on document type and processing requirements. Extraction outputs are normalised into structured formats so information can be used consistently downstream.

Validate

Rules and confidence scoring are used to assess output reliability. Results that meet thresholds can proceed while low confidence outputs are flagged for review to protect accuracy in higher risk or higher impact use cases.

Review

Where review is triggered, validation and correction are completed through controlled workflows. Human actions can be captured alongside automated outcomes to support accountability and auditability.

Output

Processed documents and extracted data are prepared for operational use supporting storage, search, records handling and system integration. Outputs may include searchable PDF or PDF/A and structured data formats such as JSON or XML.

CONTENT AI IN PRACTICE

Where Content AI is applied in practice

Content AI is embedded across Fujifilm DMS digitisation and document services, supporting high-volume, high-risk and compliance-driven workflows. Capabilities are applied selectively based on document type, process requirements and risk profile, ensuring automation is introduced where appropriate while maintaining oversight and auditability.

These use cases reflect common document and content challenges where accuracy, volume and compliance requirements make manual or basic automation impractical.


Inbound document digitisation and intake

Content AI supports the initial intake and triage of physical and digital documents, enabling faster routing and processing from the point of receipt.

  • Automatically identifies document types, formats and structures at scale
  • Reduces manual handling during early intake stages
  • Improved access to information previously stored in paper archives
  • Supports hybrid physical and digital submission channels


Records and archive digitisation

For legacy records, archives and long-term collections, Content AI assists with structuring and preparing content for compliant storage and access.

  • Identifies record classes and document groupings
  • Extracts key metadata to support indexing and retrieval
  • Produces structured outputs such as searchable PDF/A and metadata files
  • Supports records management, retention and compliance requirements
Content AI at Fujifilm DMS


Back-scanning and legacy document conversion

Content AI helps modernise large volumes of historical or paper-based material by converting it into structured, usable digital content.

  • Analyses inconsistent or ageing document formats
  • Normalises outputs for downstream systems and repositories
  • Improves searchability and reuse of legacy information
  • Reduces reliance on manual data preparation and rework


Ongoing document processing and enrichment

Beyond initial digitisation, Content AI supports continuous processing where documents are regularly received, updated or reused.

  • Enriches content with structured metadata and identifiers
  • Applies validation rules and confidence scoring to outputs
  • Supports downstream analytics, reporting and workflow automation
  • Enables controlled updates without reprocessing entire document sets


Exception handling and quality assurance workflows

Where automation confidence thresholds are not met, Content AI enables structured review and exception management.

  • Routes low-confidence outputs to human reviewers
  • Supports traceable review, correction and validation steps
  • Captures quality metrics to support continuous improvement
  • Maintains audit trails for regulated environments


System integration and downstream use

Processed content is prepared for integration into enterprise systems, reducing friction between digitisation and operational use.

  • Outputs structured data suitable for indexing, search and system ingestion
  • Supports integration with content management, line-of-business and analytics platforms
  • Reduces manual hand-offs between digitisation and operational teams
  • Enables scalable use of digitised content across the organisation

Governance, assurance and operational control

Built for regulated environments, automation is governed through defined rules, confidence thresholds and human review controls, enabling transparent and auditable decision-making across the document lifecycle.


Confidence-led automation, not blind processing

Automation is guided by confidence scoring and defined thresholds, ensuring AI supports human decision-making rather than replacing it. Outputs that meet confidence requirements can be processed automatically, while lower-confidence results are routed into structured review workflows. Thresholds can be adjusted based on document type and risk profile, preventing over-automation in sensitive or high-impact processes.


Human review and quality assurance

Human oversight remains integral to Content AI workflows, particularly where documents carry legal, financial or regulatory significance. Review and validation steps are embedded directly into processing flows, with corrections and approvals captured in a traceable and auditable way. Quality metrics are used to refine models over time while maintaining operational assurance.


Auditability, traceability and compliance alignment

Content AI outputs are designed to support downstream compliance, records management and governance requirements. Processing decisions and changes are traceable across the document lifecycle, with outputs aligned to retention and records frameworks. This provides confidence in how content is processed, classified and used across government and enterprise environments.


Scalable by design, without loss of control

Content AI is designed to operate at scale while maintaining governance, visibility and operational control. High-volume processing can be supported across diverse document types without introducing unmanaged risk, enabling organisations to scale automation while preserving consistency, accountability and oversight.

These governance controls are implemented through a defined, event-driven technical architecture designed for scale, auditability and integration.

View Content AI technical architecture

Talk to us about your Content AI requirements

If you’re exploring how Content AI can support digitisation, preservation, document processing or governed workflows, share a few details below. We’ll review your requirements and get in touch to discuss the most appropriate approach for your organisation.

Industries We Serve

Our industry expertise and solutions

Fujifilm DMS can support any industry that needs to communicate frequently with customers across multiple channels, physical or digital. Whether you’re sending or receiving information or engaging with customers online, we’re here to help.