Every contract, case and approval, on the record.

How AWS, Azure and IBM Cloud run enterprise content management

None of the big three sells one box called “ECM”. Each gives you building blocks for storing, securing, routing and understanding content, and IBM also offers a full ECM product family. Here is how each approaches the job, and where a platform like DocFlow fits.

The five jobs every ECM solution must do

1. Store files durably, with versions and retention rules.
2. Secure them with identity, encryption and an audit trail.
3. Capture and understand them: scan, extract text, classify, tag.
4. Route them through approvals and cases.
5. Integrate with the systems people already use.

Side by side

AWS: assemble from services

AWS is a toolkit. A typical design stores documents in S3, triggers a Lambda function on every upload, runs Textract to read the text, writes metadata to a database and starts a Step Functions workflow for approval. It scales very well and gives you control, but your team builds and maintains the glue, or buys an ECM product from AWS Marketplace.

Azure: extend Microsoft 365

Azure suits organizations already on Microsoft 365. SharePoint and OneDrive hold the documents, Purview applies retention and sensitivity labels, Power Automate runs approvals, and Entra ID handles sign-in. Azure Blob Storage and Document Intelligence cover large archives and automated extraction.

IBM: a complete ECM suite, now cloud-ready

IBM is the one that sells ECM as a product. FileNet Content Manager, Business Automation Workflow and Case Manager are available through IBM Cloud Pak for Business Automation, which runs on OpenShift in IBM Cloud, other public clouds or your own data center. That makes it a common choice for banks, insurers and governments with strict records requirements and existing FileNet content.

Sample architecture: contract approval on each cloud

The same five-step journey for one contract, built from each provider’s own services. Pick a cloud to see the path.

1. 1. UploadUser signs in through Cognito and uploads via API Gateway
2. 2. StoreFile lands in S3 with versioning and Object Lock
3. 3. ExtractA Lambda function calls Textract and Comprehend for text and type
4. 4. ApproveStep Functions routes to Legal, then the manager, and notifies by SNS
5. 5. AuditCloudTrail and S3 logs record each action for review

1. 1. UploadUser signs in with Entra ID and adds the file to a SharePoint library
2. 2. StoreSharePoint and Blob Storage keep versions under immutable policies
3. 3. ExtractDocument Intelligence reads fields; Purview applies a sensitivity label
4. 4. ApprovePower Automate sends approval requests in Teams and Outlook
5. 5. AuditPurview audit and Azure Monitor keep the activity record

1. 1. UploadUser signs in through IBM Cloud IAM and uses Content Navigator
2. 2. StoreFileNet Content Manager holds the document and its retention class
3. 3. ExtractDatacap captures data; watsonx can summarize clauses
4. 4. ApproveBusiness Automation Workflow runs the review and approval steps
5. 5. AuditFileNet audit logging plus Activity Tracker record the history

Which approach fits you?

Where DocFlow fits

DocFlow gives you the ECM layer as a ready service: documents, approvals, cases and audit history. It deploys on the cloud you already use, stores files in your own AWS, Azure or IBM account when you need it, and connects through APIs to the services above, such as Textract or Document Intelligence for extraction. You keep your cloud choice and skip building the workflow and records layer yourself.

Discuss your cloud plan

Product names and capabilities change often. Check each provider’s current documentation before you design.

Bring AI to your ECM content: RAG and fine-tuning

Your contracts, policies and case files hold answers your teams spend hours searching for. Two techniques put that content to work with generative AI. Retrieval-augmented generation (RAG) lets a model look up your documents when it answers. Fine-tuning teaches a model your formats and terms. We connect both to IBM FileNet, OpenText, Alfresco and DocFlow.

How each one works with an ECM system

1. 1. ConnectRead documents and their permissions from the ECM through its API
2. 2. PrepareExtract text with OCR, split it into passages and add metadata
3. 3. IndexStore embeddings in a vector index and keep it in sync with changes
4. 4. RetrieveFind the best passages, limited to what this user may see
5. 5. AnswerThe model replies with links to source documents, and the request is logged

1. 1. CollectGather approved examples, such as labeled contracts or past letters
2. 2. CleanRemove personal data, fix labels and set aside a test group
3. 3. TrainAdapt a base model to your document types, fields and wording
4. 4. TestCompare it with the base model on documents it has not seen
5. 5. DeployServe it, watch for errors and retrain when your rules change

Which one should you use?

Most projects should start with RAG. Add fine-tuning only when a specific task, such as sorting incoming mail into 40 document types, needs more accuracy than prompts and retrieval can give.

What teams build first

Tools we use on each platform

Safeguards that matter in regulated work

• Permission-aware answers: the model only sees documents the asking user may open.
• Citations on every answer: reviewers can check the source in one click.
• Human approval: AI drafts and suggests, and a person approves in the workflow.
• Audit trail: questions, retrieved documents and answers are logged like any other record.
• Data control: your content stays in your chosen region and is not used to train public models.

Plan an AI pilot

Service names and features change often. Confirm current capabilities with each provider.

How Claude works with your ECM system

Claude is an AI assistant from Anthropic. It reads long documents, understands what they say and can use tools. Connected to your ECM, it lets people ask for what they need in plain language, then searches, reads and drafts for them while your system keeps control of access and records.

What Claude does with ECM content

What an interaction looks like

1. 1. AskA user types a question in chat, Teams or the DocFlow app
2. 2. PlanClaude decides which ECM searches or tools it needs
3. 3. RetrieveThe ECM returns only documents this user is allowed to see
4. 4. AnswerClaude reads them and replies with citations or structured output
5. 5. ApproveA person confirms any change; the ECM records it in the audit trail

Illustrative example.

Ways to connect Claude to an ECM

Guardrails we put around Claude

• Least privilege: Claude starts with read-only access and acts as the signed-in user, never as an administrator.
• Human approval for changes: edits, deletions and sends wait for a person to confirm.
• Full logging: requests, tools called and documents read are recorded with your other audit data.
• Source links: factual answers point back to the documents, so reviewers can check them.
• Testing before launch: we run your real questions and edge cases, and measure accuracy first.

See Claude with your content

Claude is a product of Anthropic. World Cloud Services LLC is an independent company and builds integrations; it is not affiliated with Anthropic, IBM, OpenText or Alfresco. Confirm current Claude features, availability and data terms in Anthropic’s documentation.