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S3 stores files. AODocs manages documents.

S3 and Azure Blob Storage keep your files durable, available and cheap, at any scale. But once your application needs to find a document, control who reads it, prove what happened to it or decide how long to keep it, you are building a document platform. AODocs is that platform, on the storage you already chose.

Why build on AODocs rather than Amazon S3?

What your application actually needs

If your application only needs to upload, store and retrieve files, object storage such as Amazon S3 or Azure Blob Storage is an excellent choice: reliable, scalable, inexpensive and easy to integrate.

If it needs to understand, organize, control, search, process and retire documents, you will build a substantial amount of software around the storage. AODocs is that software, already built: a document management platform for your application to run on, not just a place to keep files.

What your application actually needs

Document management is more than file storage

Object storage was never meant to know what a document means.

That is a design decision, not an omission.

Store and retrieve files

Amazon S3

Native

AODocs

Native, on the storage you choose

Document metadata

Amazon S3

Object tags and metadata; business metadata to build

AODocs

Structured, configurable business metadata by document type

Versions

Amazon S3

Object versioning

AODocs

Document versions, revisions and lifecycle control

Business status

Amazon S3

To build separately, in custom code

AODocs

Configurable statuses such as draft, in review, approved, obsolete

Access permissions

Amazon S3

IAM and bucket policies

AODocs

Permissions that follow the document and its workflow

Approval workflows

Amazon S3

To build separately, in custom code

AODocs

Configurable workflows

Search

Amazon S3

Object listing and metadata queries; content search through other services

AODocs

Integrated search across documents and metadata. Trusted AI features.

Audit trail

Amazon S3

AWS logging services

AODocs

Document activity and workflow history

AI

Amazon S3

AWS AI services or custom models to integrate

AODocs

Advanced AI-powered metadata extraction and document classification. Trusted answers, grounded in validated documents.

User interface

Amazon S3

To build separately, in custom code

AODocs

Ready-made interface, alongside your application

APIs for applications

Amazon S3

Extensive storage APIs

AODocs

Document-oriented APIs

The latest version is not always the right one

S3 knows which object version was uploaded last. AODocs knows which version is approved: the version in force that people and applications should use, even when a newer draft exists.
The difference matters wherever a wrong version has consequences: using the wrong contract, engineering drawing, quality procedure can cost millions.

And it matters even more when AI agents read your documents. They need the version in force, not the latest upload.



The latest version is not always the right one

Don't reinvent the wheel

Six components to build, and to keep in step

Files sit in a bucket, their metadata in an application database, permissions in IAM, approvals in a workflow service, history in logs. Each piece works. Together, they form a document system nobody designed as one.

And the documents your application creates stay outside the rules the rest of the company applies: retention, permissions, audits, enterprise search, and the sources your AI is allowed to read.

Six components to build, and to keep in step

A ready-made backend for document-centric applications

AODocs provides the document layer your application needs, through document-oriented APIs: metadata, versions, statuses, permissions, workflows, audit trail and search. The documents your application creates are governed like the rest of your AODocs content, under the same retention rules, permissions and history.

Explore the AODocs APIs →
A ready-made backend for document-centric applications
We decided to build internally, on AWS, the replacement of our legacy document management system. 18 months and 3 million dollars later, we had to give up, the projected maintenance cost were too high.

CIO

of a major Insurance company

18 months - 3 M$

to build a complete document management layer

Building each module is not the hard part. Making them work together is.

Five modules, one event

When a document is approved, its permissions change, the previous version leaves circulation, its retention period starts, the audit trail records who approved it and when, and the search index, including what your AI reads, updates. If one step fails halfway, the record can no longer be trusted.

A homegrown system has to get this right in every case, for every document type, at the scale of millions of files, with security that holds when people, rules and storage change. AODocs runs these interactions as one product, tested together and operated at scale.

And shipping the first version is the easy part. Then come years of upgrades, security patches, new regulations and staff turnover, on an internal product nobody outside your company supports.

Five modules, one event

What you won't have to build.

All the modules your application needs to manipulate documents.

Search

Full-text and metadata search across every document in scope, with results filtered by what each user is entitled to see.

When it matters: when finding a document takes longer than recreating it.

Learn more about Trusted Answers

Document sets

Folders and sets that carry their own properties, permissions and lifecycle, inherited by everything inside them.

When it matters: when a case, a project or a contract is made of dozens of documents that must behave consistently.

Learn more about Content Assembly

Retention

Retention schedules driven by business events and metadata, not by object age, with holds and defensible disposal.

When it matters: when a regulator or a court asks why a document was kept, or why it was not.

Learn more about Retention

Workflow

Review, approval and assignment paths that fit how decisions are actually made in your organization.

When it matters: when the version in force has to be unambiguous.

Learn more about AI Process Automation

Deploy anywhere

Managed deployment on the storage you choose: Google Drive, Google Cloud Storage, Amazon S3, Azure Blob Storage or SharePoint Embedded, including storage you control.

When it matters: when data residency, sovereignty or an existing cloud commitment decides where your documents must live.

Learn more about Deploy Anywhere

Integrations

Connectors for Google Workspace, Microsoft 365, SAP and Salesforce, and document-oriented APIs for everything else.

When it matters: when documents must stay in step with the business applications that create and use them.

Learn more about AODocs Integrations

API first, by design

AODocs was built as a platform, not as an application that happens to expose an API. Every capability on this page is reachable programmatically, which gives you three ways to use it.

Use it, or build on it

Use the AODocs interface as it stands, and give your business teams a working document platform on day one.

Or build your own application on top of the AODocs API, and let it handle search, metadata, permissions, retention and audit while your developers build what differentiates your business. The storage stays yours. The platform layer is ours. Your team works on the part that only your team can write.

Use it, or build on it

Give your agents something to trust

Expose document capabilities to your AI agents through MCP and A2A, so an agent retrieves the version in force rather than whatever it finds, within the permissions of the user it acts for.

An agent connected directly to a bucket reads files. An agent connected to AODocs reads documents, with their status, their metadata and their access rules, which is the difference between a plausible answer and a defensible one.

Give your agents something to trust

Storage AODocs supports

AODocs governs your documents on the storage you choose. The document layer stays the same, whatever sits underneath.

Amazon S3

Your buckets, in your AWS account.

Azure Blob Storage

Your containers, in your Azure subscription.

Google Cloud Storage

Your buckets, in your Google Cloud project.

Google Drive

Native to Google Workspace.

SharePoint Embedded

Inside your Microsoft 365 tenant.

Another storage?

Tell us about your architecture → Contact us

Before you build, four questions worth settling

Can we keep our existing bucket and container structure?

Yes. AODocs does not impose a storage hierarchy. Document sets, properties and permissions live in the platform layer, which means you can reorganize one without touching the other.

Do we need to move our data out of S3 or Azure?

No. AODocs reads from and writes to your existing buckets and containers. Your storage architecture, your region and your encryption keys stay as they are.

How is AODocs retention different from Object Lock or immutability policies?

Object Lock and Azure immutability policies compute retention from the age of the object. AODocs computes it from business events held in metadata, such as the end of a contract or the closure of a case, and applies holds, reviews and defensible disposal on that basis. The two work together: AODocs can drive the native immutability features rather than replace them.

What does the AODocs API expose?

Document and folder operations, metadata read and write, search, permission evaluation, workflow actions and audit queries. The same API serves the AODocs interface, your own applications and MCP-connected agents.

Browse all frequently asked questions

Keep your storage. Skip the build.

Tell us what your application needs to do with documents, and we will tell you honestly whether you need us.