S3 stores files. AODocs manages documents.
Keep S3. Add the layer that knows which version is in force, who can see it and how long to keep it. AODocs runs on the buckets you already have, so nothing moves.
Three needs S3 alone cannot meet
S3 keeps every file durable and inexpensive. It does not know what a file is, who should see it or what happened to it. These three needs are where that gap shows.
You need authoritative answers from your AI
An assistant connected to a bucket reads everything in it: old drafts, superseded revisions, a confidential board memo from five years ago. AODocs gives it only the version in force, within the permissions of the person asking, with the source cited.
Learn more about Trusted Answers
You need to work with suppliers and customers
Contracts, specifications and certificates go back and forth with people outside the company. On S3 alone, that means presigned links and copies nobody tracks. AODocs gives each partner controlled access to the documents of the process, with their versions and approvals, and nothing leaves your control.
Learn more about the Document Control.
You need to prove what happened to a document
When an auditor, a regulator or a client asks who approved which revision, and when, S3 access logs only show who opened a file. AODocs keeps one traceable record per document: reviews, approvals, versions and retention, under the procedure that applied.
Learn more about Legacy Replacement.
Why build on S3 with AODocs, rather than on S3 alone?
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.
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.
| Capability | S3 alone | S3 with AODocs |
|---|---|---|
| Store and retrieve files | Native | Native, on the storage you choose |
| Document metadata | Object tags and metadata; business metadata to build | Structured, configurable business metadata by document type |
| Versions | Object versioning | Document versions, revisions and lifecycle control |
| Business status | To build separately, in custom code | Configurable statuses such as draft, in review, approved, obsolete |
| Access permissions | IAM and bucket policies | Permissions that follow the document and its workflow |
| Approval workflows | To build separately, in custom code | Configurable workflows |
| Search | Object listing and metadata queries; content search through other services | Integrated search across documents and metadata. Trusted AI features. |
| Audit trail | AWS logging services | Document activity and workflow history |
| AI | AWS AI services or custom models to integrate | Advanced AI-powered metadata extraction and document classification. Trusted answers, grounded in validated documents. |
| User interface | To build separately, in custom code | Ready-made interface, alongside your application |
| APIs for applications | Extensive storage APIs | Document-oriented APIs |
Store and retrieve files
S3 alone
Native
S3 with AODocs
Native, on the storage you choose
Document metadata
S3 alone
Object tags and metadata; business metadata to build
S3 with AODocs
Structured, configurable business metadata by document type
Versions
S3 alone
Object versioning
S3 with AODocs
Document versions, revisions and lifecycle control
Business status
S3 alone
To build separately, in custom code
S3 with AODocs
Configurable statuses such as draft, in review, approved, obsolete
Access permissions
S3 alone
IAM and bucket policies
S3 with AODocs
Permissions that follow the document and its workflow
Approval workflows
S3 alone
To build separately, in custom code
S3 with AODocs
Configurable workflows
Search
S3 alone
Object listing and metadata queries; content search through other services
S3 with AODocs
Integrated search across documents and metadata. Trusted AI features.
Audit trail
S3 alone
AWS logging services
S3 with AODocs
Document activity and workflow history
AI
S3 alone
AWS AI services or custom models to integrate
S3 with AODocs
Advanced AI-powered metadata extraction and document classification. Trusted answers, grounded in validated documents.
User interface
S3 alone
To build separately, in custom code
S3 with AODocs
Ready-made interface, alongside your application
APIs for applications
S3 alone
Extensive storage APIs
S3 with 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.
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.
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.
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.
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.
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.
Storage AODocs supports
AODocs runs on the storage you already chose. Your account, your buckets, your encryption keys stay yours.
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 does AODocs retention work with Object Lock and 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.
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.