RAG plus governed context
Living context for what changes. RAG for what sits still.
Retrieval is the right tool for large libraries that rarely change: manuals, archives, research. Knowledge that changes every week (pricing, policy, product facts, decisions) needs owners, versions and approval, or agents answer from last month's version. Most teams need both, and PromptOwl governs both.
The difference
Different jobs, side by side.
| Question | Retrieval (RAG) on its own | ContextNest |
|---|---|---|
| Best for | Large, mostly static libraries. | Living knowledge that changes and needs sign-off. |
| When a document changes | Re-index, and hope old versions are gone. | The approved version is what agents get. No re-sync. |
| Approval before use | Yours to design and build. | Built in: turn on stewardship and named owners approve changes. |
| Who sees what | Yours to build into every query. | Keys scoped to a nest, restricted documents for named people. |
| History | Whatever your storage keeps. | Every read recorded, and every version with its approver. |
| Who maintains it | Your team, for as long as it runs. | Us, with an open-source engine you can inspect. |
Choosing
When to use which.
Use RAG on its own when
- You have a large archive that rarely changes.
- Search across everything is the goal.
- Nobody needs to sign off on what's in it.
Choose ContextNest when
- The knowledge changes and agents must use the current version.
- The business needs to own and approve it.
- You need to show what was approved, and when.
Tool by tool
Every tool we compared: Enterprise platforms and context layers
Context on a hyperscaler
| The question | Amazon Bedrock Knowledge Bases with GraphRAG | AWS Context and the Context Ontology Accelerator | Microsoft IQ (Foundry IQ, Fabric IQ, Work IQ) | Google Gemini Enterprise | ContextNest |
|---|---|---|---|---|---|
| Who it's built forWho is the product made for? | Engineering teams assembling infrastructure on AWS. | Engineering teams assembling infrastructure on AWS. | Engineering teams assembling infrastructure on Microsoft 365, Fabric and Azure. | Engineering teams assembling infrastructure on Google Cloud. | The whole business: leaders, teams, engineers and their agents. |
| What it governsWhich kind of knowledge does it govern for agents? | Partly | Partly | Partly | Partly | Yes |
| Native to what you already runIs it already part of the cloud, tenant or platform you've standardized on? | Yes | Yes | Yes | Yes | No |
| Tables, metrics and data relationshipsDoes it model structured data for agents to query? | Partly | Yes | Yes | Partly | No |
| Multi-hop relationship reasoningCan agents follow relationships across many entities? | Yes | Yes | Partly | Partly | Partly |
| Search across your other appsDoes it search across the apps your company already uses? | Partly | Partly | Yes | Yes | Partly |
| A person approves firstDoes a named owner approve knowledge before AI may use it? | No | Yes | Partly | No | Yes |
| VersionedCan you rebuild what any version said, and keep old versions out of answers? | Partly | Partly | Partly | No | Yes |
| Record of readsIs there a record of who read what? | Partly | Partly | Partly | Partly | Yes |
| What you provision firstWhat has to be set up before it works? | Neptune Analytics graph, a Bedrock embedding model, an S3 data source and re-sync jobs, in your AWS account. | AWS Context is AWS-managed over S3, Redshift, RDS, DynamoDB and Glue. The accelerator runs on Neptune, OpenSearch Serverless and Bedrock. | A Microsoft 365 tenant, Fabric and OneLake for Fabric IQ, and Azure AI Foundry for Foundry IQ. | Google Cloud with a Gemini Enterprise subscription and connected data sources. | Nothing to stand up: plain files on a laptop, one Docker container on your servers, or hosted, free to start. |
| Time to first governed answerHow long until an agent answers from approved knowledge? | Partly | Partly | Partly | Partly | Yes |
| Ready-to-use UI for non-engineersCan people outside engineering read, edit, approve and ask, without a build? | No | Partly | Partly | Partly | Yes |
| Runs local, self-hosted or hostedCan the same knowledge run on a laptop, on your servers and in the cloud? | No | No | No | No | Yes |
| SSOSingle sign-on with your identity provider? | Yes | Yes | Yes | Yes | Partly |
| Open source coreIs the core open source, and can you run it without a cloud bill? | Partly | Partly | No | No | Yes |
| Server and UI licenseWhat license covers the server and interface your team uses? | Proprietary AWS service. | Proprietary managed service. The accelerator is Apache 2.0. | Proprietary, licensed with Microsoft 365, Fabric and Azure. | Proprietary subscription. | The Community server, wiki and read log are commercial: free for up to 10 users, with a free license key. |
| Ships with agents that maintain the knowledgeDo agents help keep the knowledge consistent as it changes? | No | Partly | No | No | Yes |
| Works across models and toolsCan agents on any model, and outside this platform, read it? | Partly | Yes | Partly | Partly | Yes |
| Proven at very large scaleIs it proven in very large enterprise deployments? | Yes | Yes | Yes | Yes | Partly |
| Available todayCan you buy and use it today? | Yes | No | Yes | Yes | Yes |
Scroll the table sideways. The first column stays put.
Graph and ontology platforms
| The question | Palantir Foundry Ontology and AIP | Neo4j GraphRAG and Aura Agent | ContextNest |
|---|---|---|---|
| Who it's built forWho is the product made for? | Engineering teams assembling infrastructure on Palantir Foundry. | Engineering teams assembling infrastructure on Neo4j. | The whole business: leaders, teams, engineers and their agents. |
| What it governsWhich kind of knowledge does it govern for agents? | Yes | Partly | Yes |
| Native to what you already runIs it already part of the cloud, tenant or platform you've standardized on? | Yes | Partly | No |
| Tables, metrics and data relationshipsDoes it model structured data for agents to query? | Yes | Yes | No |
| Multi-hop relationship reasoningCan agents follow relationships across many entities? | Yes | Yes | Partly |
| Search across your other appsDoes it search across the apps your company already uses? | Partly | No | Partly |
| A person approves firstDoes a named owner approve knowledge before AI may use it? | Yes | No | Yes |
| VersionedCan you rebuild what any version said, and keep old versions out of answers? | Yes | No | Yes |
| Record of readsIs there a record of who read what? | Yes | Partly | Yes |
| What you provision firstWhat has to be set up before it works? | A Palantir Foundry deployment with data pipelines into the Ontology. | A Neo4j database (Aura or self-managed) and a pipeline to load your graph and embeddings. | Nothing to stand up: plain files on a laptop, one Docker container on your servers, or hosted, free to start. |
| Time to first governed answerHow long until an agent answers from approved knowledge? | Partly | Partly | Yes |
| Ready-to-use UI for non-engineersCan people outside engineering read, edit, approve and ask, without a build? | Yes | Partly | Yes |
| Runs local, self-hosted or hostedCan the same knowledge run on a laptop, on your servers and in the cloud? | Partly | Yes | Yes |
| SSOSingle sign-on with your identity provider? | Yes | Partly | Partly |
| Open source coreIs the core open source, and can you run it without a cloud bill? | No | Yes | Yes |
| Server and UI licenseWhat license covers the server and interface your team uses? | Proprietary platform contract. | Community Edition GPLv3. Enterprise and Aura are commercial. | The Community server, wiki and read log are commercial: free for up to 10 users, with a free license key. |
| Ships with agents that maintain the knowledgeDo agents help keep the knowledge consistent as it changes? | Partly | No | Yes |
| Works across models and toolsCan agents on any model, and outside this platform, read it? | Partly | Yes | Yes |
| Proven at very large scaleIs it proven in very large enterprise deployments? | Yes | Yes | Partly |
| Available todayCan you buy and use it today? | Yes | Yes | Yes |
Scroll the table sideways. The first column stays put.
Your data platform's semantic layer
| The question | Databricks and Snowflake semantic layers | ContextNest |
|---|---|---|
| Who it's built forWho is the product made for? | Engineering teams assembling infrastructure on Databricks or Snowflake. | The whole business: leaders, teams, engineers and their agents. |
| What it governsWhich kind of knowledge does it govern for agents? | Partly | Yes |
| Native to what you already runIs it already part of the cloud, tenant or platform you've standardized on? | Yes | No |
| Tables, metrics and data relationshipsDoes it model structured data for agents to query? | Yes | No |
| Multi-hop relationship reasoningCan agents follow relationships across many entities? | Partly | Partly |
| Search across your other appsDoes it search across the apps your company already uses? | Partly | Partly |
| A person approves firstDoes a named owner approve knowledge before AI may use it? | Partly | Yes |
| VersionedCan you rebuild what any version said, and keep old versions out of answers? | Partly | Yes |
| Record of readsIs there a record of who read what? | Partly | Yes |
| What you provision firstWhat has to be set up before it works? | A Databricks or Snowflake account, your data in it, and modelled semantic objects. | Nothing to stand up: plain files on a laptop, one Docker container on your servers, or hosted, free to start. |
| Time to first governed answerHow long until an agent answers from approved knowledge? | Partly | Yes |
| Ready-to-use UI for non-engineersCan people outside engineering read, edit, approve and ask, without a build? | Partly | Yes |
| Runs local, self-hosted or hostedCan the same knowledge run on a laptop, on your servers and in the cloud? | Partly | Yes |
| SSOSingle sign-on with your identity provider? | Yes | Partly |
| Open source coreIs the core open source, and can you run it without a cloud bill? | Partly | Yes |
| Server and UI licenseWhat license covers the server and interface your team uses? | Proprietary platforms. Unity Catalog has an Apache 2.0 open-source edition. | The Community server, wiki and read log are commercial: free for up to 10 users, with a free license key. |
| Ships with agents that maintain the knowledgeDo agents help keep the knowledge consistent as it changes? | No | Yes |
| Works across models and toolsCan agents on any model, and outside this platform, read it? | Partly | Yes |
| Proven at very large scaleIs it proven in very large enterprise deployments? | Yes | Partly |
| Available todayCan you buy and use it today? | Yes | Yes |
Scroll the table sideways. The first column stays put.
Data catalogs turned context layers
| The question | Atlan and Collibra | ContextNest |
|---|---|---|
| Who it's built forWho is the product made for? | Data and engineering teams assembling governance on Atlan or Collibra. | The whole business: leaders, teams, engineers and their agents. |
| What it governsWhich kind of knowledge does it govern for agents? | Partly | Yes |
| Native to what you already runIs it already part of the cloud, tenant or platform you've standardized on? | Yes | No |
| Tables, metrics and data relationshipsDoes it model structured data for agents to query? | Partly | No |
| Multi-hop relationship reasoningCan agents follow relationships across many entities? | Partly | Partly |
| Search across your other appsDoes it search across the apps your company already uses? | Partly | Partly |
| A person approves firstDoes a named owner approve knowledge before AI may use it? | Yes | Yes |
| VersionedCan you rebuild what any version said, and keep old versions out of answers? | Partly | Yes |
| Record of readsIs there a record of who read what? | Partly | Yes |
| What you provision firstWhat has to be set up before it works? | A catalog platform connected to your data estate. | Nothing to stand up: plain files on a laptop, one Docker container on your servers, or hosted, free to start. |
| Time to first governed answerHow long until an agent answers from approved knowledge? | Partly | Yes |
| Ready-to-use UI for non-engineersCan people outside engineering read, edit, approve and ask, without a build? | Partly | Yes |
| Runs local, self-hosted or hostedCan the same knowledge run on a laptop, on your servers and in the cloud? | No | Yes |
| SSOSingle sign-on with your identity provider? | Yes | Partly |
| Open source coreIs the core open source, and can you run it without a cloud bill? | No | Yes |
| Server and UI licenseWhat license covers the server and interface your team uses? | Proprietary SaaS. | The Community server, wiki and read log are commercial: free for up to 10 users, with a free license key. |
| Ships with agents that maintain the knowledgeDo agents help keep the knowledge consistent as it changes? | Partly | Yes |
| Works across models and toolsCan agents on any model, and outside this platform, read it? | Yes | Yes |
| Proven at very large scaleIs it proven in very large enterprise deployments? | Yes | Partly |
| Available todayCan you buy and use it today? | Yes | Yes |
Scroll the table sideways. The first column stays put.
ContextNest vs Bedrock GraphRAG →ContextNest vs AWS Context →ContextNest vs Microsoft IQ →ContextNest vs Gemini Enterprise →ContextNest vs Palantir Ontology →ContextNest vs Neo4j →ContextNest vs Databricks and Snowflake →ContextNest vs Atlan and Collibra →
Last reviewed October 2026. Based on each vendor's public website and documentation, and prices show the month we checked them. Products change quickly, so check the vendor's current documentation before you decide. See something out of date? Tell us and we'll fix it.Product names and logos are trademarks of their owners; used for identification only; no endorsement or affiliation implied.
Govern what every agent is allowed to know.
Start free, connect the tools you already use, and approve the knowledge they rely on.