Add a Vector Store

1

Open Qdrant

Click the Qdrant card.

2

Enter the connection details

Name for the integration.
Qdrant URL, for example your-project.europe-west3-0.gcp.cloud.qdrant.io:6333.
API Key. Required for Qdrant Cloud, optional for local Qdrant.

3

Add collections

Click Fetch Collections and enable the ones you want, or add a collection by name (lowercase letters, numbers, and underscores).

4

Set an embedding config

Pick an embedding config for each collection. It must match the model that created the vectors.Don’t have one yet? Open the embedding config picker and click Create New.

Enter a Name, pick a Provider, and set the Model Name and Dimension to match the model that created your vectors. Add an API Key if the provider needs one, then save.

5

Save

Click Create Integration. Raily then configures agentic search for each collection automatically. This can take a few minutes, after which the integration appears under My Integrations with an Active status.

Once it finishes, open Inventory → Data Catalog to see the generated configuration for each collection.

6

See it in the Data Catalog

After generation finishes, Raily opens the collection in Data Catalog.

Collection configuration in the Data Catalog

1

Open Pinecone

Click the Pinecone card.

2

Enter the connection details

Name for the integration.
API Key from your Pinecone console.

3

Add indexes

Click Fetch Indexes and enable the ones you want. Each enabled index needs its Index Host URL, which Raily fills in from Pinecone.

4

Set an embedding config

Pick an embedding config for each index. It must match the model that created the vectors. If embeddings are server-generated, set the config to built-in.Don’t have one yet? Open the embedding config picker and click Create New.

Enter a Name, pick a Provider, and set the Model Name and Dimension to match the model that created your vectors. Add an API Key if the provider needs one, then save.

5

Save

Click Create Integration. Raily then configures agentic search for each collection automatically. This can take a few minutes, after which the integration appears under My Integrations with an Active status.

Once it finishes, open Inventory → Data Catalog to see the generated configuration for each collection.

6

See it in the Data Catalog

After generation finishes, Raily opens the collection in Data Catalog.

1

Open Zilliz

Click the Zilliz card.

2

Enter the connection details

Name for the integration.
Cluster endpoint URL, for example your-cluster.serverless.gcp-us-west1.cloud.zilliz.com.
API Key for your Zilliz Cloud cluster.

3

Add collections

Click Fetch Collections and enable the ones you want, or add a collection by name (start with a letter or underscore; letters, numbers, and underscores).

4

Set an embedding config

Pick an embedding config for each collection. It must match the model that created the vectors.Don’t have one yet? Open the embedding config picker and click Create New.

Enter a Name, pick a Provider, and set the Model Name and Dimension to match the model that created your vectors. Add an API Key if the provider needs one, then save.

5

Save

Click Create Integration. Raily then configures agentic search for each collection automatically. This can take a few minutes, after which the integration appears under My Integrations with an Active status.

Once it finishes, open Inventory → Data Catalog to see the generated configuration for each collection.

6

See it in the Data Catalog

After generation finishes, Raily opens the collection in Data Catalog.

1

Open Milvus

Click the Milvus card.

2

Enter the connection details

Name for the integration.
Cluster endpoint URL, for example milvus.your-company.com.
API Key. Optional for self-hosted Milvus.

3

Add collections

Click Fetch Collections and enable the ones you want, or add a collection by name (start with a letter or underscore; letters, numbers, and underscores).

4

Set an embedding config

Pick an embedding config for each collection. It must match the model that created the vectors.Don’t have one yet? Open the embedding config picker and click Create New.

Enter a Name, pick a Provider, and set the Model Name and Dimension to match the model that created your vectors. Add an API Key if the provider needs one, then save.

5

Save

Click Create Integration. Raily then configures agentic search for each collection automatically. This can take a few minutes, after which the integration appears under My Integrations with an Active status.

Once it finishes, open Inventory → Data Catalog to see the generated configuration for each collection.

1

Open Weaviate

Click the Weaviate card.

2

Enter the connection details

Name for the integration.
Weaviate URL, for example your-cluster.c0.europe-west3.gcp.weaviate.cloud.
API Key. Required for Weaviate Cloud, optional if your instance has no authentication.

3

Add collections

Click Fetch Collections and enable the ones you want, or add a collection by name. Weaviate uses PascalCase names, for example MyCollection.

4

Set an embedding config

Pick an embedding config for each collection. It must match the model that created the vectors. If embeddings are server-generated, set the config to built-in.Don’t have one yet? Open the embedding config picker and click Create New.

Enter a Name, pick a Provider, and set the Model Name and Dimension to match the model that created your vectors. Add an API Key if the provider needs one, then save.

5

Save

Click Create Integration. Raily then configures agentic search for each collection automatically. This can take a few minutes, after which the integration appears under My Integrations with an Active status.

Once it finishes, open Inventory → Data Catalog to see the generated configuration for each collection.

6

See it in the Data Catalog

After generation finishes, Raily opens the collection in Data Catalog.

1

Open pgvector

Click the pgVector card.

2

Enter the connection details

Name for the integration.
Connection String, for example postgresql://user@host:5432/dbname.
Password. Optional if the password is already in the connection string.

3

Confirm the connection

Raily checks the credentials automatically. The Credentials section shows Verified when they work, or Failed if not.

4

Add tables

Click Fetch Tables and enable the ones you want, or add a table by name. Schema-qualified names are supported, for example public.documents.

5

Set an embedding config

Pick an embedding config for each table. It must match the model that created the vectors.Don’t have one yet? Open the embedding config picker and click Create New.

Enter a Name, pick a Provider, and set the Model Name and Dimension to match the model that created your vectors. Add an API Key if the provider needs one, then save.

6

Save

Click Create Integration. Raily then configures agentic search for each collection automatically. This can take a few minutes, after which the integration appears under My Integrations with an Active status.

Once it finishes, open Inventory → Data Catalog to see the generated configuration for each collection.

1

Open Oracle

Click the Oracle card.

2

Enter the connection details

Name for the integration.
Connection String in Easy Connect form, for example user@host:1521/FREEPDB1. For Autonomous Database, add ?wallet_location=....
Password. Optional if the password is already in the connection string.

3

Confirm the connection

Raily checks the credentials automatically. The Credentials section shows Verified when they work, or Failed if not.

4

Add tables

Click Fetch Tables and enable the ones you want, or add a table by name. Schema-qualified names are supported, for example RAILY.ARTICLES.

5

Set an embedding config

Pick an embedding config for each table. It must match the model that created the vectors. If embeddings are server-generated, set the config to built-in.Don’t have one yet? Open the embedding config picker and click Create New.

Enter a Name, pick a Provider, and set the Model Name and Dimension to match the model that created your vectors. Add an API Key if the provider needs one, then save.

6

Save

Click Create Integration. Raily then configures agentic search for each collection automatically. This can take a few minutes, after which the integration appears under My Integrations with an Active status.

Once it finishes, open Inventory → Data Catalog to see the generated configuration for each collection.

7

See it in the Data Catalog

After generation finishes, Raily opens the collection in Data Catalog.

1

Open IBM Ceph

Click the IBM Ceph card.

2

Enter the connection details

Name for the integration.
RGW Endpoint URL of the Ceph RADOS Gateway, for example https://ceph.example.com.
Region. Required by the S3 client; Ceph ignores it. us-east-1 is fine.
Object Bucket where uploaded files are stored. Vectors live in <bucket>-vectors.
Index Name. Use default unless you have multiple indexes per bucket.
Access Key ID and Secret Access Key for the Ceph cluster.

3

Add vector buckets

Click Fetch Vector Buckets and enable the ones you want.

4

Set an embedding config

Pick an embedding config for each vector bucket. It must match the model that created the vectors.Don’t have one yet? Open the embedding config picker and click Create New.

Enter a Name, pick a Provider, and set the Model Name and Dimension to match the model that created your vectors. Add an API Key if the provider needs one, then save.

5

Save

Click Create Integration. Raily then configures agentic search for each collection automatically. This can take a few minutes, after which the integration appears under My Integrations with an Active status.

Once it finishes, open Inventory → Data Catalog to see the generated configuration for each collection.

6

See it in the Data Catalog

After generation finishes, Raily opens the collection in Data Catalog.

1

Open Salesforce

Click the Salesforce card.

2

Enter the connection details

Name for the integration.
Instance URL, for example https://myorg.my.salesforce.com.
Client ID, your Connected App consumer key.
Client Secret, your Connected App consumer secret.

3

Confirm the connection

Raily checks the credentials automatically. The Credentials section shows Verified when they work, or Failed if not.

4

Add collections

Click Fetch Collections and enable the ones you want. Salesforce search runs over Cases via SOSL, so no embedding config is needed.

5

Save

Click Create Integration. Raily then configures agentic search for each collection automatically. This can take a few minutes, after which the integration appears under My Integrations with an Active status.

Once it finishes, open Inventory → Data Catalog to see the generated configuration for each collection.

6

See it in the Data Catalog

After generation finishes, Raily opens the collection in Data Catalog.

Don’t have a vector database yet? Talk to us and we can provide one for you.

Add a Vector Store

Before you start

Steps

​Before you start

​Steps

Before you start

Steps