Integrations

Enterprise Cloud Integrations

riogentix provides native, first-class connectors for Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Trigger workflows from cloud events, process data with AI, and write results back to cloud services — all without leaving the visual builder.

Amazon Web Services (AWS)

Authentication

Create an AWS Credential in Settings → Credentials → Add → AWS:

IAM User — provide Access Key ID + Secret Access Key
IAM Role (recommended) — provide Role ARN; riogentix assumes the role via STS
Instance Profile — auto-detected when running inside AWS

Apply the principle of least privilege: create a dedicated IAM user or role with only the permissions your workflows need.

Supported AWS Services

Service	Operations
S3	Get object, Put object, List bucket, Delete object, Generate pre-signed URL
SQS	Send message, Receive messages, Delete message, Purge queue
SNS	Publish message, Create/delete topic, Subscribe
Lambda	Invoke function (sync or async)
DynamoDB	GetItem, PutItem, Query, Scan, UpdateItem, DeleteItem
RDS	Query via standard database connector (PostgreSQL/MySQL)
Bedrock	Invoke foundation models (Claude, Llama, Titan, Mistral)
Secrets Manager	Get secret value (inject into workflow at runtime)
EventBridge	Publish events, create rules as workflow triggers
Textract	Analyse documents, extract tables and forms
Rekognition	Detect labels, faces, text in images

Example: Process Files from S3 with AI

[S3 Event Trigger: new object in my-invoices bucket]
        ↓
[S3: Get Object → read PDF bytes]
        ↓
[AWS Textract: Extract text from document]
        ↓
[AI Agent: Parse invoice fields into JSON]
        ↓
[DynamoDB: PutItem → store structured invoice]
        ↓
[SNS: Publish → notify finance team]

Using AWS Bedrock for LLM Nodes

Select AWS Bedrock as the provider in any LLM or AI Agent node. Your data stays within your AWS account — no data leaves your cloud environment.

{
  "provider": "bedrock",
  "model": "anthropic.claude-3-5-sonnet-20241022-v2:0",
  "region": "us-east-1",
  "credential": "my-aws-credential"
}

Microsoft Azure

Authentication

Create an Azure Credential in Settings → Credentials → Add → Azure:

Service Principal — provide Tenant ID, Client ID, and Client Secret
Managed Identity — auto-detected when riogentix runs in Azure

Assign the service principal the minimum required Azure RBAC roles (e.g., *Storage Blob Data Contributor*, *Service Bus Sender*).

Supported Azure Services

Service	Operations
Blob Storage	Upload blob, Download blob, List containers, Delete blob
Service Bus	Send message, Receive message, Topic subscriptions
Event Hubs	Send events, receive and process event streams
Azure Functions	Invoke HTTP-triggered functions
Cosmos DB	Read item, Upsert item, Query (SQL API)
SQL Database	Full SQL query support via database connector
Azure OpenAI	Call GPT-4o, GPT-4-turbo deployed in your subscription
Cognitive Services	Form Recognizer, Text Analytics, Translator
Key Vault	Get secret, inject into workflow as credential
Entra ID	List users/groups, manage identities (via Graph API)

Example: Document Intelligence Pipeline on Azure

[Service Bus Trigger: new message on contracts queue]
        ↓
[Blob Storage: Download PDF contract]
        ↓
[Azure Form Recognizer: Extract key-value pairs]
        ↓
[Azure OpenAI (GPT-4o): Summarise obligations]
        ↓
[Cosmos DB: Store contract summary]
        ↓
[Teams: Post summary to #legal channel]

Using Azure OpenAI

Deploy your own GPT model in Azure OpenAI Studio, then connect it in riogentix:

Settings → Credentials → Add → Azure OpenAI
Enter your Endpoint, API Key, and Deployment Name
Select *Azure OpenAI* as the provider in any LLM node

Your prompts and completions stay within your Azure tenant.

Google Cloud Platform (GCP)

Authentication

Create a GCP Credential in Settings → Credentials → Add → Google Cloud:

Service Account Key — upload the JSON key file from the GCP Console
Workload Identity — auto-detected when running on GKE

Grant only the IAM roles your workflows require (e.g., *roles/storage.objectViewer*, *roles/pubsub.publisher*).

Supported GCP Services

Service	Operations
Cloud Storage (GCS)	Upload, download, list, delete objects
Pub/Sub	Publish message, pull messages, push subscription trigger
BigQuery	Run query, insert rows, create/delete tables
Cloud Functions	Invoke HTTP-triggered functions
Firestore	Get document, set document, query collection
Cloud SQL	Query via standard PostgreSQL/MySQL connector
Vertex AI	Call Gemini models, run custom model endpoints
Document AI	Parse documents, extract entities
Cloud Translation	Translate text between languages
Secret Manager	Access secrets at workflow runtime

Example: Real-Time Analytics Pipeline on GCP

[Pub/Sub Trigger: user_events topic]
        ↓
[AI Agent (Vertex Gemini): Classify event intent]
        ↓
[BigQuery: Insert classified event row]
        ↓
[Switch: if intent == "churn_risk"]
        ↓
[HTTP Request: POST to CRM → flag account]
        ↓
[Slack: Notify customer success team]

Using Vertex AI (Gemini)

Enable the Vertex AI API in your GCP project
Add a GCP Service Account credential with *Vertex AI User* role
Select *Google Vertex AI* as the provider in any LLM or AI Agent node
Choose your model (e.g., gemini-1.5-pro) and region

Multi-Cloud Patterns

Cross-Cloud Data Replication

[AWS S3: New file trigger]
        ↓
[AI Agent: Extract and transform data]
        ↓
           [Merge]
      ↙              ↘
[Azure Blob]     [GCS]   ← replicate to multiple clouds

Unified Alerting Across Clouds

Connect AWS CloudWatch, Azure Monitor, and GCP Cloud Monitoring to a single riogentix workflow that normalises alerts and routes them to your team's Slack or Teams channels.