Rayven.io has introduced an advanced Generative AI capability that allows users to ask natural language questions about their data and receive intelligent, real-time answers.
Rayven.io enables organizations to harness the power of Generative AI through seamless integration with OpenAI’s language models. This functionality allows users to embed AI-driven reasoning, text generation, summarization, and response automation directly within workflows, dashboards, notifications, and interfaces.
What is Generative AI in Rayven?
Rayven’s Generative AI Node allows users to connect to OpenAI’s API using their own credentials, define prompts, and dynamically generate content or decisions based on live or historical data. You can use this output in:
-
Real-time workflow logic
-
Interface widgets
-
Automated alerts (e.g., email, SMS)
-
AI-driven reports or summaries
-
Data enrichment processes
Setup: Connecting to OpenAI
To get started:
-
Insert a Generative AI Node in your workflow.
-
Add your OpenAI API credentials (securely managed via Rayven’s credential vault).
-
Define a prompt—this can include variables from data tables, external inputs, or workflow values.
-
Run the prompt and retrieve the AI-generated response.
-
Use the response in downstream nodes (e.g., alerts, widgets, table writes).
Data Sources for Prompts
You can generate context-aware AI output by feeding the model structured or unstructured data:
-
File Uploads: PDF, text, or CSV documents can be read and parsed into prompts.
-
Table Data: Use values from internal tables (e.g., sensor logs, ticketing data).
-
External Systems: Connectors can bring in external inputs (e.g., CRM, ERP, field reports).
-
Workflow Variables: Use real-time values (e.g., alerts, machine state, location) directly in prompt construction.
Use Cases for Generative AI in Rayven
Use Cases for Generative AI in Rayven
1. AI-Powered Email Alerts
Trigger contextual, human-readable emails based on real-time events.
-
Prompt:
“Summarize the cause and impact of this vibration anomaly: [insert data snapshot]” -
Use:
Inject the result into the Send Email node to alert engineers or managers with clear next steps.
2. Natural Language Dashboard Summary
Summarize operational performance for daily overviews or shift handovers.
-
Prompt:
“Summarize shift performance using this data: [insert production, downtime, and output figures]” -
Use:
Display in a Text Widget on a dashboard for supervisors or shift leads.
3. Intelligent SMS Notifications
Send field personnel AI-generated instructions tailored to fault types.
-
Prompt:
“Explain error code [X] and suggest immediate response for the operator.” -
Use:
Output is passed to an SMS Node to alert technicians with actionable language.
4. AI Data Enrichment in Tables
Convert raw inputs (e.g., user reports, IoT logs) into classified, summarized records.
-
Prompt:
“Categorize and summarize this issue: [insert description]” -
Use:
Save the output into a workflow table for reporting or ticket generation.
5. Shift-Based Improvement Recommendations (Mining)
Evaluate operational data at the end of a mining shift and recommend improvements.
-
Prompt:
“Review this mining shift’s haul data, delays, and equipment performance. Recommend 2 improvements to reduce cycle time and improve output.” -
Output:
“Recommendation 1: Reduce wait time at crusher by staggering truck arrivals.
Recommendation 2: Assign Loader B to Bench 3 to minimize travel distance.” -
Use:
Sent via email, written into a daily shift report, or added to a dashboard summary.
6. Auto-Generated Maintenance Proposals
Generate a natural language maintenance or optimization proposal from logs or diagnostics.
-
Prompt:
“Based on this performance history and recent faults, generate a proposal for scheduled maintenance and potential upgrades.” -
Output:
“Proposal: Schedule valve inspection for Q3 based on repeated flow irregularities. Recommend installing remote pressure monitoring to reduce unplanned stops.” -
Use:
Output inserted into a formatted document or auto-submitted as a request via integrated workflow.
7. Customer-Facing AI Report Generation
Automatically generate a summary report from client-specific operational data.
-
Prompt:
“Write a monthly performance summary for Client A using these KPIs: [insert data]. Include key wins, issues, and next-step suggestions.” -
Use:
Included in PDF exports, email reports, or customer dashboards.
Summary
Rayven.io’s Generative AI integration offers:
-
Secure, real-time access to OpenAI language models
-
Prompt-based content generation inside workflows
-
AI-powered outputs for dashboards, emails, SMS, and logic flows
-
Full support for context-rich inputs including files, tables, and external systems
This capability empowers teams to automate communication, summarize data, enrich interfaces, and build logic-enhanced applications using natural language models.
Q&A
Q: Can I use any OpenAI model (e.g., GPT-4)?
A: Yes. You can configure the node to target different model versions via your OpenAI API settings.
Q: Is prompt content dynamic?
A: Yes. Prompts can include live workflow values, external inputs, or table data using variable placeholders.
Q: Can I store AI outputs in a data table?
A: Absolutely. AI-generated content can be written into any connected table for historical logging or later analysis.
Q: Can I generate content for different languages?
A: Yes. Just specify the desired output language in the prompt. For example, “Summarize this in Spanish…”
Q: Can I preview the AI response before using it in production?
A: Yes. Use test workflows or sandbox environments to validate output quality before live deployment.