AI-Powered Workflow Automation
Stop routing data through external AI APIs. Fovea runs inside your Infoveave workflows — write a prompt once, and it handles the processing on every scheduled run.
How AI Workflows Work
You write the prompt. Fovea does the rest.
Connect your data source
Read from databases, files, APIs, or any Infoveave-connected source into the workflow.
Add an AI activity
Drop a Summarize or Transform activity into the workflow canvas and write your prompt in plain English.
Fovea generates and executes
Fovea reads your prompt, writes the code, and runs it across every row.
Results flow downstream
The updated data feeds into dashboards, databases, or the next activity in your workflow.
AI Workflow Activities
Two activities. Both drop into your existing workflows with no infrastructure changes.
Summarize using Gen AI
Turn paragraphs into one-line insights. At scale. On a schedule.
Point it at any long text column — feedback, descriptions, notes — write a prompt, and get a clean summary column added on every run. The original column stays untouched.
Common use cases
- Summarise call centre transcripts for CX dashboards
- Condense product descriptions for catalogue exports
- Generate headline insights from survey open-text
Transform using Gen AI
Describe the transformation in English. Fovea writes and runs the code.
Write the transformation rule in plain English. Fovea generates the code and runs it on every row. No Python environment, no script file to manage, no manual re-runs.
Common use cases
- Fill missing salary values with the column average
- Classify transactions into expense categories from descriptions
- Standardise inconsistent date formats across merged datasets
Powered by Fovea
Fovea also works interactively
Same engine, different mode. When you want answers on the spot rather than on a schedule, Fovea works as a conversational assistant directly inside your Infoveave dashboards.
AI Workflows by Industry
What teams are actually using AI workflows for, by industry.
Retail & E-commerce
- Summarise 10,000 product reviews into sentiment tags for a pricing dashboard
- Auto-classify customer complaints into return / refund / delivery categories
- Generate short product descriptions for catalogue exports from long spec sheets
Banking & Financial Services
- Classify transaction descriptions into expense categories for spend analytics
- Fill missing reference fields using AI inference from adjacent columns
- Summarise audit trail narratives for compliance reporting
Manufacturing & Operations
- Summarise maintenance log notes into structured fault codes
- Extract part numbers and fault descriptions from free-text service records
- Standardise inconsistent supplier names across merged procurement datasets
Frequently Asked Questions
Ready to see Infoveave in action?
