Transform using Gen AI
Infoveave Data Automation — AI-Powered
Write the rule in English. Fovea generates the code and runs it.
Data wrangling takes up a disproportionate share of analyst time: missing values, inconsistent formats, categories that don't line up across systems. Fixing it usually means Python or SQL. Transform using Gen AI changes that — describe what you want in plain English, and Fovea generates and runs the code inside your workflow. Same result, no scripting required, and it runs again automatically every time new data arrives.
What Transform using Gen AI does
Describe any data transformation in plain English. Fovea AI generates and executes the code on your dataset automatically — no Python environment, no script management, no manual runs.
When to use Transform using Gen AI
- You need to fill missing values using statistical logic (average, median, mode) without writing code
- You want to classify or categorise records based on text descriptions — for example mapping transaction narrative to expense categories
- You need to standardise inconsistent formats across merged datasets — date formats, address fields, product codes, units of measure
- You need a new column from business logic that's simpler to say in English than write in SQL
- You are prototyping a transformation and want to test different logic quickly by changing the prompt rather than rewriting code
When to avoid it
- Your transformation requires deterministic, auditable logic that must be version-controlled — use SQL Transform or Execute Python Script for full code control instead
- You need to join multiple datasets — use workflow-level data merge or SQL Transform before this activity
- The transformation is a simple column rename, type cast, or format change — dedicated activities like Rename Columns, Custom Date Format, or Numerical Formatting are faster and more predictable
Where it fits in your Infoveave automation
Transform using Gen AI is one step inside a multi-step Infoveave workflow. Chain it with other activities — no code, no manual hand-offs.
Build this workflow visually in Infoveave Data Automation — drag, connect, and schedule with no infrastructure setup.
How teams use Transform using Gen AI
Real scenarios where this transformation saves hours of manual work.
Transaction Category Classification from Descriptions
A bank's transaction export contains free-text merchant descriptions. Transform using Gen AI classifies each transaction into expense categories (Travel, Dining, Utilities, Retail) based on the description — feeding a spend analytics dashboard without any rule-based coding or manual tagging.
Missing Price Imputation Across Product Records
A retailer's consolidated product file has missing prices for some SKUs after a system migration. Transform using Gen AI fills missing price values with the median price for that product category — ensuring the pricing dashboard shows complete data on every run.
Unit Standardisation Across Supplier Datasets
Procurement data arrives from multiple suppliers with inconsistent units (kg vs lbs, mm vs inches). Transform using Gen AI converts all values to a standard unit per column — producing a clean, comparable master dataset for materials planning.
See Transform using Gen AI in action
Input data (left) is transformed using the configuration below. The output table (right) is ready for dashboards or downstream steps.
Fill missing salary values with the average of the existing salaries in the dataset.(Auto-generated by Fovea — visible in the activity panel for review)Input Data
| ID | Employee | Department | Salary | Start_Date |
|---|---|---|---|---|
| 101 | John Doe | HR | 50000 | 2020-01-15 |
| 102 | Jane Smith | IT | 2019-03-10 | |
| 103 | Alice Johnson | Finance | 60000 | 2021-06-25 |
| 104 | Bob Williams | Marketing | 2018-09-12 | |
| 105 | Emma Brown | Sales | 65000 | 2022-02-20 |
Output Data
| ID | Employee | Department | Salary | Start_Date |
|---|---|---|---|---|
| 101 | John Doe | HR | 50000 | 2020-01-15 |
| 102 | Jane Smith | IT | 58333 | 2019-03-10 |
| 103 | Alice Johnson | Finance | 60000 | 2021-06-25 |
| 104 | Bob Williams | Marketing | 58333 | 2018-09-12 |
| 105 | Emma Brown | Sales | 65000 | 2022-02-20 |
Configuration
Key fields to configure in the Infoveave workflow builder. Full reference available in the documentation.
Prompt
Plain-English description of the transformation you want applied to the dataset. Be specific — include the column names, the logic, and the desired output. For example: 'Fill missing values in the Salary column with the average of existing Salary values.' The more precise the prompt, the more reliable the generated code.
Code (Auto-generated)
Fovea generates Python code from your prompt and displays it in the activity panel before execution. You can review the generated code to verify the logic before the workflow runs — providing a transparent, auditable view of what AI will do to your data.
Frequently asked questions
Everything you need to know about Transform using Gen AI in Infoveave.
Also in AI-Powered — and what runs before & after
Transformations in the same family as Transform using Gen AI, often chained together in the same Infoveave workflow.
Part of Infoveave Data Automation
80+ transformations. Zero manual steps.
Transform using Gen AI is one of over 80 transformation activities available inside Infoveave workflows. Chain transformations together — no code, no exports, no waiting for IT.
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