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Table & List AI Assistants

Row-level AI for every table screen: multi-select bulk actions, data cleanup, natural-language filtering, summarization, and inline smart suggestions.

Overview

Every table and list screen in TotalApp — Asset Registry, My Projects, Purchase Orders, Employees, and dozens more — has an AI Assistant panel that operates directly on the rows in front of you. It is built for operational, row-level work: select records, run bulk actions, clean up messy data, filter with plain English instead of a filter builder, summarize what you're looking at, and get smart per-row suggestions.

1. Select or filter rows
→
2. Ask the assistant
→
3. Review the suggested action
→
4. Apply

1. Multi-Select & Mass Action

Select any number of rows and describe the bulk change in plain language — the assistant translates it into the right batch update.

Example

"Set status to Approved for these 5 maintenance records and create a work order." The assistant updates all 5 selected rows and creates the linked work order in one step, instead of five separate edits.

2. Data Cleanup & Validation

The assistant scans selected rows (or the whole table) for inconsistent or missing data — mismatched units, blank required fields, duplicate entries, out-of-range values — and proposes fixes in bulk rather than making you hunt for each one manually.

3. Smart Natural-Language Filtering & Search

Instead of building a filter with multiple dropdowns and date pickers, just describe what you want to see.

Example

"Show all CNC machines that were overdue last month with downtime over 10 hours." The assistant parses the equipment type, the date window, the status condition, and the downtime threshold, then applies all four as one combined filter.

4. Quick Summarization & Data Transformation

Ask for a summary of the selected rows or the entire table, and get a plain-English digest instead of scrolling through every record. The same panel can also convert the current view into other formats on demand — CSV for spreadsheets, JSON for further processing, or plain report text for sharing.

5. Inline Smart Suggestions

Beyond responding to typed requests, the assistant proactively flags things worth acting on as you browse a table.

Example

"This vendor has a high delay score — here are 3 alternative vendors with better on-time delivery." The suggestion appears inline next to the row it's about, with no need to ask for it explicitly.

Capability Summary

Multi-Select & Mass Action

Bulk edits and linked record creation across any number of selected rows.

Data Cleanup & Validation

Detects and fixes inconsistent or missing data across the table in one pass.

Smart NL Filtering

Plain-English queries turn into precise, multi-condition filters instantly.

Summarization & Transformation

Summarize selected rows or the whole table, or export to CSV/JSON/report text.

Inline Smart Suggestions

Proactive, row-scoped recommendations that surface without being asked.

Frequently Asked Questions

Do I need to select rows before asking the assistant something?
Not always. Multi-select & mass action and inline smart suggestions work on selected rows, but summarization and natural-language filtering can be run against the whole table with nothing selected.
Can the assistant make changes without my confirmation?
No. Bulk edits and data-cleanup fixes are proposed first — you review the suggested action before it's applied. Nothing is written to your data until you confirm.
Does natural-language filtering replace the regular filter controls?
No, it's an alternative path to the same filters. You can still use the dropdowns and date pickers directly; the assistant just translates a plain-English request into the same underlying filter conditions.
What export formats can I get from the summarization feature?
CSV for spreadsheets, JSON for further processing, or plain report text for sharing — all generated from the current selection or the full table view.
Does the Table Assistant use the same AI engine as the rest of TotalApp?
Yes. It respects whichever Writer Engine is set in Settings → Agentic (Ollama, In-Browser, Cloud LLM, or Local CLI) — see AI Assistants → Overview for how the two assistant families share this configuration.