Choose a grid only for multi-record work
A short factual answer or small read-only table should remain prose or markdown. Use Ace Grid output when the assistant returns enough business records that users need sorting, filtering, selection, editing, validation, comparison, or approval. Account risk, support triage, finance review, compliance checks, and operations queues are strong candidates because the answer becomes a temporary workspace rather than a static message.
Define a versioned assistant contract
The model should return a constrained document rather than arbitrary React props. Include schema version, typed columns, stable row IDs, values, provenance, validation issues, and an allow-listed command set. Versioning lets the application reject or migrate incompatible output. Unknown fields that could grant access or trigger actions should fail validation instead of being ignored. The contract should be understandable without depending on a specific model provider.
Preserve provenance with the rows
Store source labels, URLs, timestamps, model or provider information, confidence where meaningful, and warnings. Provenance must remain accessible when users sort or filter the result. A valid schema proves only that the output has the expected shape; it does not prove that values are current or correct. The application should verify sensitive facts against authoritative systems before users act on them.
Separate rendering from commands
Rendering validated rows is lower risk than changing business state. Suggested commands should reference allow-listed operations and stable row IDs, never executable code. Before applying a command, the server rechecks authorization, current record versions, and business rules. Consequential changes require explicit user approval. Return per-row outcomes so the grid can show success, rejection, conflict, or retry without hiding partial failure.
Design failure and fallback states
Handle streaming, incomplete output, schema errors, missing citations, empty results, expired authorization, and backend failures. Preserve a readable text fallback and the raw response for diagnosis without exposing sensitive internals to unauthorized users. Do not silently coerce malformed fields into valid-looking rows. Explain which part failed and let users retry the assistant request or continue with the verified portion.
Protect sensitive data
The assistant, retrieval layer, grid, logs, and mutation service must enforce the same data-access rules. Limit fields before model invocation, avoid placing sensitive prompts or payloads in client logs, and redact diagnostics according to policy. Revalidate authorization when a user applies an action because permissions or record state may have changed since generation. A schema does not replace security controls.
Measure usefulness and safety
Track whether users sort, filter, select, edit, approve, reject, or abandon generated grids. Measure schema failure, unsupported output, citation coverage, stale data, command rejection, and correction rates. These signals reveal whether a grid improves the assistant or merely adds visual complexity. Review high-impact workflows with domain owners and update the schema as recurring failure patterns emerge.
Use business data examples, not abstract rows
Account risk, renewal exceptions, compliance findings, invoice variance, and support escalation explain why AI output needs sorting, filtering, selection, validation, and approval. Abstract rows do not demonstrate the workflow. Use records and actions that resemble the internal assistant's real business domain.
Implement the complete answer pipeline
Retrieve only data the user can access, ask the model for a constrained versioned result, validate the result, map allowed fields into Ace Grid, and retain provenance beside each row. Rendering can proceed after validation. Any proposed mutation must pass a separate approval and server authorization step that checks current permissions and record versions. Return per-row outcomes so partial success, rejection, and conflict remain visible.
Keep the chat and grid responsibilities separate
The chat experience owns the conversation, request context, and explanation. The schema owns the stable result format. Ace Grid owns interactive tabular rendering. The application and server own authorization, persistence, and business actions. Keeping these boundaries explicit allows the same validated result to appear in chat, a review queue, or an audit view without giving the model direct control over the React component.
Live Ace Grid example
Native AI chat table output
An assistant response becomes a validated, interactive Ace Grid block with business rows and auditable actions.
Validated AI grid output example
import { Grid } from "@ace-grid/enterprise";
import {
createGridAiResultSchema,
validateGridSchemaDocument,
applyGridSchemaDocument,
} from "@ace-grid/schema-ai";
const resultSchema = createGridAiResultSchema({
kind: "update_view",
view: assistantGridView,
});
export function applyAssistantResult(actions) {
const validation = validateGridSchemaDocument(resultSchema);
if (!validation.valid) return validation;
return applyGridSchemaDocument({ actions, value: resultSchema });
}
export function AssistantAnswerGrid({ rows, columns }) {
return <Grid data={{ rows, columns }} columns={{ columnWidths: {} }} layout={{ width: 1200, height: 420 }} />;
}