# Chat Limitations

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We're continuously working to improve the quality of the responses. Here are the current limitations.
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Lumi is designed to generate instant insights from structured data. But like any tool, it has boundaries. Understanding these limitations ensures you can design better prompts, avoid confusion, and troubleshoot issues effectively. This guide covers the key limitations of Lumi Chat and how to work within them.

### Lumi Chat Limitations Guide

| Category                                                        | Recommended Practice                                                                                 |
| --------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- |
| [**Data Availability**](#id-1.-data-availability)               | Use Table Preview to verify what’s accessible before prompting.                                      |
| [**Data Returned From Query**](#id-2.-data-returned-from-query) | Always restate specific values or filters in follow-up questions.                                    |
| [**Follow Up Questions**](#id-3.-follow-up-questions)           | Use reasonable judgment to ensure follow-ups match the dataset context and reference available data. |
| [**Row Limitations**](#id-4.-row-limitations)                   | Use filters, limits, or aggregation to focus results and avoid truncation.                           |
| [**Latency**](#id-5.-latency)                                   | Simplify queries and collaborate with your data team to optimize performance.                        |

***

### Detailed Limitations

### 1. Data Availability

Lumi can only generate insights from data that is connected and defined in the Knowledge Base. If a field or table isn’t present within the KB, Lumi cannot access the data.

**Why this matters**: Lumi can't infer data that doesn't exist in the connected data set.

**Best Practices**:

* Use Table Preview to inspect available fields.
* Check the Knowledge Base for table names, relationships, and renamed fields.
* Validate your assumptions before writing prompts.

<figure><img src="/files/sngxB7E8nMERWgUZ5dQG" alt=""><figcaption></figcaption></figure>

**Example**:

* Prompt: “Show sales by region”
* Problem: `region` isn’t a valid column → Lumi will not be able to access that column.

***

### 2. Data Returned From Query

Lumi does not retain or access the visual results of previous queries result. It can only reference the prior prompt text and a summary, not the full table output.

**Why this matters**: Prompts like “Why did the top row drop?” are not understood because Lumi can't see what was in that row.

<figure><img src="/files/197rt2vf4YgHvjCn8ZGr" alt=""><figcaption></figcaption></figure>

**Avoid**:

* “What about the second row?”
* “Why did the top item drop?”

**Use instead**:

* “What was the revenue for item 1003 in 2023?”
* “Investigate the reasons behind the decline in sales for item 1003.”

**Tips**:

* Always include full identifiers in follow-up prompts.
* Don’t rely on positional language like “this,” “that,” or “above.”
* Manually extract values from prior outputs and reinsert them into the next prompt.

***

### 3. Follow Up Questions

Lumi may suggest follow-up questions, but these are not always guaranteed to work. Suggested prompts are generated heuristically and may include invalid columns or filters based on your schema. Additionally, Lumi is not connected to the internet or has access to non-structured data sources such as sharepoint or google drive equivalent.&#x20;

**Why this matters**: Clicking follow-up suggestions without checking may result in impossible prompts.

<figure><img src="/files/OfmFnksc5wq92RQAxA1w" alt=""><figcaption></figcaption></figure>

**Best Practices**:

* Manually review and rewrite follow-up prompts.
* Verify column and table availability before reusing suggestions.

***

### 4. Row Limitations

Each Lumi query can return a maximum of 100 rows. This limitation is set to ensure consistent performance and cost control across enterprise environments.

**Why this matters**: Broad queries without limits may be cut off, resulting in partial or incomplete outputs.

<figure><img src="/files/H2UySwMPYuTdexZdNb8l" alt=""><figcaption></figcaption></figure>

**Tips**:

* Use filters such as `Sort by`, `Group by`, and `Filter by`.
* Avoid trying to export large tables via Lumi. Focus on summarizing insights.

**Example**:

* <mark style="color:red;">Avoid:</mark> “Show all transactions in 2024”
* <mark style="color:green;">Use:</mark> “Show the top 10 SKUs by total revenue in 2024”

***

### 5. Latency

Lumi’s speed depends entirely on your data warehouse. Queries are executed live, and delays are often caused by limited compute resources.

**Why this matters**: Lumi does not control backend infrastructure. Performance is tied to your environment.

<figure><img src="/files/uMSB0vm2o2oCJh8KBiCy" alt=""><figcaption></figcaption></figure>

**Tips**:

* Coordinate with your data team if performance is consistently slow.
* Allocate more compute resources to source system.


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```
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