Best practices

Refer to the prompting and indexing best practices below to effectively use aiR Assist.

Prompting

Following these prompting best practices may help ensure accurate, efficient, and relevant responses from aiR Assist.

• Ask clear and focused questions
  To help improve results, keep questions concise and specific. Focus each query on a single topic or piece of information so it can be mapped to documents. Long, compound, or highly complex questions may take longer to process, may not map to documents, and can reduce clarity in the generated response. Start a new conversation when switching topics to prevent stale content from skewing results.
• Leverage keywords and synonyms
  Retrieval engines like specific terms. Include specific names, likely variations of keywords (such as, bribe, gift, incentive, Rolex), or entity synonyms (such as, bt or bt.us for Big Thorium). Retrieval benefits from alternative phrasing.
• Stay within the saved search context
  aiR Assist generates responses based on the documents included in the public saved searches used to build its indexes. Each saved search defines the specific dataset aiR Assist can draw from within the workspace. Questions should therefore relate to the content of those saved searches rather than general or external topics.
• Expect some variation in repeated queries
  Submitting the same or similar questions multiple times may produce slightly different answers, as aiR Assist regenerates responses dynamically. However, the core content and conclusions are generally expected to remain similar, though variation may occur.
• Review citations and supporting references
  Each aiR Assist response includes citations and supporting document references. Review these sources to verify accuracy and context, especially when using the results for analysis, reporting, or decision-making.
• Maintain high-quality indexed data
  Response quality depends on the content indexed. Ensure that the dataset includes clean, text-extractable documents and that saved searches accurately capture relevant materials. Avoid including duplicate or irrelevant documents within indexes.
• Avoid overly broad or “find me everything” queries
  aiR Assist is optimized to find and synthesize the most relevant information, not to return exhaustive lists of all matching documents. For comprehensive discovery, you can use standard search tools in combination with aiR Assist or, depending on the use case, consider using our other aiR Suite products.
• Avoid using aiR Assist for calculations
  Do not rely on aiR Assist to add up invoices, total damages, or perform complex calculations. The right data may be scattered across multiple files, and LLMs are not perfectly reliable at math calculations.
• Break down complex reasoning or multi-step queries
  Avoid questions that require multiple steps or “leaps” (such as, “show me emails from the director who signed the compliance policy”). Break these into smaller, sequential questions so aiR Assist retrieves the most relevant information and clearly understands your objective.

Examples of unsupported prompts and their supported alternatives

Indexing

To achieve the best indexing results, below are some data preparation recommendations:

• Build focused indexes—align each index to specific custodians, issues, themes, or time periods, for example.
• Curate the Saved Search—point the index at a well-defined public saved search; private ones are not supported.
• Optimize document quality—ensure documents contain extracted text and that the Extracted Text field is Data Grid File System enabled, as aiR Assist does not support environments where the text is stored in SQL. Also, exclude files over 5MB, duplicate documents, irrelevant documents, and documents that do not contain text.
• Manage indexes well—establish clear naming conventions, use names longer than five characters, and use the index Description field to help clearly describe the index.