KQL Builder

Purpose & User Intent: The tool translates business goals into robust eDiscovery KQL expressions, enabling legal and IT teams to craft precise searches across mail, documents, chats, and file stores. It emphasizes repeatability, auditable trails, and exportability for litigation and compliance workflows. Intended users include eDiscovery analysts, legal operations, compliance officers, and IT admins who require domain-guided query construction.
Core Logic & Features: The system uses a field-based model with required field, operator, and value components and supports advanced grouping via parentheses. It enforces syntax validation, operator precedence, and structured export. Optional features include reusable templates, version history, template import/export, and API-ready JSON blocks for integration.
Inputs & Outputs: Users provide target content scope, field definitions, date ranges, attachment flags, and sample values. The tool outputs a KQL string, a summary, and a syntax-valid flag, with ISO 8601 date validation. Exports can be standalone queries or embedded blocks in enterprise pipelines.
Algorithms & Calculations: High-level criteria map to KQL tokens (e.g., contains, equals, starts_with, ends_with). The engine groups expressions with parentheses, applies date literals, escapes special characters, and concatenates tokens with AND/OR/NOT logic to form the final query.
Error & Edge Cases: The tool reports invalid field names, unsupported operators, unbalanced parentheses, empty values, or date parsing issues with structured error details and no UI messaging. If external data sources are unavailable, it preserves input while flagging the issue.
Industry/Region & Localization: ISO 8601 dates are required; times are UTC unless a timezone is specified. English KQL syntax is assumed; localization is limited to date formats.
Assumptions & Exclusions: Assumes access to an eDiscovery index and mapping of fields to supported entities. UI, authentication, and data rendering are outside the scope; only KQL generation and metadata are produced.