Neo4j Bloom is a tool that enables users to navigate and visualize Neo4j graphs without needing to know Cypher query language. This allows for a more natural, visual exploration of the graph's connections, similar to taking an unknown path through a forest. While BI tools can provide subtotals, bar charts, etc., they were not designed for this functionality. To address this, Bloom enables custom Cypher queries executed in search phrases, which use a combination of text, parameters, and Cypher to guide users in building customized queries. These search phrases can be used to dynamically search the graph based on and/or logic, such as finding all :Person labeled nodes where the property born is between 1965 and 1992. The search phrase functionality allows for flexible searching with exact matching values, but can be problematic for other types of operators. A generic search phrase can be used to guide a user through this functionality, using parameters such as $label, $property, $condition, and $value. The search phrase also presents the user with conditional tests based on the data type of the property being tested. Additionally, Bloom allows users to find multi-label nodes by excluding invalid label combinations from the options presented to the user via a Cypher WHERE NOT clause. Finally, the blog discusses tips and techniques for working with Bloom, including using metadata commands, avoiding unwanted categories, and removing query parameters while editing search phrase definitions.