Data & File Processing
Searches uploaded content for recurring keywords or patterns, with counts and context.
A focused file analysis agent for analysts
Text Pattern Finder is an AI agent built to searches uploaded content for recurring keywords or patterns, with counts and context. It is built for analysts, operators, researchers, and teams working with files who need to avoid searching manually for recurring phrases, formats, anomalies, or extraction candidates. Add text or dataset file, specific pattern type or keywords to search, and output format; the agent turns those inputs into matched patterns, counts, examples, and interpretation notes. Run it once per file batch or dataset, then reuse the slots whenever the input format repeats.
Start with text or dataset file. Then add specific pattern type or keywords to search and output format so the agent has enough context to produce matched patterns, counts, examples, and interpretation notes.
Yes. That is one of the core outputs. More specific inputs produce more specific results.
It asks for the details most likely to change the answer, especially text or dataset file, specific pattern type or keywords to search, and output format. That prevents searching manually for recurring phrases, formats, anomalies, or extraction candidates.
Yes. Use the file-or-text slots for spreadsheets, documents, transcripts, exports, or pasted text, then specify the exact extraction or analysis goal.
Yes. Add your preferred format, examples, tools, or constraints in the slots, and the agent can shape the result around them.
Clarify text or dataset file, add missing constraints, and state what a good result should include. The next run will usually improve when the failure mode is explicit.