Qualitative thematic analysis (TA) is valuable but challenging to scale because of the time, cost, and complexity involved. Existing tools offer limited automation and often lack flexibility, trustworthiness, and usability with unstructured data. To address this gap, we developed DeTAILS 1 - an interactive toolkit that integrates large language models into reflexive TA workflows. Built on a modern architecture, DeTAILS supports qualitative data analysis through iterative, LLM-in-the-loop interactions. Next, we plan to conduct a formal evaluation with domain experts to assess its usability, trust, and analytic value. By embedding interactive LLM-in‑the‑loop processes, DeTAILS strives to extend TA to far larger datasets while preserving analytic depth and researcher reflexivity-going beyond the throughput limits of manual coding in a given time.