BranchChat provides a visual tree interface for AI chat interactions, letting users branch off any message to explore alternative responses without losing the original thread. It enables side‑by‑side comparison of conversation paths and links context across branches, helping developers and users evaluate model outputs more effectively.
Funding
Funding not disclosed
Founders
Product
Problem
Developers and teams working with AI language models often struggle to explore multiple prompt variations within a single conversation, as traditional linear chat interfaces make it difficult to branch, compare, and retain context without losing the original thread.
Solution
BranchChat replaces the conventional linear chat view with an interactive visual tree that lets users fork any message to create alternative response paths. Users can place two branches side by side to directly compare answers, latency, and token usage, while a linking feature pulls relevant context across branches so the model retains necessary information. The interface operates without recording chat content, ensuring privacy while providing a clear workflow for evaluating prompt performance and response quality.
Target Audience
BranchChat is aimed at AI developers, prompt engineers, and product teams who need to test and iterate on prompt designs and model outputs efficiently.
Features
- Visual tree UI that allows forking from any message to generate parallel conversation branches
- Side‑by‑side branch comparison view for evaluating answer quality, latency, and token consumption
- Context linking across branches to preserve important information for the model
- Privacy‑first design: in‑app chat content is never stored or recorded
- Real‑time preview of AI responses with syntax‑highlighted code snippets