Funding
Funding not disclosed
Founders
Product
Problem
Development teams using AI coding assistants often generate extensive terminal and agent session logs that are noisy and unstructured, making it difficult to capture proven workflows and reuse them in future automated tasks. Without a systematic way to extract and share this context, teams must repeatedly recreate steps, leading to slower development cycles and inconsistent results.
Solution
Visr captures command-line interactions and agent-driven sessions from tools such as Claude Code, Codex, and Cursor, then transcribes them into structured runbooks and reusable skill packages. The platform filters out irrelevant output, preserving only the essential commands, decisions, and team rules that define a successful workflow. These distilled runbooks can be fed directly into subsequent coding agents, providing continuous, shareable context that accelerates task execution. By integrating with common shells (Bash, Zsh, Fish) and supporting agent sessions, Visr enables teams to promote proven processes into a persistent knowledge base without manual documentation.
Target Audience
Visr is aimed at software development teams and engineering organizations that incorporate AI coding assistants into their workflows, as well as DevOps groups seeking to automate and reuse command-line processes.
Features
- Real-time transcription of terminal commands, outputs, and agent decisions into a searchable log
- Automated distillation of noisy transcripts into concise runbook steps and skill definitions
- Compatibility with multiple shells (Bash, Zsh, Fish) and AI coding agents such as Claude Code, Codex, and Cursor
- Export of runbooks and skills as reusable context packages for downstream agents
- Command-line interface (`visr relay`) for easy integration into existing development workflows
- GitHub authentication for secure, team‑specific context management