Practical Applications
Discover how engineering teams and developers leverage ReclaimLLM to solve token waste, audit agentic coding tools, move context between models, and secure AI data.
Reduce redundant AI tool-result tokens by up to 40% on shell and read-heavy workloads.
Avoid re-sending unchanged files and huge build logs. Diff-on-change read caching, test output compaction, loop breakers, and result deduplication keep your prompts lean.
Reconstruct step-by-step tool executions and code file diffs from AI coding assistants.
Native CLI hooks capture structured sessions from Claude Code, Gemini CLI, Cursor, and Antigravity. Inspect exact file diffs and tool execution inputs/outputs.
Move complete sessions between frontier models and local tools without re-explaining background.
Start a complex debugging session in Claude Code and transfer context to Gemini CLI, Cursor, or a local open model without losing step history or re-deriving context.
Default-on secret masking and enterprise governance for AI development.
Prevent credentials, API keys, and sensitive data from leaking to third-party LLM APIs. Enforce org-wide DLP, encrypted session blobs, and enterprise gateway keys.