When you work on a project with an AI agent, you generate a tremendous amount of thinking — ideas, decisions, debates, and architectural choices. You save your code with Git, but you have never saved the context and thinking behind the code — the reasoning that created it in the first place.
In the AI Agentic Era, that thinking IS the most valuable asset. Whether you are an individual developer or an enterprise team, losing that context means starting from zero every time you open a new tab, switch machines, or change AI tools.
AI-NEURON captures, preserves, and replays the complete context of your AI-assisted development journey, forever.
Unzip, double-click, and your browser opens the portal automatically.
Drop the binary on your PATH. Use with Cursor, Claude Code, Copilot, or any MCP-compatible agent.
Or install from source:
cargo install --git https://github.com/vishalkudmethe/ai-neuron
Binaries built automatically via GitHub Actions on every tagged release. View all releases →
5 native tools exposed over JSON-RPC 2.0 stdio — zero configuration required
*No raw files leave your machine. Only stripped structures, signatures, and sanitised text are emitted to reasoning engines.
Provide instant, continuous workspace context for Google Gemini and xAI Grok. Deploy dedicated, isolated memory sidecars at a bulk licensing rate of $1.00 / active user / month.
Flat directory parsing drops full file content into LLM windows, wasting valuable tokens on repetitive boilerplates.
Agents lack context of sibling projects or packages, making signature updates extremely error-prone.
Unprocessed logs, database connections, and environment files leak directly to commercial cloud providers.
Without monitoring, agents repeatedly run identical compiler routines and cycle through file reversions indefinitely.
Filters project assets dynamically, keeping structure and signature definitions while stripping token bloat.
Maintains child-parent dependency trees with instant notification warnings when upstream APIs modify signatures.
Intercepts database queries and outputs to scrub passwords, raw keys, and proprietary tokens before payload delivery.
Monitors workspace changes to detect recursive agent compile or write cycles. Introduces safety delays and auto-halts looping agents to protect against runaway API token bills.
Provides stdin/stdout communication mapping perfectly to the standard Model Context Protocol. Exposes local context directly to agent plugins.
Understands project structure at syntax level. Maps classes, structures, and declarations into SQLite index for sub-millisecond retrieval.
Establish topological linkages. Track parent-child workspace relationships and trace cascades when signature hashes change.
Auto-detection engine that intercepts outputs and cleans credentials, authentication endpoints, and SSH keys in real-time.
Stops runaway AI coding loops. The Loop Guardian monitors active agent directories for recursive write or test cycles, automatically warning the user and pausing/halting the execution (e.g., 5x duplicate writes in 60s) to prevent astronomical API token drain.
Acts as an immutable Information Blockchain Ledger of all AI actions. The Memory Digest Engine translates dense AST and SQLite logs into human-readable executive summaries, perfect for team handoffs.
AI-NEURON is local-first and free for individual developers. Upgrade for cloud synchronization, team collaboration, or enterprise security compliance.
Looking for OEM or hyperscaler licensing? See Enterprise →
AI-Neuron is protected by provisional patent filings in India (June 2026) with additional international protection planned. We are actively expanding our intellectual property portfolio to protect developers who want full control over their code.
View Patent SpecificationsA deterministic, on-device system combining real-time filesystem monitoring, AST parsing, content hashing, and embedded SQLite for structured AI agent context.
An autonomous sliding-window detection system that identifies repetitive AI agent behavior and interrupts it to prevent runaway LLM API costs.
Delivering only structural changes (not raw files) to dramatically reduce token consumption while maintaining high accuracy.
Memory that survives folder changes, machine restarts, and account switches through global indexing and auto-restore.