Reserved for future development. Ping me if you want to have a chat: [email protected]

Continual learning for Pi at the harness and prompt surfaces — declarative tool-call guardrails plus memory retrieval, injection, and consolidation. Model weights are out of scope.

Official Node.js/TypeScript SDK for Moda — the continual learning layer for AI agents. Automatic conversation threading and OpenTelemetry-native tracing.

Continual learning: a stop hook that, when the task that just ended ran more than 30 completed turns, hands a condensed excerpt of that task to a background subagent, which folds the durable findings into the agent's own skills.

Automatically and incrementally keeps AGENTS.md up to date by mining session conversations for high-signal learnings

Continual-learning orchestrator — downloads platform binary from GitHub Releases

MCP integration for FedLearn local continual learning (Cursor, Claude Desktop, AntiGravity)

On-device LoRA adapter (~150KB) with EWC continual learning

Continual learning MCP server for AI agents — topology-aware knowledge graph with kappa-routing, exposed as 5 loop-phase machines (retrieve/route/act/learn/consolidate), causal metadata, and neural embeddings. One of four MCP servers in the [&] three-prot

Standalone DeepSeek Harness plugin: continual harness self-evolution. The agent persists and refines reusable prompt notes, memories, skill contracts, and subagent specs through small evidence-backed edits, with automatic refinement gates, rollback, and p

Continual self-evolution plugin for DeepSeek Harness: versioned, auditable, rollback-safe harness state (prompt notes, memories, skills, subagent specs) refined from session trajectories.

Command line for Continual development and App deployment

Build cross platform desktop apps with JavaScript, HTML, and CSS

TypeScript SDK for Continual agents and Project tools

Generic build of Mozilla's PDF.js library.

Drop-in SDK to add an AI memory layer to any application. Works with OpenAI, Anthropic, Gemini, Claude, Vercel AI SDK.

Continual's standard Vite configuration for TanStack Start applications

TensorFlow layers API in JavaScript

Self-Optimizing Neural Architecture (SONA) - Runtime-adaptive learning with LoRA, EWC++, and ReasoningBank for LLM routers and AI systems. Sub-millisecond learning overhead, WASM and Node.js support.

Self-learning vector memory for AI agents — single-file .rvf cognitive container with HNSW search, episodic Reflexion memory, causal graph + Cypher, 9 RL algorithms, Thompson Sampling bandit, 41 MCP tools, hybrid (BM25 + dense) retrieval, GNN attention. 1