Agent memory that learns over time instead of just recalling past chats: retain/recall/reflect primitives turn interactions into facts, experiences, and mental models. Reports top LongMemEval scores; self-hostable with Python and Node SDKs.
Drives an LLM-powered agent to autonomously research, write, and ship ML code by accessing Hugging Face docs, datasets, repos, and cloud compute. Provides interactive CLI and headless modes, approval gates, tool routing, and integrations for HF, GitHub, and Anthropic models.
Visual workspace for managing multiple LLM-powered coding agent sessions and iterating on code, docs, and mockups. Combines WYSIWYG editors, session kanban, task tracking, and git tooling so developers can review, approve, and integrate agent-generated changes.
Builds knowledge-grounded AI agents by combining hybrid RAG retrieval with a visual, block-based workflow editor, keeping question-answering tied to your own data. Supports document import, reranking, MCP, and self-hosted deployment.
Packages reusable GitHub Copilot building blocks — agents, prompts, instructions, and skills — to make AI-assisted coding repeatable and standards-aligned for a team. Built around an RPI (Research, Plan, Implement) workflow in VS Code.
Packages Salesforce development workflows as on‑demand Agent Skills (SKILL.md, scripts, assets) that let AI assistants scaffold Apex/LWC, author Flows, run SOQL, and manage metadata and permission sets. Optimized for Agentforce Vibes and usable by any tool that supports the Agent Skills specification.
Unifies team email, chat, docs, tasks, CRM, calls and AI agents into a single workspace with bidirectional @-linking and a shared, exportable team memory.
Drives penetration testing from chat commands, orchestrating 100+ security tools through an MCP-native multi-agent engine on CloudWeGo Eino. Adds attack-chain graphs, risk scoring, and human-in-the-loop approval gates for authorized use.
Provides adaptive workflow steering rules for AI coding agents to guide development across Inception, Construction, and Operations phases. Includes opt-in extensions (security, testing), IDE/agent integrations (Cursor, Kiro, Amazon Q, Copilot, Claude), and human-in-the-loop approval points.
Provides a frontend-design skill plus 20 steering commands and curated anti-patterns to steer LLMs toward clearer, accessible UI designs. Designed to plug into AI harnesses (Cursor, Claude/Gemini CLI, code agents) for auditing, critiquing, and polishing interfaces.
Combines a vector store, Cypher-style graph queries, and on-device LLM inference in one Rust engine, with a graph neural network that reranks results and adapts to query patterns in under a millisecond. Services ship as self-contained .rvf containers.
Agent-first development platform: spawn autonomous agents that plan, edit, run terminals, and drive a browser to verify their own work, returning reviewable artifacts like plans and screenshots. Defaults to Gemini 3 Pro; also runs Claude and GPT-OSS.