EverOS vs. Beacon

EverOS is a persistent memory platform for AI agents that combines long-term context, multimodal ingestion, self-evolving skills, and cross-platform compatibility. The system is designed to sit inside an existing agent loop and retrieve relevant context before each large language model call. Rather than sending an entire conversation or knowledge history into the model every time, EverOS selects the most relevant stored memories for the current task. Its memory architecture is built to support low-latency retrieval while reducing token usage and maintaining continuity across sessions. EverOS also introduces self-evolving skills, which turn successful task executions into cases that can later be consolidated into reusable procedural knowledge. Repeated successful patterns can be promoted into shared skills that are available to multiple agents without requiring manual curation or brittle workflow logic. The platform accepts multimodal sources including PDFs, images, spreadsheets, documents, slides, URLs, and Markdown and automatically parses, chunks, and indexes them for retrieval. EverOS works with agent environments and interfaces such as Claude Code, Codex, OpenClaw, Hermes, MCP, and OpenAI- and Anthropic-compatible SDKs. Its Markdown-first portability model allows organizations to export memories in a readable, version-controllable format and move between hosted and self-managed deployments. Teams can start with EverOS Cloud or deploy the Apache 2.0 open source version on their own infrastructure using the same API and memory format. EverOS is designed for developers, AI infrastructure teams, and enterprises that want agents to retain context, learn reusable procedures, and operate more efficiently across tools and environments. EverOS achieves 93.05% on the LoCoMo long-term memory benchmark (research: arXiv:2601.02163).

Beacon is an open-source framework for telemetry and memory, tailored specifically for AI coding agents. This innovative tool captures agent sessions across diverse environments such as local setups, continuous integration (CI) systems, and cloud platforms, creating a searchable repository that benefits both individual developers and teams. With this functionality, users can effectively analyze workflows, troubleshoot agent performance issues, evaluate usage trends, identify potential security risks, and convert recorded sessions into reusable skills and agent memory. Beacon supports various agent frameworks, including Claude Code, Cursor, Codex, and OpenCode, as well as more than 20 other agent harnesses, while the Observe SDK enhances the instrumentation of cloud agents. It operates seamlessly in local environments or can connect to Beacon Cloud, which provides hosted session histories, valuable insights, analytics, collaborative features, and access to the MCP. The free plan of Beacon Cloud includes 50 findings, the ability to search session histories via the MCP, and options for sharing sessions. In contrast, the Pro version offers unlimited findings, expansive agent memory capabilities, reusable skills, comprehensive MCP access, and real-time notifications. Additionally, the Enterprise tier is tailored for large organizations, featuring organization-wide findings, deployment capabilities for endpoints and CI, approval workflows, single sign-on (SSO), role-based access control, audit logging, and dedicated customer support services. Each subscription tier is thoughtfully crafted to accommodate the diverse needs of developers and organizations striving to optimize their AI coding processes and enhance productivity.