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What is EverOS?
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).
What is Engram?
Engram is a sophisticated, fully managed system created to improve memory and contextual awareness for AI agents, allowing them to retain information, learn, and progress effectively as time passes. Instead of letting a vast array of unstructured conversations and events pile up, it skillfully converts disorganized interaction data into structured, enduring, and adaptable memories. Users can easily send raw text, full conversations, or pre-processed information through a REST API or Python SDK without any need for prior formatting. Engram then employs asynchronous processes to identify relevant information, streamline it by eliminating duplicates, and synchronize it with existing knowledge, leading to an improved memory state that operates independently of the application's core functions. It effectively manages inconsistencies and adapts to new preferences and changes in information over time, ensuring that the context remains pertinent and efficient. Furthermore, agents can quickly access prioritized memories using methods like vector similarity, BM25 keyword searches, or a blend of retrieval techniques, thus reducing the need for resending entire conversation histories. This innovative approach greatly boosts the interaction's efficiency and effectiveness, making AI agents more agile and better equipped to comprehend user requirements. Ultimately, Engram not only enhances the operational capabilities of AI agents but also fosters a more user-centric experience.
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free: $0/month. 3 Memory Spaces, 50,000 MCU/month, 100,000 Retrieval API calls/month.
Pro: $25/month (free during Early Access). 8 Memory Spaces, 250,000 MCU/month, 500,000 Retrieval API calls/month, includes Self-Evolving Skills.
Enterprise: Custom pricing. Custom limits, dedicated account manager, private deployment available.
Pro: $25/month (free during Early Access). 8 Memory Spaces, 250,000 MCU/month, 500,000 Retrieval API calls/month, includes Self-Evolving Skills.
Enterprise: Custom pricing. Custom limits, dedicated account manager, private deployment available.
Free Version
Pricing Information
$45 per month
Free Version
Supported Platforms
SaaS
On-Prem
Supported Platforms
SaaS
Customer Service / Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
Company Facts
Organization Name
EverMind
Date Founded
2025
Company Location
United States
Company Website
evermind.ai/everos
Company Facts
Organization Name
Weaviate
Date Founded
2019
Company Location
The Netherlands
Company Website
weaviate.io/product/engram
Categories and Features
AI Memory Layers
Not specified
Categories and Features
AI Memory Layers
Not specified