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What is Trajectory?

Trajectory is a cutting-edge platform focused on continuous learning, aimed at transforming real-world product interactions into self-improving AI systems. By recognizing every change, retry, correction, re-prompt, and user endorsement as critical data points, it allows each product to develop into a fluid and responsive entity. The actions of users serve as a more accurate measure of task effectiveness than any conventional metrics can provide, and Trajectory offers teams a creative framework to monitor, direct, and enhance the intelligence that drives their products. With its user-friendly SDK, integration of Trajectory into AI applications is seamless, enabling teams to effortlessly capture user-generated signals like edits, corrections, and re-prompts. This capability aids teams in understanding the model's learning trajectory, steering it toward key objectives, and confidently executing updates. Trajectory proves especially valuable in situations where model performance can differ greatly across various contexts, making steerability a vital operational requirement rather than just an academic goal. By utilizing this platform, teams are empowered to not only adapt but also excel in swiftly evolving environments, ensuring they remain competitive and responsive to user needs. In an era of rapid technological advancements, the ability to leverage such adaptive tools is essential for sustained success.

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.

Media

Media

Integrations Supported

Clay
Decagon
Harvey AI
Rogo

Integrations Supported

Tanka

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Trajectory

Company Location

United States

Company Website

trajectory.ai/

Company Facts

Organization Name

EverMind

Company Location

United States

Company Website

evermind.ai/everos

Categories and Features

AI Infrastructure

Not specified

Categories and Features

AI Memory Layers

Not specified

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