NeuBird is the Agentic Operations Center. As production outgrows human understanding and agents arrive to fill the gap, NeuBird gives the enterprise one secure, audited point of access to its telemetry and its LLMs, queried in place with no data copied and tokens spent once, and a central memory that records every investigation, by human or agent, versioned and cited inside the customer's own environment. Working alongside the engineers who run production, NeuBird uses Context Engineering to catch incidents before the page and resolve them in minutes with the causal chain shown. Managers see every piece of agentic work in one view, and the enterprise's own agents connect over MCP to inherit the same context, memory, guardrails and audit trail. Backed by Xora Innovation, Mayfield and M12, NeuBird is headquartered in Redwood City, California. For more information, visit neubird.ai
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Most asset tracking tools offer one tagging method. GoCodes bundles four: patented QR code labels, real-time GPS trackers, Bluetooth beacons, and RFID/NFC tags.
Pick what fits each asset and manage everything from one cloud dashboard.
QR labels ship with every account at no extra charge. Stick them on tools, equipment, or inventory and scan with the GoCodes app (4.7 stars, App Store) or any phone browser. Check items in and out in seconds. Your team can be tracking assets within days, not months.
Built for trades and industrial companies. Contractors, school districts, manufacturers, and facilities teams use GoCodes to know exactly what they own, where it sits, and who touched it last.
Log maintenance schedules, service history, warranties, and equipment utilization. Create custom fields, rename defaults, and control access with role-based permissions. Reports generate in seconds.
Free trial available. No credit card, no setup fee, no app download required.
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CMEM Cloud
CMEM Cloud functions as the connective synchronization layer for claude-mem, facilitating universal memory access for AI agents through a private MCP link. The open-source framework of claude-mem captures notes while agents execute tasks, and CMEM Cloud mirrors this local memory, granting agents the ability to retrieve it smoothly across various sessions, devices, editors, and MCP-compatible clients. This cutting-edge system removes the necessity for users to constantly reiterate context, transfer previous notes, or begin anew, as it automatically logs key decisions, bug fixes, dead ends, environmental observations, architectural choices, and other structured insights in real-time. These important insights are stored in a temporal database, enabling searches based on meaning through vector recall, and can be accessed via a private MCP endpoint that any compatible agent can use for reading and writing purposes. The process begins with the setup of the local engine, followed by the activation of a secondary model that autonomously generates structured notes, syncing the local database with CMEM Cloud, and ultimately allowing for memory recall from any location. This method not only boosts efficiency but also cultivates a more collaborative atmosphere among agents, as they can share insights with ease and contribute to a more cohesive working environment. As a result, agents can work more effectively together, leveraging shared knowledge to enhance their collective performance.
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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).
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