Search Results for "ofn-layer-aligner"

We build for developers who need a reliable, production-ready data layer for AI applications. Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. ...

Phantasm offers toolkits to create a human-in-the-loop approval layer to monitor and guide AI agents' workflows in real-time, ensuring safety and reliability in AI operations.

Notte is an open-source browser framework that enables the development and deployment of web-based AI agents. It introduces a perception layer that transforms web pages into structured, navigable maps described in natural language, allowing agents to interact with the internet more effectively. Notte is designed for building scalable and efficient browser-based AI applications.

Wren AI is a SQL AI Agent for data teams to get results and insights faster by asking business questions without writing SQL, and it's open-source. Wren AI has implemented a semantic engine architecture to provide the LLM context of your business; you can easily establish a logical presentation layer on your data schema that helps LLM learn more about your business context. With Wren AI, you can process metadata, schema, terminology, data relationships, and the logic behind calculations and aggregations with “Modeling Definition Language”, to generate accurate SQL queries with semantic context. When starting a new conversation in Wren AI, your question is used to find the most relevant tables. ...

Semantic Router is a superfast decision-making layer for your LLMs and agents. Rather than waiting for slow, unreliable LLM generations to make tool-use or safety decisions, we use the magic of semantic vector space — routing our requests using semantic meaning. Combining LLMs with deterministic rules means we can be confident that our AI systems behave as intended. Cramming agent tools into the limited context window is expensive, slow, and fundamentally limited.

Mastra is a TypeScript-first framework for building AI-powered applications and agents, designed to take projects from prototype to production on a modern JavaScript/TypeScript stack. It integrates cleanly with React, Next.js, and Node-based backends, but can also run as a standalone server, giving teams flexibility in how they deploy their AI logic. At its core, Mastra provides abstractions for agents, workflows, tools, memory, retrieval, and model routing, so developers can focus on...

...The project includes tooling for registering agents with AIOS by uploading them via a command-line interface, enforcing a consistent naming scheme that matches the local folder layout. A companion tooling layer lets agents call external tools described in the tools.md documentation, enabling them to orchestrate APIs, retrieval pipelines, and other utilities in response to LLM decisions.

...Chidori is an open-source orchestrator, runtime, and IDE for building software in symbiosis with modern AI tools. When using Chidori, you author code with python or javascript, we provide a layer for interfacing with the complexities of AI models in long-running workflows. We have avoided the need for declaring a new language or SDK in order to provide these capabilities so that you can leverage software patterns that you are already familiar with.