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Description

Backboard is an advanced AI infrastructure platform that offers a comprehensive API layer, enabling applications to maintain persistent, stateful memory and orchestrate seamlessly across numerous large language models. This platform features built-in retrieval-augmented generation and long-term context storage, allowing intelligent systems to retain, reason, and act consistently during prolonged interactions instead of functioning like isolated demos. By effectively capturing context, interactions, and extensive knowledge, it ensures the appropriate information is stored and retrieved precisely when needed. Additionally, Backboard supports stateful thread management with automatic model switching, hybrid retrieval, and versatile stack configurations, empowering developers to create robust AI systems without the need for cumbersome workarounds. With its memory system consistently ranking among the top in industry benchmarks for accuracy, Backboard’s API enables teams to integrate memory, routing, retrieval, and tool orchestration into a single, simplified stack, ultimately alleviating architectural complexity and enhancing overall development efficiency. This holistic approach not only streamlines the implementation process but also fosters innovation in AI system design.

Description

Humiris AI represents a cutting-edge infrastructure platform designed for artificial intelligence that empowers developers to create sophisticated applications through the integration of multiple Large Language Models (LLMs). By providing a multi-LLM routing and reasoning layer, it enables users to enhance their generative AI workflows within a versatile and scalable framework. The platform caters to a wide array of applications, such as developing chatbots, fine-tuning several LLMs at once, facilitating retrieval-augmented generation, constructing advanced reasoning agents, performing in-depth data analysis, and generating code. Its innovative data format is compatible with all foundational models, ensuring smooth integration and optimization processes. Users can easily begin by registering, creating a project, inputting their LLM provider API keys, and setting parameters to generate a customized mixed model that meets their distinct requirements. Additionally, it supports deployment on users' own infrastructure, which guarantees complete data sovereignty and adherence to both internal and external regulations, fostering a secure environment for innovation and development. This flexibility not only enhances user experience but also ensures that developers can leverage the full potential of AI technology.