#Japan #Tokyo #AI API #Quantum Box #Tachyon Agent

Quantum Box Launches Tachyon Agent API

Quantum Box, a leading company based in Shibuya, Tokyo, has officially launched the Tachyon Agent API, a groundbreaking development platform for autonomous AI agents that fully complies with the Model Context Protocol (MCP). This service allows AI agents to think independently, learn continuously, and execute tasks until they achieve their designated goals, marking a new era in API technology for automating complex business processes.

Background and Purpose

With the rise of generative AI, numerous APIs have emerged that focus solely on single-instance reasoning and text generation. However, traditional AI APIs have been limited in their ability to autonomously pursue long-term objectives or continuously improve. Quantum Box aims to address these limitations with a vision of making technology accessible to everyone, enhancing operational efficiency, and alleviating workforce shortages by developing a practical platform for autonomous AI agents.

Features of Tachyon Agent API

Autonomous Execution and Goal Achievement
The Tachyon Agent API allows for complete autonomous execution, enabling AI agents to finish complex tasks without human intervention. The agents persist in task execution until they reach the set goals, showcasing a commitment to perseverance. Moreover, through recursive execution, the agents learn and optimize their processes continuously, ensuring that they become progressively more efficient.

Enterprise-Ready Solutions
The API is designed for enterprise use, offering a secure execution environment coupled with 24/7 Japanese language support.

Key Differences from Other AI APIs

• - Autonomous Execution System: The API incorporates recursive task processing capabilities, which allow the agents to automatically recover from failures and execute alternative methods as needed. Progress can be monitored in real-time.
• - MCP Compliance: The Tachyon Agent API is fully compliant with the MCP, ensuring high interoperability and easy integration of custom tools.
• - Multi-Agent Collaboration: The platform facilitates parallel and distributed processing among multiple agents, enabling real-time information sharing and role delegation between agents.

Primary Use Cases

1. Automated Scheduling and Meeting Setting: The API automates the process of aligning participants' available times, booking meeting rooms, preparing materials, and even rescheduling activities.
2. Assistance in Proposal and Quotation Creation: It can automatically calculate optimal quotes from previous cases and generate proposals tailored to specific requirements, including analysis of competitive pricing.
3. Enhancing Sales and Customer Management: The platform assists in scoring potential clients, determining optimal proposal timings, sending contract renewal notifications, and automating the creation of progress reports for negotiations.
4. Automation of Document and Data Management: This includes organizing invoices, receipts, linking with accounting systems, managing contract expiration dates, and overseeing compliance with legal document retention periods.

Technical Infrastructure and API Specifications

The Tachyon Agent API is built on a scalable API infrastructure utilizing GraphQL and gRPC protocols. The frontend is constructed using TypeScript, while Rust supports the backend. Key endpoints have been established to handle streaming responses and tool invocations. Future developments include support for multimodal interactions and agent memory functionalities.

Quantum Box also offers business automation solutions, development support, and consulting services that leverage the Tachyon Agent API, ensuring comprehensive assistance from API implementation to custom solution deployment.

Pricing Plans and Availability

Starting today (October 28), applications for the beta version Proof of Concept (PoC) are now being accepted. Interested users should reach out through the contact details provided below.

Sign up for the PoC here

Understanding the Model Context Protocol (MCP)

The Model Context Protocol (MCP), proposed by Anthropic in November 2024, is an open standard designed to standardize how AI systems integrate with external tools and data sources. It allows for common interfaces for file reading, function calls, and contextual prompt exchanges, simplifying the integration of AI assistants with business systems. Major AI providers, including OpenAI and Google DeepMind, have adopted MCP, facilitating its widespread adoption industry-wide. The Tachyon Agent API's full compliance with MCP enhances interoperability and safe data integration. Furthermore, the API aims to expand connections within the MCP ecosystem to seamlessly integrate various internal and external tools and services, thereby improving corporate information utilization.

Executive Comment

Taketoku Fukuyama, CEO and CPO of Quantum Box, stated, "Our vision is to create a world where everyone can benefit from the latest technologies. The Tachyon Agent API stands apart from traditional AI APIs as an infrastructure that thinks, learns, and acts on behalf of humans. We aspire to create a society where people can break free from routine tasks and focus on more creative endeavors."

Company Overview

Along with the Tachyon Agent API, Quantum Box offers several products aimed at streamlining business operations, including Bakure, an integrated B2B platform that automates sales flow and synchronizes data across various software, and Library, a knowledge OS that connects documents, people, and reference information while visualizing update histories and sources for enhanced reuse.

Founded on October 9, 2020, Quantum Box is based at 1-10-8 Dogenzaka, Shibuya, Tokyo, with a secondary location in Sapporo. From generative AI development and consulting to system development and rapid web release services, Quantum Box is dedicated to fostering digital transformation across industries.

For more details about the services or inquiries, please visit their official website or contact them at [email protected].