Inside a partnership showing how open-source platforms and startups are scaling autonomous driving beyond the lab.
Updated
January 8, 2026 6:30 PM
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A Robotaxi prototype developed by TIER IV. PHOTO: TIER IV
Autonomous driving is often discussed in terms of futuristic cars and distant timelines. This investment is about something more immediate. Japan-based TIER IV has invested in Turing Drive, a Taiwan startup that builds autonomous driving systems designed for controlled, everyday environments such as factories, ports, airports and industrial campuses. The investment establishes a capital and business alliance between the two companies, with a shared focus on developing autonomous driving technology and expanding operations across Asia.
Rather than targeting open roads and city traffic, Turing Drive’s work centres on places where vehicles follow fixed routes and move at low speeds. These include logistics hubs, manufacturing facilities and commercial sites where automation is already part of daily operations. According to the release, Turing Drive has deployments across Taiwan, Japan and other regions and works closely with vehicle manufacturers to integrate autonomous systems into special-purpose vehicles.
The investment also connects Turing Drive more closely with Autoware, an open-source autonomous driving software ecosystem supported by TIER IV. Turing Drive joined the Autoware Foundation in September 2024 and develops its systems using this shared software framework. TIER IV’s own Pilot.Auto platform, which is built around Autoware, is used across applications such as factory transport, public transit, freight movement and autonomous mobility services.
Through the alliance, TIER IV plans to work with Turing Drive to further develop autonomous driving systems for these controlled environments, while strengthening its presence in Taiwan and the broader Asia-Pacific region. The collaboration brings together software development and on-the-ground deployment experience within markets where autonomous driving is already being tested in real operational settings.
“This partnership with Turing Drive represents a significant step forward in accelerating the deployment of autonomous driving across Asia”, said TIER IV CEO Shinpei Kato. “At TIER IV, our mission has always been to make autonomous driving accessible to all. By collaborating with Turing Drive, which has demonstrated remarkable achievements in real-world deployments in Taiwan, we aim to deliver autonomous driving that enables a safer, more sustainable and more inclusive society”.
“We are thrilled to establish this strategic alliance with TIER IV, a global leader in open-source autonomous driving”, said Weilung Chen, chairman of Turing Drive. “In Taiwan, autonomous driving deployment is gaining significant momentum, particularly across logistics hubs, ports, airports and industrial campuses. By combining our field expertise with TIER IV's world-class Pilot.Auto platform, we aim to accelerate the development of practical, commercially viable mobility services powered by autonomous driving”. Overall, the investment highlights how autonomous driving in Asia is being shaped by operational needs and gradual integration, rather than headline-grabbing demonstrations.
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As workplace knowledge spreads across chats, AI firms are building systems that can structure, retrieve and preserve it over time.
Updated
May 11, 2026 5:24 PM
A messaging app on a phone. PHOTO: ADOBE STOCK
Votee AI, an enterprise AI company headquartered in Hong Kong, has partnered with its Toronto-based research lab Beever AI to launch Beever Atlas. The new platform is designed to turn workplace chats into searchable knowledge that AI systems can retrieve and understand.
The release focuses on a growing issue inside organisations. Much of today’s workplace knowledge now exists inside chat platforms such as Slack, Microsoft Teams, Discord and Telegram. Important discussions, project decisions and technical information often disappear into long message histories that are difficult to search later.
Beever AI developed the platform to organise those conversations into a structured system for AI assistants. The software connects with Telegram, Discord, Mattermost, Microsoft Teams and Slack, then converts conversations into linked records of people, projects, files and decisions.
The collaboration combines Votee AI’s enterprise infrastructure work with Beever AI’s research around AI memory systems. The companies are releasing two versions of the product. The open-source edition is aimed at individual developers, researchers and creators. The enterprise edition is designed for banks, government agencies and larger organisations with stricter security requirements.
The release also reflects a broader shift happening across the AI industry. Companies are increasingly looking at how AI systems store and retrieve long-term knowledge, rather than relying solely on large context windows or search-based retrieval.
Earlier this year, OpenAI founding member and former director of AI at Tesla Andrej Karpathy discussed the growing need for what he described as “LLM Knowledge Bases.” He argued that AI systems need structured and evolving memory rather than depending only on context windows and vector search.
Beever Atlas approaches that problem through workplace communication. Instead of focusing mainly on uploaded files, the system is designed around conversations that happen daily across team chat platforms. It can also process images, PDFs, voice notes and video files within the same searchable system.
The companies say the software is designed to work directly with AI assistants and coding tools such as Cursor, AWS Kiro and Qwen Code. Integrations for OpenClaw and Hermes Agent are expected later in 2026.
Pak-Sun Ting, Co-Founder and CEO of Votee AI said: "Hong Kong has always been known for property and finance. Beever Atlas is proof that world-class AI infrastructure can emerge from an HK-headquartered company and be shared openly with the world. Every growing organization faces the same silent liability: conversational knowledge loss. Beever Atlas turns this perishable resource into a compounding organizational asset."
A large part of the enterprise version focuses on privacy and access control. The system mirrors permissions from Slack and Microsoft Teams so users can only retrieve information they are already authorised to access. Permission updates are reflected automatically when access changes inside company systems.
The enterprise edition also includes audit logs, encryption controls and data retention settings for organisations handling sensitive internal data. Companies can run the software entirely inside their own infrastructure using Docker and connect it to their preferred AI models through LiteLLM.
The companies argue that organising information is more useful than simply storing chat archives. Jacky Chan Co-Founder and CTO of Votee AI said: "The key technical decision was to treat agent memory as a knowledge engineering problem, not a retrieval problem. Structure beats similarity — a typed graph of who works on what is more useful to an AI than vector search over a Slack archive."
The software also includes protections against prompt injection attacks and systems designed to reduce hallucinated responses. According to the companies, the AI is designed to return “I don't know” with citations when confidence is low instead of generating unsupported answers.
As workplace communication becomes increasingly fragmented across chat platforms, companies are beginning to treat internal conversations as information that AI systems can organise, retrieve and build on. Beever Atlas reflects a broader push to turn everyday workplace communication into long-term organisational memory.