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.
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Circles is using AI to turn telecom support from a cost centre into a faster, more personalised growth engine
Updated
May 1, 2026 2:04 PM
A woman holding a phone while using a laptop. PHOTO: ADOBE STOCK
Circles, a Singapore startup that builds software for digital telecom operators, has launched an AI concierge as part of its partnership with OpenAI. The release marks a new step in the company’s effort to modernise how telecom providers serve and retain customers. The move reflects a wider shift in the telecom sector. Many operators still rely on older support systems that can be slow, fragmented and costly to run. AI is now being tested as a way to improve service while creating new revenue opportunities.
Circles said the concierge is built on OpenAI’s API platform and sits within what it calls an AI-native telecom stack. In practical terms, the system is designed to handle customer support, account changes and personalised offers through automated interactions.
One part of the platform is called CareX. According to the company, it can deal with billing issues, service requests and network-related problems. Circles said CareX currently resolves 85% of customer queries globally without human intervention and reaches a 95% resolution rate on end-to-end tasks. That matters because customer support remains one of the larger operating costs for telecom providers. Faster automated handling could lower pressure on service teams while reducing wait times for users.
The second part of the platform is Xplore IQ, which focuses on revenue growth. The tool is designed to predict what a customer may need, recommend a suitable plan or offer and complete upgrades or downgrades automatically. Circles said the early rollout has led to a 22% rise in average revenue per user for Circles.Life Singapore. It also said personalised offers helped reduce customer churn by 9%.
"AI should empower users - not force-fit into outdated journeys. OpenAI's role has been critical in enabling Circles to scale this vision globally. With the AI concierge, we are moving beyond providing simple answers to delivering real-world outcomes, along with balancing cost and latency to maximize value for operators and customers alike", said Awais Malik, Global Chief Growth Officer at Circles.
"Circles is demonstrating how advanced AI can modernize essential industries like telecommunications at scale. By combining frontier models with multi-agent systems, they are enabling telecom operators globally to deliver faster, smarter and more personalized customer experiences. This milestone is a strong example of how AI can deliver tangible value for businesses and customers they serve", Oliver Jay, Managing Director, International for OpenAI, added.
Together, the tools are intended to connect customer service, operations and sales into one system. Rather than treating support and monetisation as separate functions, the company is combining them into a single digital layer.
Circles said the partnership will continue over the next two years as both companies work toward a more autonomous telecom model. Whether that vision is achieved remains to be seen, but the direction is clear: telecom operators are increasingly treating AI as core infrastructure rather than an optional add-on.