Intelligent Space Management

Workspace strategy has entered a new phase. It is no longer about how much space a company has. It is about how intelligently that space is used. And leaders preparing for 2026 are prioritizing one principle above everything else: Grow with real demand, not assumptions. Because productivity is strengthened when space expands in alignment with how people truly work, not based on forecasts that may never materialize. Why right-sizing matters now: 1/. Start small and expand with data Space should grow only when utilization shows the need, not based on predictions. 2/. Protect cost discipline Lower fixed costs create room for strategic investment in talent, technology, and capability development. 3/. Support hybrid work with flexibility Teams return in different rhythms. Workspace must adapt to those rhythms instead of forcing new habits. 4/. Turn scalability into an operational advantage When space can grow or contract without disruption, leaders gain the freedom to adjust quickly. Adaptability itself becomes a competitive edge. A recent industry report shows that 59% of businesses plan to expand office space through coworking in the next two years. This confirms that flexible, demand-driven space strategies are rapidly becoming standard. A growing number of companies are choosing to begin with smaller suites or open-desk configurations, expanding only as more employees choose to be in-person. This approach protects budgets while ensuring every square foot serves a clear purpose. That is where WorkSocial | Shared Office Space | Enterprise Coworking (TM) supports forward-thinking companies planning for 2026. Start with day passes, open desks or a small suite. Scale to larger spaces and private setups when data proves the need. Expand based on real usage, not guesswork. Workspace becomes a strategy, not a fixed cost. Is your 2026 plan based on real utilization intelligence or on forecasted assumptions? How are you preparing your workspace model to stay flexible, scalable, and financially responsible?

🚀 𝐒𝐩𝐚𝐭𝐢𝐚𝐥𝐋𝐌 𝐢𝐬 𝐡𝐞𝐫𝐞 – 𝐚𝐧 𝐀𝐈 𝐭𝐡𝐚𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐬 𝐬𝐩𝐚𝐜𝐞𝐬, 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐰𝐨𝐫𝐝𝐬. It started as a research project, but now it’s open-source, pretrained, and ready for anyone to try on Hugging Face. So, what does it actually do? 👉 A simple phone video goes in. 👉 It turns that video into a 3D map of the space. 👉 Then, instead of just saying “object detected,” it understands what’s happening. For example, instead of - “𝐅𝐥𝐚𝐭 𝐬𝐮𝐫𝐟𝐚𝐜𝐞 𝐝𝐞𝐭𝐞𝐜𝐭𝐞𝐝.” 𝐈𝐭 𝐬𝐚𝐲𝐬 - “𝐓𝐡𝐚𝐭’𝐬 𝐚 𝐰𝐚𝐥𝐥, 𝐰𝐢𝐭𝐡 𝐚 𝐝𝐨𝐨𝐫 𝐢𝐧 𝐢𝐭. 𝐓𝐡𝐚𝐭’𝐬 𝐚 𝐬𝐨𝐟𝐚, 𝐭𝐡𝐢𝐬 𝐛𝐢𝐠, 𝐟𝐚𝐜𝐢𝐧𝐠 𝐭𝐡𝐚𝐭 𝐝𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧.” And the best part—it gives this information as clean, structured data. Perfect for AR, robotics, indoor mapping, and more. This is more than object detection. It’s vision + language + structure. Not just pixels → but meaning. Built on LLaMA + Quinn, trained on real-world video, and fully open-source. Oh, and one more thing - GenAI AgentOS just got open-sourced too – a lightweight framework for running multi-agent workflows. 🔗 Check it out here - GitHub: https://bit.ly/4kzE1Mt   #generativeai        #aiagents            #llms         #opensource

Three months ago, I watched a spatial AI system fail at something humans do effortlessly. It could detect every chair and table in a room perfectly. But it couldn't understand that the chair was positioned for conversation, or that the cluttered area blocked wheelchair access. The problem? We're treating 3D data as geometry instead of knowledge. 𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝗰𝗵𝗮𝗻𝗴𝗲𝗱 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴: Scene graphs transform point clouds from passive visualization into queryable spatial intelligence. Each object becomes a node. Relationships become edges. Your room layout becomes a knowledge base that LLMs can reason about naturally. Instead of complex geometric queries, you ask: "Find all chairs positioned for conversation" or "Identify areas blocking wheelchair access." 𝗧𝗵𝗶𝘀 𝗶𝘀 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝘀𝗽𝗮𝘁𝗶𝗮𝗹 𝗔𝗜: Current systems are reactive - they process what they see. The next generation will be contextually intelligent - they understand what spaces 𝑚𝑒𝑎𝑛. Think construction sites that understand workflow patterns, warehouses that optimize material flow, retail spaces that predict customer behavior. 𝗦𝗽𝗮𝘁𝗶𝗮𝗹 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝘄𝗶𝗹𝗹 𝗯𝗲𝗰𝗼𝗺𝗲 𝘁𝗵𝗲 𝗺𝗶𝘀𝘀𝗶𝗻𝗴 𝗽𝗶𝗲𝗰𝗲 𝘁𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗔𝗜 𝘁𝗿𝘂𝗹𝘆 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀. I've built a complete Python tutorial showing exactly how to create this system: → DBSCAN clustering for object extraction → NetworkX for scene graph construction → OpenUSD export for production systems → LLM integration for natural language queries Everything included: code, datasets, detailed explanations. 👉 Complete tutorial here: https://lnkd.in/eviX6t_H What spatial intelligence applications are you building?

For many years, companies invested heavily in flagship, highly customised #offices. A space was a statement. Design was inflexible. Layouts rarely changed. This created impressive environments, but it created rigidity as well. Then came #workplace strategy. The industry shifted toward office behaviour analysis. Understanding how people move, collaborate and focus became essential. But the reality is simpler. Teams continuously evolve, even more now with hybrid work and AI as a disruptor. Patterns shift. Overall analysis becomes difficult when everything that is analysed is in constant motion. We are entering a new era of the workplace. One where decisions are driven by efficiency, adaptability and return on investment. Offices are becoming more value-focused. Less about large capital expenditure. More about operational flexibility. Less rigid. More modular. Less static. More dynamic. Modularity changes the economics of space. It requires thoughtful investment at the beginning, but it creates environments that evolve naturally with the organisation. From traditional serviced offices, the concept moves toward 𝗼𝗳𝗳𝗶𝗰𝗲 𝗮𝘀 𝗮 𝘀𝗲𝗿𝘃𝗶𝗰𝗲 𝘄𝗶𝘁𝗵 𝗮 𝘁𝘄𝗶𝘀𝘁. Where the service is constantly adapted to the new market dynamics. A model where companies gain the best possible space at a lower cost per use and with far more adaptability. This is the direction the industry is taking. Spaces envisioned for flexibility. Spaces designed to adjust. Spaces created to perform. The future of work will not be defined by how impressive an office looks on day one. It will be defined by how intelligently it adapts yearly or even quarterly. This is where value will be compounded. A modular foundation. A dynamic office. A better experience for current and future tenants. Based on deep spatial intelligence and built to create and adjust compliant, functional and creative layouts, 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝟯𝗗 𝗦𝗽𝗮𝗰𝗲 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 is a foundational layer in the office industry shift we are witnessing.

Challenges and solutions in implementing a hybrid working model for facility management, particularly focusing on space management, transportation, food & beverages, and other services: 1. Space Management Challenges: Underutilization or overcrowding of office space on certain days. Difficulty in forecasting space requirements due to fluctuating attendance. Desk sharing and sanitization concerns. Lack of real-time visibility into occupancy. Solutions: Implement desk booking systems with real-time analytics. Use IoT and sensor-based tech to monitor occupancy and usage trends. Adopt flexible seating plans and agile workstations. Define sanitization protocols between shared usage. 2. Transportation Challenges: Inefficient routing due to unpredictable employee presence. Under- or over-utilized transport assets. Difficulty in aligning transport schedules with flexible work hours. Managing last-mile connectivity. Solutions: Introduce on-demand or app-based transport booking systems. Use AI-based route optimization to dynamically plan pickups and drop-offs. Collaborate with third-party mobility providers for flexible solutions. Encourage carpooling and green commuting options. 3. Food & Beverages Challenges: Wastage due to unpredictable headcount. Managing vendor contracts and pricing for fluctuating demand. Ensuring food safety in shared spaces. Limited operating hours may not suit flexible work patterns. Solutions: Use pre-ordering systems or F&B booking apps. Partner with corporate food aggregators for flexible meal plans. Introduce vending machines and self-service kiosks. Shift to modular kitchen models for scalable operations. 4. Other Services (Housekeeping, Security, Mailroom, etc.) Challenges: Overstaffing or understaffing during peak or lean days. Need for higher hygiene standards. Inefficient mail/package handling with inconsistent office presence. Monitoring and access control for hybrid users. Solutions: Use AI-based workforce planning tools for smart rostering. Adopt smart lockers for mail/package handling. Upgrade to touchless access and surveillance systems. Use mobile apps for service requests and visitor management. Integrated Solutions Across Services: Deploy an Integrated Workplace Management System (IWMS) to centralize operations. Leverage data analytics to predict usage patterns and optimize services. Foster employee communication tools to keep them informed and engaged. Embrace sustainability practices across services to align with hybrid work goals. IFMA Workplace Evolutionaries Hub France Workplace Evolutionaries #ifma #hybrid