Homai Tech

At Homai Tech, we believe that with the surging power of AI, human beings will have a much better chance to pursue their dreams without having to spend the majority of their awake time on repetitive work. Let's say 5 years from now (in 2030), that will come true - work will be optional... https://lnkd.in/gCjGPw8C

Crows Trading Trash for Food - And the Belief Homai Tech Pursue About AI In Sweden, something unusual is happening: people are training crows to pick up cigarette butts. A small device placed outdoors works simply. When a crow drops a cigarette butt into the slot, the machine dispenses a food pellet. No noise, no commands - just a straightforward agreement between nature and humans. One billion cigarette butts every year, and change begins with something very small. What surprises me isn't the crow itself. It's how humans took the time to sit down, listen to nature, understand the bird's behavior, and create a system where both sides could collaborate. Sometimes, solving big problems doesn't require complex technology. We just need to design a solution smart enough, subtle enough, and harmonious enough with the world around us. In a world that talks too much about "automation," "acceleration," and "disruption," sometimes the key lies in making things more accessible, simpler, and more human. This only strengthens our commitment to Homai Tech's mission and vision: to make AI accessible by connecting AI research with real-world applications - so that small and medium enterprises (SMEs) can also harness its transformative power. We're building toward a future where every business, regardless of size, can tap into the power of AI. We believe: - Technology doesn't need to be complex to be powerful. - AI doesn't need to be massive to create change. - Businesses don't need to be large to deserve empowerment. Just as that small machine can shift the behavior of an entire bird species, the right AI solutions - lean and human-centered - can help businesses untangle operational knots, bit by bit. Crows can't speak. But they act to protect the environment. And perhaps every major change starts with a very small system. A very simple idea. And a very human belief: "That technology can collaborate with people, rather than dominate them." Homai simply wants to do that: create our own "small boxes" - small, yes, but smart enough, human enough, and sufficient to inspire lasting collaboration between humans and technology. #EcoInnovations #SustainableLiving #SimpleSolution #HumanCentricAI #BusinessGrowth #SMEs #Innovation

AI for SMEs: Why Every Industry Needs a "Tailored" Approach? Legal: High Stakes, High Precision In law, accuracy is absolute. A single error in a contract means severe consequences, making caution understandable. Generic AI misses the nuanced, context-dependent legal language. Until clear legal standards exist, the risk outweighs the benefit.   HR: The Paradox of the "Human Touch" AI filters CVs fast, but human recruiters are still essential for assessing cultural fit. Concerns over fairness and algorithmic bias are valid. Since candidate data is often poorly digitized, personal human understanding remains optimal.   Healthcare: Compliance Over Code A clinic needs more than an accurate model; strict patient data confidentiality and regulatory compliance are non-negotiable. The core question is liability: "If the AI errs, who is responsible?" Gaining trust from experienced medical staff is a significant hurdle.   Logistics: When Data Isn't Ready Route optimization is ideal, but transport businesses using Excel, handwritten notes, and legacy GPS face a different reality. The issue is "dirty" data, not poor algorithms. IoT investment remains a heavy cost for capital-thin SMEs.   Retail: The Digital Gap Small shops rely on cash and notebooks, lacking basic CRM. The problem isn't a lack of AI, but a lack of digital infrastructure. Without data on customer behavior, "personalization" and "inventory optimization" are huge questions.   Fintech: Regulator as the Second "Customer" Businesses must serve consumers while strictly complying with regulations. AI implementation requires explaining every decision (explainability). Regulatory uncertainty often pushes companies toward the safer option: manual processing.   Real Estate: Local Knowledge Still Wins AI appraises homes, but successful brokers rely on "tacit knowledge" - local networks, owner psychology, and hidden insights - which are hard to encode. Inaccurate land data also makes AI inputs unreliable.   Education: When Culture "Resists" Change Schools change slowly. Teachers worry AI strips away the human element and question content accuracy. Budgets prioritize staff and facilities over new software. AI must be positioned as a "co-pilot," and adoption demands immense patience.   Regardless of the industry, SMEs face common barriers: capital, data, expertise, and cultural inertia. However, the manifestation of these barriers varies greatly. Understanding these specifics - at the business model level - is the line between success and failure.   This is why we believe in Agentic AI. Instead of offering generic AI tools, Homai Tech builds Autonomous Agents trained to understand your unique industry context. Our AI doesn't just answer questions; it knows how to act in alignment with your specific processes and culture.   Let technology adapt to the business, don't force the business to bend to technology. #AIsme #Savingtime #AIapply #LogisticsTech #proptech #HomaiTech #optimization #automate

THE AI ADOPTION GAP: What's Really Holding SMEs Back? The Technical Reality Let's be honest: finding someone who actually knows how to implement AI is like finding a unicorn. And even if you do, your existing systems probably weren't built to talk to each other. That customer data? It's scattered across different databases, Excel files, and someone's personal laptop. Upgrading everything to make it AI-ready isn't just expensive - it's a complete overhaul most SMEs can't afford while keeping the lights on. The Money Problem CFOs are asking the right question: "Show me the return on this investment." And honestly? Nobody can give them a straight answer. Implementation costs are high, maintenance is ongoing, and the payback timeline is fuzzy. For businesses on tight margins, betting big on AI feels like gambling with money you can't afford to lose. The People Challenge Here's what really slows things down: your team doesn't see how AI solves their actual, daily problems. They've built their careers on intuition and hands-on experience. Now you're asking them to trust an algorithm? Add in the fear that automation might eliminate jobs, and you've got internal resistance at every level. The Regulatory Headache Data privacy laws aren't just checkboxes. They're serious legal obligations with real penalties. And AI regulations? They're evolving faster than anyone can keep up. For SMEs without legal teams, one mistake could be catastrophic. But here's what makes this even more complicated: these challenges play out differently depending on your industry. I'll break down what this looks like in my next post. What's the biggest barrier you're facing? Drop a comment - I'd genuinely like to hear your experience. #ArtificialIntelligence #SMEs #DigitalTransformation #Asia #BusinessStrategy #Innovation #AIAdoption #AIVietnam #AIThailand #AIJapan

Building an Effective AI Deployment Strategy for SMEs: 4 Core Pillars Statistics reveal that 80-90% of AI projects fail due to strategic errors, not weak technology. Apply this 4-pillar framework to optimize your success rate: 1. Identify Quantifiable Pain Points Focus on your most resource-draining problem, measured by concrete metrics (cost, time, error rate). Set a goal to demonstrate clear ROI within 90 days—for example: reducing quote processing time from 2 days to 4 hours. 2. Prepare Data and Workflows Map your current process (As-Is), clearly distinguishing work requiring human judgment from repetitive tasks suitable for AI. Ensure data is cleaned and standardized to avoid "Garbage In, Garbage Out." 3. Implement Phased Pilots Apply a 90-day strategy with a step-by-step approach instead of "Big Bang": First 30 days run a pilot with a small team, next 30 days optimize based on real feedback, final 30 days scale after establishing proof of success. 4. Manage Human Change Communicate clearly: AI doesn't replace jobs—it elevates employee roles. Organize hands-on training and build internal AI Champions to foster a culture of AI learning. Integrate Governance elements from the start, including transparency and security. Begin by selecting 1 pain point and mapping the workflow today instead of rushing to buy expensive tools. #AgenticAI #SME #DigitalTransformation #AIStrategy #DigitalLeadership #AIforBusiness