Timspark

𝗟𝗶𝗗𝗔𝗥 𝘀𝗰𝗮𝗻𝘀 are rich in data. 📡 The bottleneck starts after capture. 𝗔𝗘𝗖 𝘁𝗲𝗮𝗺𝘀 can scan a site fast. Turning 𝗿𝗮𝘄 𝗽𝗼𝗶𝗻𝘁 𝗰𝗹𝗼𝘂𝗱𝘀 into usable building elements and 𝗕𝗜𝗠-𝗿𝗲𝗮𝗱𝘆 𝗼𝘂𝘁𝗽𝘂𝘁𝘀 is the part that still eats up time. That’s where our team stepped in. For an AEC client, Timspark built a custom 𝗦𝗰𝗮𝗻-𝘁𝗼-𝗕𝗜𝗠 workflow that: • segments 𝗽𝗼𝗶𝗻𝘁 𝗰𝗹𝗼𝘂𝗱 𝗱𝗮𝘁𝗮 with 𝗠𝗟 • detects 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗮𝗹 𝗲𝗹𝗲𝗺𝗲𝗻𝘁𝘀 based on the client’s taxonomy • validates the output • converts it into 𝗕𝗜𝗠-𝗿𝗲𝗮𝗱𝘆 𝗺𝗼𝗱𝗲𝗹𝘀 for real project workflows Tech behind it: Python, TensorFlow, PyTorch, PCL, Pointcept, Azure GPU instances, Revit-compatible conversion logic. Result: ✅ ~𝟬.𝟴𝟱 𝗺𝗜𝗼𝗨 overall ~𝟱-𝗺𝗶𝗻𝘂𝘁𝗲 𝗿𝘂𝗻𝘁𝗶𝗺𝗲 in modern 𝗚𝗣𝗨 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀 less 𝗺𝗮𝗻𝘂𝗮𝗹 𝗺𝗼𝗱𝗲𝗹𝗶𝗻𝗴 𝗲𝗳𝗳𝗼𝗿𝘁 faster path from 𝗟𝗶𝗗𝗔𝗥 𝘀𝗰𝗮𝗻𝘀 𝘁𝗼 𝗕𝗜𝗠-𝗿𝗲𝗮𝗱𝘆 𝗼𝘂𝘁𝗽𝘂𝘁𝘀 Disclaimer: The solution is not an off-the-shelf product, but a client-specific engineering workflow built for delivery. Case study in comments. 👇 #ScanToBIM #LiDAR #PointCloud #BIM #AEC #DigitalTwin #ComputerVision #MachineLearning #Revit #ConstructionTech

𝗧𝗵𝗲 𝗜𝗧 𝘁𝗮𝗹𝗲𝗻𝘁 𝘀𝗵𝗼𝗿𝘁𝗮𝗴𝗲 𝗶𝘀 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗮𝗯𝗼𝘂𝘁 𝗮 𝗹𝗮𝗰𝗸 𝗼𝗳 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀. 👨💻 It is about 𝗳𝗮𝘀𝘁-𝗰𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝘀𝘁𝗮𝗰𝗸𝘀, 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗱𝗲𝗺𝗮𝗻𝗱, 𝗰𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗽𝗿𝗲𝘀𝘀𝘂𝗿𝗲, unrealistic "𝘂𝗻𝗶𝗰𝗼𝗿𝗻" roles, and location-related hiring complexity. 🌍 That is why scaling a tech team today requires more than posting a vacancy and waiting for the right CV. It requires 𝗳𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗰𝗮𝗽𝗮𝗰𝗶𝘁𝘆 built around your actual roadmap. ⚙️ At Timspark, we help companies close skill gaps with 𝗳𝗹𝗲𝘅𝗶𝗯𝗹𝗲 𝗼𝘂𝘁𝘀𝗼𝘂𝗿𝗰𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀, 𝗔𝗜 𝘀𝗽𝗲𝗰����𝗮𝗹𝗶𝘀𝘁𝘀, 𝗰𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲, 𝗗𝗲𝘃𝗢𝗽𝘀 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀, and 𝗘𝗨/𝗨𝗞-𝗳𝗼𝗰𝘂𝘀𝗲𝗱 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗰𝗮𝗽𝗮𝗰𝗶𝘁𝘆. 🚀 🔗 https://lnkd.in/em9MCyFJ Need to move faster without turning hiring into a bottleneck? 𝗟𝗲𝘁’𝘀 𝘁𝗮𝗹𝗸. 🤝 #ITOutsourcing #SoftwareDevelopment #TechTalent #DevOps #Cybersecurity #AIEngineering #StaffAugmentation #DedicatedTeams #Timspark

Great to see Olga Voronkova representing Timspark at London Tech Week 2026. Wishing her a productive event filled with valuable conversations, fresh insights, and new opportunities for collaboration in AI, enterprise tech, and innovation.

Finding the right software development partner isn’t easy — especially with 𝘀𝗼 𝗺𝗮𝗻𝘆 𝘃𝗲𝗻𝗱𝗼𝗿𝘀 𝗼𝗻 𝘁𝗵𝗲 𝗺𝗮𝗿𝗸𝗲𝘁. That’s why platforms like RightFirms are valuable for companies looking to compare 𝘃𝗲𝗿𝗶𝗳𝗶𝗲𝗱 𝘁𝗲𝗰𝗵 𝗽𝗿𝗼𝘃𝗶𝗱𝗲𝗿𝘀, explore expertise areas, and make more informed partnership decisions. At Timspark, we help businesses build and scale digital products through 𝗰𝘂𝘀𝘁𝗼𝗺 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁, 𝗱𝗲𝗱𝗶𝗰𝗮𝘁𝗲𝗱 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀, 𝗔𝗜/𝗠𝗟 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀, 𝗱𝗮𝘁𝗮 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴, 𝗰𝗹𝗼𝘂𝗱, 𝗗𝗲𝘃𝗢𝗽𝘀, 𝗮𝗻𝗱 𝗺𝗼𝗯𝗶𝗹𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁. 💡 We’re glad to be featured on RightFirms and appreciate their contribution to making the 𝗕𝟮𝗕 𝘁𝗲𝗰𝗵 𝗺𝗮𝗿𝗸𝗲𝘁𝗽𝗹𝗮𝗰𝗲 𝗺𝗼𝗿𝗲 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝘁 𝗮𝗻𝗱 𝗮𝗰𝗰𝗲𝘀𝘀𝗶𝗯𝗹𝗲 for companies searching for reliable development partners. 🤝 You can explore our RightFirms profile here: https://lnkd.in/dAJMcBAj #Timspark #RightFirms #SoftwareDevelopment #AI #MachineLearning #DataEngineering #CloudComputing #DevOps #MobileDevelopment #TechPartner #DigitalTransformation #B2BTech

Another talk from Tech Show Frankfurt that I kept thinking about was Bertie Müller ’s session on “Skills for Future Careers — The Impact of AI on Recruitment”. The topic sounded like recruitment at first, but the discussion was actually much broader: job market, education, lifelong learning, trust in AI, and the skills people will need when more and more execution can be automated. One phrase from the talk was strong enough that I sent it to our Timspark team right after the talk: “AI won’t replace people. But people who use AI will replace people who don’t.” I like this phrase because it sounds simple, but it leads to a much deeper question. AI will not just take some jobs away. It will change the structure of work. The repetitive parts of many roles will become easier to automate. But what remains for people may become more complex, not less. Evaluation, responsibility, critical thinking, checking AI-generated decisions, working with uncertainty, ethics, trust, and human communication will become much more important. And this is probably the part that many people underestimate. Using AI is not the same as understanding what it produced. The education part was especially interesting. If students can use AI to summarize articles, write assignments, and generate polished answers, then simply checking the final output becomes much weaker. The real question is whether the person understands the topic, can critically evaluate the answer, notice mistakes or hallucinations, verify the sources, and explain the reasoning behind the result. In a world where answers are easier to generate, understanding becomes more valuable than output. Recruiting is another area where this shift is already visible. Candidates can generate CVs, cover letters, and applications at scale. Companies can use AI to screen those applications at scale. So we may end up with more volume, more filtering, more polished documents, and more noise on both sides. That means hiring will probably need to move further away from surface-level output and closer to actual capability, judgment, potential, and fit. There was also a very interesting question about the junior-to-senior path. If AI takes over more junior-level execution tasks, how do people build the experience needed to become senior? Senior judgment does not appear from nowhere. It is built through repetition, mistakes, feedback, and real context. For me, the talk was a good reminder that AI is not only changing the tools we use. It is also changing what we should teach, how we should hire, and what we should value in professionals. So maybe the real question is: If polished output becomes easy to produce, how do we evaluate real competence?

After two days at Tech Show Frankfurt 🇩🇪, we’re leaving Frankfurt with a question in mind: 𝗪𝗵𝗮𝘁 𝗸𝗶𝗻𝗱 𝗼𝗳 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 — 𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝗸𝗶𝗻𝗱 𝗼𝗳 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝘁𝗲𝗮𝗺𝘀 — 𝘄𝗶𝗹𝗹 𝗺𝗮𝘁𝘁𝗲𝗿 𝗺𝗼𝘀𝘁 𝗶𝗻 𝗮𝗻 𝗔𝗜-𝗳𝗶𝗿𝘀𝘁 𝗺𝗮𝗿𝗸𝗲𝘁? What stood out in Frankfurt was not a simple “AI will take over” narrative. It was something more practical. On 𝗗𝗮𝘆 𝟭, one of the clearest messages was that 𝗔𝗜 𝘀𝗵𝗼𝘂𝗹𝗱 𝗻𝗼𝘁 𝗯𝗲 𝘃𝗶𝗲𝘄𝗲𝗱 𝗼𝗻𝗹𝘆 𝗮𝘀 𝗮 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝘁𝗼𝗼𝗹. That lens is too narrow. The bigger shift is about 𝗵𝗼𝘄 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀𝗲𝘀 𝗰𝗿𝗲𝗮𝘁𝗲 𝘃𝗮𝗹𝘂𝗲. On 𝗗𝗮𝘆 𝟮, the discussion became even more grounded: 🔐 the human factor is still the weakest point in security 🤝 trust, culture, and leadership behavior still decide whether adoption succeeds 🗣️ communication is not decoration — it is part of execution ⚙️ and in many organizations, the hardest gap is still the one between strategy and rollout That is why the “AI vs developers” debate feels incomplete. Yes, AI is accelerating parts of software delivery. Yes, routine coding tasks will keep changing. Yes, expectations for speed will rise. But faster code is not the same as better systems. Someone still has to: 𝗱𝗲𝘀𝗶𝗴𝗻 𝘁𝗵𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲 𝘁𝗼𝗼𝗹𝘀 𝗶𝗻𝘁𝗼 𝗿𝗲𝗮𝗹 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝗼𝘂𝘁𝗽𝘂𝘁𝘀 𝘀𝗲𝗰𝘂𝗿𝗲 𝗱𝗮𝘁𝗮 𝗮𝗻𝗱 𝗮𝗰𝗰𝗲𝘀𝘀 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 𝗰𝗼𝘀𝘁 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝘁𝗼 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀 And that is where the real shift is happening. As Vlad Nemshon, CEO at Timspark, put it: “AI will not replace strong developers. It will amplify the gap between teams that only produce code and teams that know how to build systems, products, and business value.” 🚀 A lot of companies are not struggling with the willingness to adopt AI. They are struggling with business architecture, operational readiness, and organizational alignment. In other words, technology is often the easier part. The harder part is making AI survive contact with reality. So no, we do not think AI simply replaces developers. We think it raises the bar. That feels like the real takeaway from Frankfurt. 𝗔𝗜 𝗶𝘀 𝗻𝗼𝘁 𝗿𝗲𝗺𝗼𝘃𝗶𝗻𝗴 𝘁𝗵𝗲 𝗻𝗲𝗲𝗱 𝗳𝗼𝗿 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀. 𝗜𝘁 𝗶𝘀 𝗿𝗲𝗱𝗲𝗳𝗶𝗻𝗶𝗻𝗴 𝘄𝗵𝗮𝘁 𝗴𝗿𝗲𝗮𝘁 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗹𝗼𝗼𝗸𝘀 𝗹𝗶𝗸𝗲. #AI #TechShowFrankfurt #Engineering #DigitalTransformation #Timspark

Looking for an AI-first Engineer who already uses agentic automation as part of daily work - not just AI for basic code generation. You’re probably building automated workflows, AI-assisted pipelines, autonomous agents, integrations, and internal productivity systems that help reduce manual work and move faster. You like experimenting, adapting quickly, and trying new approaches instead of doing everything the old way. You do not see AI as just a chatbot for vibe coding. Main stack: Next.js / NestJS. If this sounds like your kind of environment - DM me. #agenticautomation #nextjs #nestjs #timspark #ai #aifirst