Latest news with #GoodShip
Geek Wire
6 days ago
- Business
- Geek Wire
Freight logistics startup GoodShip opening new Bellevue office after raising $25M
GeekWire's startup coverage documents the Pacific Northwest entrepreneurial scene. Sign up for our weekly startup newsletter , and check out the GeekWire funding tracker and venture capital directory . GoodShip co-founders Ryan Soskin (left) and David Tsai. (GoodShip Photo) GoodShip, a software startup that helps companies manage shipping logistics data, raised $25 million and announced plans for a new office in Bellevue, Wash. Founded in 2022, the company's software serves as a hub for finance, procurement, carrier management, analytics, and other data related to shipping goods across the country. GoodShip has a few dozen customers including Kellanova, Reser's Fine Foods, Mike's Hard Lemonade, Tropicana, and others. The startup grew its annual recurring revenue by tenfold in 2024. The company is fully remote, with CEO Ryan Soskin based in Nashville and CTO David Tsai in Seattle. Soskin and Tsai previously worked at Seattle trucking startup Convoy before launching GoodShip. The new office in downtown Bellevue is GoodShip's first physical location. The company employs 14 people in the Seattle region and nearly 40 people total. Greenfield Partners led the Series B round. Other backers include Bessemer Venture Partners, Ironspring Ventures, Chicago Ventures, and Bellevue-based venture firm FUSE. GoodShip is one of several logistics startups with a presence in the Seattle area, which has emerged as a major epicenter for supply chain software innovation. Funding to logistics startups hit record highs in 2021 as the pandemic disrupted supply chains but total investment and deal flow fell sharply through 2024.
Forbes
29-04-2025
- Business
- Forbes
Upskilling In AI: The Key To Survival And Success For Startups
AI skills are crucial to business survival and success The pace of AI innovation is relentless, with new tools and platforms continually emerging and delivering transformative benefits for business. For entrepreneurs and startup founders, this rapid evolution can feel overwhelming. But rather than seeing this as a barrier, upskilling in AI should be perceived as an opportunity to create a culture of continuous learning and maintain a competitive advantage - because the companies that fail to adapt will be left behind. Most firms are already investing heavily; a recent survey revealed that over 77% of firms are utilizing or exploring AI in their business, and 83% report that AI is a primary business imperative in their business strategies. In today's business world, it is not just a matter of staying competitive but of survival and success. There are countless AI tools on the market, ranging from content creation and design platforms to automation, analytics, and customer service, many of them free of charge. Regardless of industry sector, the key is not to try and use everything, but to identify the right tools for your toolbox, as Gavin Sherratt, founder of digital agency GoodShip, explains. He says: 'Each business has unique needs. The AI tools you invest in should be chosen based on how they can streamline your operations, unlock efficiency, and free up time for your people to focus on meaningful work. But this only happens when your team is given the space to explore, test, and learn.' Despite the abundance of tools, many businesses are still hesitant to get started. Tools like ChatGPT and Gemini are powerful, accessible, and free to use at a basic level, yet many employees haven't been shown how to use them effectively. Here, entrepreneurs, startup founders and management should be taking the lead. 'Investing even a small amount of time into training teams on foundational AI tools can unlock significant gains in productivity, creativity, and autonomy,' says Sherratt. 'A basic understanding of how to prompt ChatGPT effectively, or how to automate tasks using simple no-code tools, can change how a team works, forever.' One of the main reasons AI adoption may be slower than expected is resistance, often born out of a fear of the unknown, especially when the pace of change feels overwhelming. Creating trust in these tools is vital and that means demystifying AI, offering hands-on experience, and creating safe spaces where employees can explore tools, experiment, and make mistakes without consequences. Having built and grown technology-driven companies, Luca Dal Zotto, cofounder of Rent a Mac, believes that the most effective way of upskilling in AI is by blending proactive training and an ongoing learning culture. He says that providing employees access to online learning, workshops, and mentorship can empower teams with the required competencies, but adds that there are challenges, not least, resistance from employees who feel threatened by AI or intimidated by the learning curve. 'Breaking this resistance requires using a 'carrot' rather than a 'stick', says Dal Zotto. 'Incentivizing employees to learn AI by offering them promotions, bonuses, or reward systems promotes a good learning culture. For example, I introduced an initiative whereby employees who attained AI certifications received a good bonus and additional responsibility. This motivated them and fostered a culture where AI capability was rewarded and valued.' Then there is the issue of false confidence, where teams assume they're already using AI because they've experimented with ChatGPT or tried out a plugin. Many fail to appreciate the gap between playing with AI and solving real business problems with it in a repeatable way. Cahyo Subroto, founder of MrScraper, has overcome this challenge by avoiding abstract training, and instead, upskilling by showing each team exactly how AI fits into their specific workflow. 'We sit down with marketers, salespeople, analysts etc., and walk them through how a single, high-impact task AI can improve right away,' he says. 'The key is giving people a real outcome to own and not a new tool to memorize.' At software development firm Zibtek founder, Cache Merrill has pushed his teams to explore bite-sized, project-based learning. He says: 'We throw together 'AI sprints' on real issues, from routing support tickets automatically to optimizing sales outreach. These small projects serve as hands-on workshops that force people to learn by doing, not by watching a tutorial.' But it isn't always plain sailing. The biggest hurdle is mindset inertia, where seasoned developers worry AI will render their expertise obsolete, and business folk get overwhelmed by buzzwords. 'We've countered this by spotlighting early adopters,' says Merrill. 'Our QA built a simple defect predictor in a week that became our in‑house AI champion. The 'carrot'- recognition, peer kudos, a small bonus, even a social‑media shout‑out - goes further than any edict from above.' The 'stick' is reserved until necessary, for example, if a team member continues to miss AI‑based deliverables, the approach is to train first, then marry foundational AI skills to performance objectives. 'In my experience, a supportive learning culture, coupled with transparent milestones and public acknowledgement of small wins engenders far more momentum than any penalty threat,' says Merrill. Samantha Evans, founder of Humphreys of Henley, has a team of four, who recognize that embracing AI in certain areas of the work is fundamental to their success and the future success of the business. 'Each team member is committed to spending a certain amount of time each week exploring uses of AI so we can optimize the best options for the business,' she explains. 'We are all learning together. Some have a greater aptitude than others, but it is already saving us huge amounts of time by applying it to repetitive tasks. They all know AI will not take over their jobs or the business. They also know that if we don't embrace effective and managed use of AI, there is a good chance that we will lose out to those businesses that have done so.' Ultimately, the businesses that thrive in the AI era will be those that foster curiosity, allow space for learning, and encourage experimentation. They will also be the ones that build resilience, by protecting their information, upskilling in AI and creating adaptable, data-conscious ways of working.
