The Tesoro AI Podcast

In this episode of the Tesoro AI podcast, we speak with Hunter Brooks, co-founder and CEO of Ellipsis. We discuss Hunter's journey from a self-taught developer with a background in astrophysics to creating an AI-driven code review tool. Hunter elaborates on his professional experiences at companies like Capital One and Amazon, where he gained exposure to machine learning and AI. We delve into the capabilities of Ellipsis, how it revolutionizes the code review process by leveraging state-of-the-art large language models (LLMs) to ensure code quality and efficiency. Hunter shares insights into the transition from traditional coding methods to AI-assisted development, emphasizing the importance of integrating AI to improve productivity without replacing human oversight. The discussion also covers the challenges and advantages of launching an AI startup, including valuable advice from their experience with Y Combinator and the role of VC funding in the crowded AI DevTools space. The episode provides a comprehensive look at how AI can optimize software development, the future of coding, and practical steps for teams and individuals to adopt these advanced tools.   If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.   Founder Bio:   Hunter Brooks is a versatile professional who transitioned from astrophysics to software engineering. Before co-founding Ellipsis, he gained experience at Amazon Web Services (AWS), where he honed his technical expertise. He also contributed to the field of cosmology through research and publications.   Time Stamps:   00:33 Hunter's Background and Career Journey 04:03 Early Challenges with AI and Code Generation 05:26 The State of AI in Code Writing 09:06 Introduction to Ellipsis 12:01 How Ellipsis Enhances Code Review 15:46 Team Code Review Process 19:34 Personalization and Efficiency in Code Review 24:04 Starting an AI Platform as a Startup 26:12 What Ellipsis Does to Go Beyond Basic Code Review 28:19 Empowering Developers with Advanced Tools 29:52 Getting Started with Ellipsis 31:30 Addressing Security Concerns 34:12 Building a Technical Team 38:38 Fundraising in the AI Space 43:07 Future Developments and Features   Resources   Company website: https://www.ellipsis.dev/ LinkedIn: https://www.linkedin.com/company/ellipsis-dev/ Twitter: https://twitter.com/ellipsis_dev  

In this episode of the Tesoro AI podcast, host Darius Gant converses with Steven Atneosen , a seasoned serial entrepreneur and executive with a diverse background in law, corporate strategy, and technology. Steven shares his career trajectory from a fascination with automobiles to the legal profession, and eventually into the world of AI and tech startups. He recounts his roles in various companies, including carparts.com, aristocrat, Axiom, and finally Tomta. The discussion delves into the importance of data privacy in AI development, the challenges of using sensitive data, and Tomta's innovative solutions for creating hyper-accurate yet anonymized datasets. This conversation sheds light on the critical intersection of technology, data privacy, and the future of AI, emphasizing the need for robust and ethical data management practices.   If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.     Founder Bio:   Steven Atneosen has a Bachelor of Science (BS) degree in Accounting and Finance from Drake University. Additionally, they hold a Doctor of Law (JD) degree from Mitchell Hamline School of Law, with a focus on Entrepreneurship/Entrepreneurial Studies, Business, Litigation, and Appellate. Steven is also certified as an Attorney by the Minnesota State Bar Association. Steven has a diverse work experience spanning over a decade. Steven is currently the CEO and Co-founder of tomtA, where they focus on creating ML solutions for organizational missions by allowing the safe sharing and use of anonymized real data. Before tomtA, Steven founded Grand Chasm Ventures in 2018 and served as the Managing Director. Steven also worked as an Advisor for ElectricFish and NIO, where they held the role of Advisor to XPT before becoming the Vice President of Corporate Development for the same division. At NIO, they played a key role in attracting funding, building product roadmaps, and securing acquisitions for electric, connected, and autonomous vehicles. Steven has also been an Investor and Advisor for Deepen AI, an Advisor and interim COO for Wireline.io, and the SVP of Corporate Development, General Counsel, and Chief Privacy Officer for StayWell Health Management. Furthermore, they co-founded and served as the CEO of DebateHall.com and worked as the Vice President of Operations for RxVantage. Steven was responsible for developing growth strategies and improving product adoption in these roles.   Time Stamps:   00:36 Steven Background From Law to Entrepreneurship 05:08 Transition to Business Development 09:36 Venturing into Healthcare and Ad Tech 13:14 Founding a Venture Capital Firm 16:12 Challenges in AI 19:27 The importance of Data and Privacy 23:02 What problem is Tomta solving 25:32 Understanding Attribute Risk 29:20 Who is more concerned about Data and privacy 33:02 Engaging with Tomta AI 37:20 Future of Data Privacy and AI 45:54 Synthetic Equivalent Data and Its Benefits   Resources   Company website: https://tomta.ai/ LinkedIn: https://www.linkedin.com/company/tomta-ai/ Twitter: https://twitter.com/tomtA_ai  

In this episode, we sit with Marcus Lampinen, the founder of Prifina. Marcus discusses how AI is revolutionizing the way individuals can manage and control their personal and professional data. We then delve into Marcus's background and how his passion for data led to the creation of Prifina, a user-controlled data company aimed at ensuring AI serves individuals' interests. The conversation covers the practical applications of AI in various fields such as athletics, education, and content creation, highlighting how easy-to-use consumer-grade tools provided by Prifina allow users to create their own AI twin. Marcus explains the technicalities behind training these AI models and assures that data control remains with the user, leading to more engaging and personalized interactions. They also explore innovative business models and future possibilities where AI can significantly augment human expertise and save time on mundane tasks.   If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.   Founder Bio:   Markus Lampinen is a serial entrepreneur and early stage investor. Markus is specialized on data and applied AI, currently the CEO of Prifina focused on empowering the consumer market with AI that both represents them publicly and helps them privately. He is also involved in several innovative startups in fintech, data, machine learning and transparent AI.   Time Stamps:   00:36 Marcus Background and Personal Insights 03:55 The Concept of Prifina 08:04 User Engagement with Prifina 13:16 AI in Education and Beyond 17:19 Challenges and Customization in AI Responses 25:04 Simplifying AI for Consumers 25:37 Building and Launching AI Products 28:56 Consumer-Grade AI Platforms 30:14 Horizontal AI Applications 33:02 Contrast between Prifina approach vs. Fine-tuning an LLm 37:14 Business Model and Pricing 40:41 Future of AI Representatives 46:30 Final Thoughts and Upcoming Features   Resources   Company website: https://www.prifina.com/ LinkedIn: https://www.linkedin.com/company/prifina/ Twitter (X): https://twitter.com/myprifina Facebook: https://www.facebook.com/myprifina Markus AI Twin chat: https://hey.speak-to.ai/markus  

In this episode, we speak with Maria Telleria co-founder and CTO of Canvas. Maria shares her journey from a mechanical engineering background in Mexico to leading innovations in AI and robotics for the construction industry. Starting from her research at MIT to building robots designed for unstructured environments, Maria discusses the challenges and breakthroughs in integrating AI with hardware. She emphasizes the critical role of sensors, AI models, and safety checks in developing effective robotic solutions. Maria also elaborates on how Canvas' technology is improving productivity and safety in construction, outlining the business benefits and future prospects for robots in commercial settings. The conversation covers the practical applications, adoption strategies, and the new hardware platform Canvas is launching to further augment construction workflows.   If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.  Founder Bio:   Maria Telleria is co-founder and CTO of venture-backed Canvas. Her company is building and deploying robotic systems to assist workers in arduous and dangerous construction tasks. The Canvas System is now being deployed in the Bay Area. Before Canvas, Maria was a company lead at Otherlab, an independent research laboratory focused on developing hard tech ideas from research to product. At Otherlab, she oversaw three large-scale government grants and two commercial development programs aimed at developing a new class of compliant robotic systems for unstructured environments. She secured multi-million-dollar grants from agencies like NASA, DARPA, and the Office of Naval Research. She is author on sixteen patents and fifteen patent applications related to Canvas systems and is a co-inventor on an additional three patents related to pneumatic robots. Prior to joining Otherlab, Ms. Telleria worked at MIT Lincoln Laboratory on the design of next-generation data systems. Maria holds a Ph.D. in Mechanical Engineering from MIT. Her dissertation established the field of cylindrical compliant mechanisms. While at MIT she co-founded the MIT Grad Catalyst Program with the mission to give minority students the tools and information required to pursue advanced degrees in science and technology.   Time Stamps:   00:31 Maria’s introduction and background 03:50 Challenges in Robotics 05:46 Canvas and real-world applications 07:58 AI and robotics in construction 14:22 Infusing AI into hardware 16:52 Simulation and data challenges 23:05 Use cases for the future of robotics 27:09 Core components of AI-enabled hardware 30:40 Human-AI Collaboration 32:21 Real-world applications and challenges 38:07 Market launch and business strategy 43:10 Adoption and future prospects 46:37 Future directions and how to get in contact with the Canvas team   Resources   Company website: https://www.canvas.build/ LinkedIn: https://www.linkedin.com/company/we-are-canvas/ Twitter: https://x.com/canvas_build  Instagram: https://www.instagram.com/we_are_canvas/  

AI governance and risk management are crucial frameworks designed to ensure the responsible development, deployment, and oversight of artificial intelligence technologies. As AI becomes increasingly integral to various sectors, effective governance ensures that these systems operate ethically, transparently, and in compliance with relevant regulations. It addresses key issues such as bias, fairness, accountability, and privacy, ensuring that AI systems benefit society while minimizing potential harms. Risk management in AI involves identifying, assessing, and mitigating risks associated with AI technologies, from algorithmic bias to security vulnerabilities, to safeguard against negative impacts and promote trust in AI applications.   In this episode, we sit with Guru Sethupaty Co-founder and CEO of Fairnow. Guru talk about his extensive background in AI, detailing his journey from an AI enthusiast inspired by IBM's Deep Blue to his academic pursuits at Stanford and professional contributions at Capital One. The conversation delve into the critical aspects of AI governance and risk management, emphasizing the challenges enterprises face in integrating and scaling AI technologies while ensuring compliance and trustworthiness. Guru introduces Fairnow, which provides a platform to help organizations automate AI governance, manage risks, and comply with evolving regulations. Specific case studies, such as the Air Canada chatbot mishap, highlight the necessity for rigorous AI governance. Furthermore, they discuss the market dynamics, talent acquisition challenges in the AI sector, and the future landscape of AI governance.   If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.     Founder Bio:   Guru Sethupathy has dedicated nearly two decades to understanding the impact of powerful technologies, such as AI, on business value, risks, and the workforce. He has written research papers on bias in algorithmic systems and the implications of AI technology on jobs. At McKinsey, he advised Fortune 100 leaders on harnessing the power of analytics and AI, while managing risks. As a senior executive at Capital One, he built the People Analytics, Technology, and Strategy function, leading both AI innovations as well as AI risk management in HR. Most recently, Guru founded a new venture, FairNow. FairNow’s AI governance software reflects Guru’s commitment to helping organizations maximize the potential of AI while managing risks through good governance. When he’s not thinking about AI governance, you can find him on the tennis court, just narrowly escaping defeat at the hands of his two daughters. Guru has a BS in Computer Science from Stanford and a PhD in Economics from Columbia.     Time Stamps:   01:59 Guru’s background and journey into AI 06:17 Implications of AI in the enterprise world 09:24 Challenges in AI adoption 11:03 Founding of Fair Now 13:18 Fair Now's governance platform 15:09 Governance and compliance examples 19:18 Modules and customer engagement 21:49 AI integration: understanding compliance and regulations 24:46 Building the engineering and data science team 27:54 Navigating talent acquisition challenges 31:00 Strategies for enterprise sales 34:09 The future of AI governance 38:26 Future directions and how to get in contact with the Fair Now AI team   Resources   Company website: https://fairnow.ai/ LinkedIn: https://www.linkedin.com/company/fairnowai/ Twitter: https://x.com/FairNow_AI  

When getting into AI application development, it's important not to overlook the evaluation process. Many companies concentrate on building and training AI models, but struggle with systematically assessing the performance of these models. This emphasizes the necessity of using robust evaluation tools to accurately gauge the effectiveness of AI systems, stressing the importance of quantitatively measuring AI performance to identify strengths and weaknesses.   Today, we sit with Yi Zhang, co-founder of Relari AI, to learn about their journey from a mix of finance and technology backgrounds into the field of artificial intelligence. We discussed Yi Zhang's early career in computer science, a role in investment banking, and then a transition to AI with a significant position at Pony AI. Our conversation focused on the evolution of the AI industry, specifically the transformative impact of LLMs (Large Language Models) like ChatGPT. We also examined Relari AI's mission to tackle the challenges of operationalizing AI applications, emphasizing their unique approach using synthetic data for rigorous evaluation. Additionally, we covered the importance of cross-industry AI applications, the critical need for reliability in AI outputs, and the company's ongoing recruitment efforts to grow their innovative team. If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.   Founder Bio:   Yi is the co-founder & CEO of Relari AI. Relari is the testing and simulation platform for Generative AI systems. AI teams use Relari to generate large scale synthetic data to systematically test and improve their LLM-powered applications. Relari is backed by top investors like Y Combinator, Soma Capital and General Catalyst. Prior to founding Relari, Yi was a product leader at two AI unicorns, Pony.ai - an autonomous vehicle startup and Dexterity.ai - an AI robotics startup. Yi holds a Bachelor's Degree in Computer Science from Northwestern University and an MBA from Harvard Business School.   Time Stamps:   01:40 Yi’s background and journey into AI 05:41 Founding Relari: The genesis and vision 07:46 Challenges in moving LLMs from demos to production 11:57 Relari's approach to AI evaluation and synthetic data 19:19 Synthetic data and its importance 21:36 Using synthetic data to improve AI chatbot accuracy 26:38 Optimizing AI systems through evaluation and improvement strategies 32:08 The evolution of AI adoption in enterprises 35:33 Building the Relari team 40:17 Closing remarks and how to get in contact with the Relari team Resources Company website: https://www.relari.ai/ LinkedIn: https://www.linkedin.com/company/relari/ Twitter: https://x.com/RelariAI  

Understanding the regulatory landscape in AI governance is essential for organizations to comply with emerging regulations, such as the EU AI Act. Responsible AI goes beyond principles to accountability, requiring organizations to demonstrate ethical practices in their AI implementations. Model transparency ratings provide a valuable tool for evaluating large language models and assessing their risk factors based on public disclosure.   In this episode we sit with Gerald Kierce, co-founder and CEO of Trustible AI, a leading technology provider focused on responsible AI governance. Gerald provides insights into his background, including his experience at FiscalNote and his vision for Trustible AI. The discussion covers how Trustible AI helps organizations manage AI risks, comply with emerging regulations, and implement responsible AI practices. Gerald also shares his thoughts on the regulatory landscape, the role of third-party audits, and the challenges and strategies in building an AI governance platform. The conversation also touches upon Trustible AI's recent feature, the model transparency ratings, and the complexities of fundraising in the AI sector.   If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.  Founder Bio: Gerald Kierce is the Co-Founder & CEO of Trustible – a leading technology provider of responsible AI governance. Its software platform enables AI and compliance teams to scale their AI Governance programs to help build trust, manage risk, and comply with AI regulations. Prior to founding Trustible, Gerald was an executive at FiscalNote (NYSE: NOTE) where he spent nearly a decade at the company across a variety of roles including VP & General Manager of their AI Solutions division, Corporate Development, Chief of Staff, Product Marketing, and Customer Success. FiscalNote was the most recent DC-based company to go public in the New York Stock Exchange in August of 2022. He is originally from San Juan, Puerto Rico.   Time Stamps:   01:46 Gerald's background and journey into AI 03:58 Navigating AI without a technical background 07:45 Trustible AI pain point: AI Governance and Compliance 13:36 Managing AI risks and mitigation strategies 17:13 The shift from responsible AI to accountable AI 21:34 Navigating AI governance and regulatory compliance challenges 25:50 AI in practice: Real-world applications 28:25 Challenges and solutions in deploying generative AI models 30:04 Building an AI startup: From vision to product adoption 36:31 Understanding model transparency ratings for evaluating AI risks 41:14 Fundraising and market dynamics in AI 45:23 Future Directions and how to get in contact with the Trustible team   Resources   Company website: https://www.trustible.ai/ LinkedIn: https://www.linkedin.com/company/trustible/ Twitter: https://twitter.com/TrustibleAI  

In this episode, we sit with Omar Tabba, Chief Product Officer at Brainbox AI, to delve into the transformative use of artificial intelligence in building automation and energy efficiency. With over 20 years of experience, Omar shares his journey into the AI sector, real-world applications of AI in managing HVAC systems, and Brainbox AI's innovations like ARIA, the world's first virtual building assistant.   We discuss the operational and environmental benefits of AI in smart building management, including significant reductions in energy consumption and carbon emissions. The conversation highlights the importance of normalized data, the role of AI in predictive maintenance, and the cultural and technical synergies needed to drive AI innovations in the built environment.   If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development. Founder Bio: Omar Tabba leads the product management function at BrainBox AI. With more than 20 years of expertise in energy efficiency, artificial intelligence, and building automation, he has held various positions spanning technical, sales, and executive roles. Prior to joining BrainBox AI, he led the digital solutions team at the General Electric Current business unit, where he supported the sale of Current’s digital solutions to Fortune 200 companies as well as the product, marketing and business development functions. Earlier in his career, Omar co-founded a venture-backed lighting control company and spearheaded sales for Distech Controls (NYSE:AYI) across Eastern North America and the Middle East.   A patent holder, Omar has applied building automation and energy management systems globally across multiple vertical markets (e.g., retail, commercial office, education) and in portfolios ranging from single buildings to several thousand.   Time Stamps:   01:55 Omar's journey into AI and smart buildings 05:11 Pain point that Brainbox is solving: building automation systems 09:01 ROI benefit examples 11:37 The role of AI in building management 16:05 AI applications in building maintenance 20:40 Acquiring and integrating building data 22:17 Solving data retention issues 23:54 Introducing ARIA: The Virtual building assistant 26:28 Building a specialized technical team 30:00 Navigating the AI talent market 32:25 The importance of cultural fit for hiring the right team 36:05 Funding journey and investor insights 41:00 The future of AI in building management 43:10 Exciting Announcements for 2024   Resources   Company website: https://brainboxai.com/en/ Instagram: https://www.instagram.com/brainboxai/ LinkedIn: https://www.linkedin.com/company/brainboxai/ Facebook: https://www.facebook.com/BrainBoxAI Twitter: https://x.com/brainboxai  

In today’s episode, we sit with Patricia Thaine, the Co-founder and CEO of Private AI. Patricia shares her journey into the world of AI, the challenges companies face in adhering to data protection regulations like GDPR, and the vital role of privacy-enhancing technologies. She elaborates on how Private AI leverages artificial intelligence to help companies identify and safeguard personal information within their data, ensuring compliance and protecting customer privacy. Additionally, Patricia emphasizes the importance of data minimization and discusses the real-world applications of AI in addressing privacy and data protection challenges.   Private AI is addressing the pain point of data privacy by leveraging AI to help companies identify and protect personal information in unstructured data. Patricia explained that AI is crucial in understanding the context of the data and making accurate predictions about what constitutes personal information. While traditional methods like regular expressions can be used, they often fall short due to their inability to handle the complexity and variety of unstructured data.   If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.  Founder Bio:   Patricia Thaine is the Co-Founder & CEO of Private AI, a Microsoft-backed startup who raised their Series A led by the BDC in November 2022. Private AI was named a 2023 Technology Pioneer by the World Economic Forum and a Gartner Cool Vendor. She is also a Computer Science PhD Candidate at the University of Toronto (on leave) and a Vector Institute alumna. Her R&D work is focused on privacy-preserving natural language processing, with a focus on applied cryptography and re-identification risk. She also does research on computational methods for lost language decipherment. Patricia is a recipient of the NSERC Postgraduate Scholarship, the RBC Graduate Fellowship, the Beatrice “Trixie” Worsley Graduate Scholarship in Computer Science, and the Ontario Graduate Scholarship. She is the co-inventor of one U.S. patent and has ten years of research and software development experience, including at the McGill Language Development Lab, the University of Toronto’s Computational Linguistics Lab, the University of Toronto’s Department of Linguistics, and the Public Health Agency of Canada.   Time Stamps:   02:10 Patricia's background and journey into AI 03:54 Challenges and solutions in data privacy 06:15 Consequences of noncompliance in data protection 09:43 Enhancing data privacy in AI startups 11:34 Unraveling data privacy in AI for multinational compliance 15:11 Demystifying AI’s role in data analysis and application 17:10 AI, privacy, and internal risks in large language models 21:09 Building the private AI platform: Team and technology insights 23:35 Efficiency and expertise in building custom machine learning models 28:33 Catalysts and compliance in conversational AI adoption 30:35 Evaluating AI’s role over regular expressions in customer solutions 33:07 Investing millions for superior Data-Driven AI models 34:51 Fundraising journey for an AI startup 38:20 Private AI upcoming announcements and where to find them   Resources   Company website: https://private-ai.com/ Youtube: https://www.youtube.com/@privateai715 LinkedIn: https://www.linkedin.com/company/private-ai/ Patricia’s LinkedIn: https://www.linkedin.com/in/patricia-thaine/ Twitter: https://twitter.com/_PrivateAI

Artificial intelligence (AI) has come a long way since its early days of identifying cats in images. Today, AI is transforming the way we work and interact with technology, thanks to the development of AI agents. These agents, powered by advanced AI models, act as virtual colleagues, capable of automating tasks, providing insights, and orchestrating complex workflows   In this episode we speak with Alexander de RidderDirector, co-founder and CTO of Ink Co. The conversation explores Alexander's journey in the AI and machine learning space, starting from early innovations in computer vision to the development of Smith OS, an operating system for collaborative AI agents. Alexander shares insights into the transformative potential of AI in marketing, SEO, and business, highlighting his contributions through patenting semantic optimization technology and predicting Google rankings with impressive accuracy. The discussion also covers the impact of AI on consumer and enterprise levels, the advent of AI agents and multi-agent systems as future workforces, and the challenges and opportunities presented by AI integration into various sectors. Alexander emphasizes the importance of AI orchestration through tools like Smith OS and offers advice for individuals interested in AI, highlighting AI technology's democratizing potential. If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development. Founder Bio:   Alexander De Ridder is an entrepreneur, technologist, and visionary focused on leveraging AI to transform marketing and business. As Co-Founder and CTO of INK Content, Inc., he currently leads the development of Smyth OS, an operating system for collaborative AI agents.A recognized thought leader on the future of AI, Alexander paints a bold vision for how AI assistants will interact with specialized websites to deliver hyper-relevant, personalized experiences he calls "Web 3.0." He sees major changes on the horizon as AI transforms search, e-commerce, and human-computer interaction.With deep expertise in areas including AI, machine learning, marketing, and SEO, Alexander frequently shares his insights on where technology is heading and how businesses can prepare. He advises enterprises on transitioning to AI-driven strategies and workflows.    Time Stamps:   02:00 Alexander's journey: from machine learning to AI pioneering 05:26 The evolution of AI in search and content marketing 08:03 Revolutionizing content creation with AI 13:08 The future of AI agents and workforce automation 19:24 The exponential growth of AI through multi-agent systems 23:17 Consumer domination and workspace revolution 28:35 Exploring the capabilities of AI in automation 30:32 Showcasing SmythOS: practical applications and examples 35:22 Building your Own AI agent: Accessibility and Skill Levels 41:46 The Technical Backbone of SmythOS 47:30 SmythOS found raising journey: the future of work with AI agents 51:54 How to get in contact with the SmythOs team   Resources: Company website: https://smythos.com/ Facebook: https://www.facebook.com/people/SmythOS/61552328188105/ LinkedIn: https://www.linkedin.com/company/smythos/ Twitter: https://x.com/adridder