Maven AGI’s Post

Pleased to present IVP’s second annual Enterprise AI 55 💡. With so much innovation underway in AI over the past year, we’ve decided to feature a fresh set of companies this year — application layer startups that have introduced compelling new GenAI products with Enterprise traction or those that have successfully kickstarted an Enterprise GTM motion in the past year. Though some of it is experimental, Enterprise budgets for generative AI have undoubtedly grown since we published our first edition last summer, and billions of dollars of budget creation and reallocation are up for the taking for startups. Many advances in the AI infrastructure layer have also propelled generative AI adoption – fine-tuning, inference, hosting, model evals, data governance, security, and other important features are now more broadly available for Enterprises to use to deploy GenAI adoption. The Enterprise AI 55: 2024 Edition is a collection of best-in-class AI products, sourced by operators for operators. We built this list incorporating feedback from hundreds of meetings with founders, management teams, Board meetings, and collaboration with out Fortune 500 network. We hope this is useful reference for operators at Enterprise companies looking to successfully use generative AI for real results. If you are building in this next generation of AI for the Enterprise, please reach out. Look through the full list here: https://lnkd.in/eCzWp6as Chief Revenue Officer: 11x, Attio, AutogenAI, Clay, Docket, Instantly, Nooks, Poggio, Regal, Regie AI, Rohirrim AI, Unify Chief Marketing Officer: Captions, Creatify, HeyGen, Kittl, Krea, Riverside.fm, Tofu Chief Financial Officer: Brex, DataSnipper, Levelpath, Numeric, Omnea, Orb, Payflows, Ramp Chief Customer Officer: Decagon, MavenAGI, Neuron7, Parloa, Sierra Chief People / L&D Officer: Ashby, Teambridge, Simpplr Chief Information Officer (Cross-Functional): Ema, Gamma, Julius AI, Kognitos, Mimica, Orby AI, Perplexity, Polycam, Seek AI, Sema4.ai, Sundial, Superhuman Chief Legal / Compliance Officer: Altana, Doppel, Eve, Greenlite, Leya, MarqVision, Modulate, Norm AI 

AI adoption in the enterprise continues to gain steam. My colleagues Karthik Ramakrishnan and Cynthia Kuo wrapped up the most promising enterprise AI companies we’ve been hearing about in our conversations with C-Suite decision-makers. Check it out: https://lnkd.in/eJAChbKE

Why Large Enterprises Need to Rethink Their AI Strategy 🚀 In 2024, speed, scalability, and seamless integration have become critical for enterprises adopting AI at scale but with a crowded market of AI platforms and hardware, the question isn’t whether to adopt AI—but how fast and efficiently can your enterprise deploy it? Here’s the reality: ▪️ 79% of enterprises report that time-to-value is their number 1 obstacle when adopting AI. Imagine cutting this time dramatically compared to traditional models. Faster deployment means faster results and a quicker competitive edge not to mention a faster return on your investment. ▪️ AI platforms that seem cost-effective upfront often carry hidden scaling costs. A solution that’s 30% more cost-efficient over a 3-year span completely changes the discussion for sustained ROI. ▪️ Legacy AI solutions often crumble when scaled. For enterprises running complex models, SambaNova Systems's ecosystem offers 4x faster inference speed compared to its nearest competitor, a game-changer. ▪️ Did you know 75% of enterprises consider data privacy and security as a barrier to full AI adoption? With a solution architected from the ground up with security-first principles, you can focus more on innovation and less on risk. In a rapidly evolving landscape, choosing the right enterprise AI platform isn't just a tech decision—it's a business strategy. The ability to deploy, scale, and operate with unmatched speed, security, and efficiency makes all the difference between leading and lagging behind. What’s your enterprise’s AI strategy in 2024?

🚀 Navigating the AI Revolution in Small Business In the realm of burgeoning technology, AI continues to spearhead innovations that could transform mundane tasks into automated processes, enhancing productivity across the board. For startups and small businesses, staying updated with such advancements isn't just beneficial; it's imperative for scaling efficiently amidst ever-growing competition. 🌐 Key Insights from Orby AI's Latest Development: - 🤖 AI agents developed by Orby are designed to autonomously execute tasks like data entry and form validations, capturing the subtle nuances of everyday business operations. - 🌟 Leveraging both generative AI and symbolic AI, these tools are engineered to adapt to new workflows dynamically—ensuring high-level accuracy even as your business evolves. 💡 How Can Startups Utilize Such Technologies? - 💼 Integrate AI to manage repetitive tasks, allowing your team to focus on more strategic initiatives. - 📈 Harness AI's data-processing capabilities to gain deeper insights into customer behaviors and market trends. Orby AI and similar technologies are not just tools; they represent a strategic pivot to more resilient, agile, and intelligent business operations. As we witness an increasing number of enterprises harnessing AI to maintain a competitive edge, the question for startups and small businesses is not if, but how quickly they can adapt to these changes. 🔗 For more information on how AI agents are shaping enterprise solutions: https://lnkd.in/gbhibuuE #Technology #AI #Startups This post was generated by an AI. Please contact us for more information.

Very good article summarizing the enterprise adoption of Gen AI. Key insights from the article. One interesting observation is the adaptation of open-source models by enterprises, which makes sense because they offer control, customization, and privacy. ·     Enterprise are tripling their budgets for generative AI, signaling a massive opportunity for startups · Open-source models are gaining popularity, with 46% of survey respondents expressing a preference for open-source models in 2024. ·     Enterprises are increasingly using multiple models to tailor to specific use cases thereby avoiding a lock-in. ·     Control and customization are the primary reasons for adopting open-source models, with cost being a lower priority. ·     While enterprises are currently focused on building AI applications in-house, the emergence of innovative apps beyond the "LLM + UI" formula could reshape the market. ·     Enterprises remain cautious about external use cases of generative AI, particularly due to concerns around safety and potential PR issues. ·     The total spend on model APIs and fine-tuning is expected to exceed $5 billion by the end of 2024, driven by increased enterprise adoption and investment. ·     RAG and Fine tuning are two popular methods used by enterprises to customize the models. https://lnkd.in/gAiSfzzG

Are you looking for some light reading over the holidays?  Check out our State of Gen AI in the Enterprise report, which cuts through the hype to see what's really happening in enterprise AI, with insights from Naomi Pilosof Ionita and Derek Xiao.  REPORT:  https://lnkd.in/gj_4JVTt Here are a few key takeaways:    In 2023, enterprise spending on AI was surprisingly low. Buyers will not move from "experimentation" to "adoption" until they see real ROI. For now, the market will continue to favor incumbents who integrate AI into existing products. Incumbents are moving faster than ever before and have an advantage over newer entrants because established leaders have brand/trust, distribution, and data advantages.  Three areas where we see the most promising opportunities for AI startups:   Horizontal AI: next-gen workflow automation/agents Vertical AI: industry-specific software Modern AI stack: new infrastructure for AI

Great report from Menlo Ventures - interesting insights into current state of Gen-AI. "Retrieval-augmented generation (RAG) is becoming a standard. RAG is an AI framework that augments LLMs with relevant and current information retrieved from external knowledge bases to improve the quality of responses. This dynamic augmentation allows LLMs to overcome the limitations of fixed datasets to generate responses that are up-to-date and contextually relevant. Thirty-one percent of AI adopters we surveyed are using this approach, more than those fine-tuning (19%), implementing adapters (18%), or leveraging RLHF (13%)" https://lnkd.in/dYMBVf5P

Must read write-up on investments in AI and the market's understanding...

🚀 Exploring the Strategic Role of CIOs in the Generative AI Revolution 🚀 As we stand on the cusp of a technological renaissance driven by generative AI, the pivotal role of Chief Information Officers (CIOs) cannot be overstated. AI's transformative potential holds immense power and responsibility. 🔍 Balancing Act: Innovation vs. Governance The opportunities with generative AI are groundbreaking, promising to elevate everything from code quality to operational efficiency. However, the rapid adoption of these tools raises significant challenges in managing technical debt and maintaining robust governance. The choices we make now will set the course for the future of technology. 🛠️ Prioritizing Quality and Security Stephen O’Grady from Red Monk points out the real risks associated with increased technical debt. This makes it imperative for CIOs to carefully select and manage AI tools to ensure they are deployed effectively and responsibly. 🚀 AI: The New Catalyst for Operational Excellence Imagine a workplace where every team member has an AI copilot, amplifying productivity and innovation. Leaders like Juan Perez of Salesforce and Neal Sample of Walgreens are making this a reality, showcasing AI's transformative impact across departments. 💡 Enhancing Team Empowerment and Customer Experiences AI isn’t just about automation—it’s about revolutionizing how we work and interact with customers, significantly boosting satisfaction across the board. But successful implementation is just the start. Ensuring the integrity of AI outputs and maintaining ethical standards are crucial. 🔗 Calling All CIOs! Navigating the AI integration journey is complex but filled with opportunities for significant enhancements in our technological and operational frameworks. How are you incorporating generative AI into your strategy? 👇 Share your thoughts and discuss AI’s future in business. For more in-depth insights, check out the full article on how CIOs are navigating generative AI in the enterprise. https://lnkd.in/gJrQe6Th #AI #technology #leadership #innovation #genai

Profet AI Launches AILM, the World's First Enterprise AI Lifecycle Management Platform for AI Governance Taiwan-based Profet AI has launched AILM (AI Lifecycle Management Platform), the world's first enterprise platform for AI governance. Targeting the manufacturing industry, AILM enables companies to control, manage, and disseminate their core domain know-how, facilitating global expansion. The platform addresses common challenges in AI adoption, providing standardized problem identification, transparent implementation processes, and incentivized reward systems. Profet AI plans to integrate AILM with Generative AI to enhance usage efficiency. The company recently completed a Series A funding round, raising $5.6 million, and expanded its presence to Vietnam, Japan, Malaysia, Singapore, Thailand, and China. #ProfetAI #AILM #EnterpriseAI #AIgovernance #AI LifecycleManagement #ManufacturingIndustry #GlobalExpansion #StandardizedProcesses #IncentivizedRewards #GenerativeAI #SeriesAfunding #ExpansionInAsia #TechInnovation #AIAdoption #AIInBusiness #EnterpriseTech