Ali Hamriti’s Post

FINNY uses artificial intelligence to help financial advisors grow their businesses more efficiently. The company focuses on solving the problem of finding new clients, which is usually a long and inefficient process for financial advisors. Normally, advisors spend a lot of time searching for potential clients, sorting through lists from various platforms like LinkedIn or ZoomInfo, and setting up meetings. This process often results in low success rates and many wasted hours. Finny AI's tool automates much of this work. It helps advisors find and prioritize potential clients who are more likely to be interested in their services by using AI to analyze thousands of data points for each lead. It then automates the outreach process, including scheduling meetings with the most promising prospects. This allows financial advisors to focus more on building relationships with potential clients, rather than spending their time on repetitive tasks. Finny AI has already launched its product with several firms and has seen rapid growth and interest, showing that its approach is making a real difference in the financial advisory industry. Founders - Eden Ovadia, Theodore Janson & Victoria Toli Check out Finny AI - https://www.finnyai.com/ P.S - if you need any written content for your early-stage startup... Send me a DM or schedule a call here - https://lnkd.in/d5VeNGkm Ciao👋🏾

In the last month, we've all heard this Service-as-a-Software narrative that AI will enable applications to sell an outcome or a full task, rather than a seat as in vertical SaaS. This could then increase annual contract values from 3 or 4-figures to 6 or 7-figures. After all, that is the cost of labor previously delivering the service, right? Service-as-a-Software expands the $650B Software Market into the $10T Services markets. We've heard this seductive VC narrative from Mamoon Hamid at Kleiner Perkins; Sarah Tavel at Benchmark and Pat Grady at Sequoia Capital. Smart investors, no doubt. But what if this thinking ignores the competitive element? Since when is pricing a function of the work you replace, rather than the next application who is seeking to replace you? I suspect customers will see massive savings in cost / task, but competition will render value capture difficult for these first movers. With dozens of AI SDRs, AI Coding Agents, and AI Work Assistants and discerning IT procurement departments, how will these price assumptions sustain? The answer, I think, lies in dusting off Hamilton Helmer's 7 Powers, specifically 3 of them: 1) Network Effects (on users or data) 2) High Switching Costs (system of record) 3) Counter-Positioning (inimitable pricing or delivery mechanism) This is what we are looking for at Optimist Ventures. Would love others' thoughts on this.

Thanks to Scaleup Finance for a very insightful webinar yesterday on “How to raise funding in an AI era”. It was really interesting to hear viewpoints from both founders and investors on how AI is changing the conversation for VCs and start ups.    Three key takeaways for me:   1. Your company doesn’t necessarily need to be using AI to be interesting to investors – there are some sectors and companies that don’t have a burning requirement for it right now. But leaders of all companies need to be prepared to answer the question around where and how they’re using AI – and critically, where they’re not.   2. Using third-party tech solutions, and the AI that’s embedded in them, doesn’t make you an “AI-enabled company”. There are lots of lofty claims in this space that quickly unravel when subject to scrutiny – building your own solutions is more impressive to investors. For instance, if you’re claiming to be an AI business but you don’t employ any data scientists or ML engineers, you’ll come unstuck pretty rapidly.   3. In some cases, investors are using AI within a deal process – mainly to speed up laborious tasks such as reviewing company information or pitch decks – but there is room for growth here. That being said, humans will always be the decision makers, as understanding the personalities and characters of the teams you want to invest in remains a critical factor.   At twisted loop, we’re supporting both investors and business leaders to get the most from AI advancement, so it was great to hear some more perspectives on the topic.

Technology grows exponentially, taking no prisoners. What does it mean to commercial real estate? 🟥 Employees love things that make their life easier If the CRE industry doesn't keep pace with tech, it'll struggle to attract top talent. Given a choice between an AI-driven business and a spreadsheet-based CRE, the odds aren't in our industry's favor. I get that AI feels fresh and foreign now, but in the coming years, it'll be as routine as morning coffee. 🟥 Shareholders will push for higher returns It's not a secret that the biggest advantage of AI in industries such as healthcare, finance, and insurance is its optimization power. Being data-driven opens brand-new opportunities to grow businesses like never before. Just to mention the recent news from McKinsey about launching an internal generative AI tool (Lilli) to quickly get actionable insights from thousands of company documents. If it's not a challenge for CRE today, it will certainly be one tomorrow. 🟥 The world speeds up It's as simple as that. Technology is dynamic and forces it on us. 'Long-term' no longer means 50 years (not even 10, IMO), quarters sound like ages, and decisions are expected in months, not years. This is, for example, where McKinsey's Lilli can enter with its power to "allow us to spend more time with clients activating insights and maximizing the value we can create” (Erik Roth, McKinsey). "Activating & maximizing" is a really powerful promise, especially when delivered fast. #commercialrealestate #proptech #cretech

if you know, you know...journalists are a funny lot. always writing the extremes as opposed to righting the extremes. i guess advert $ can buy you (happiness) ;) the data. always. always. always. always. pay attention to the data. the devil is in the details. not the devil that most journalistic narratives appear to be today. or perhaps it always was and only now in the internet, digital being days we see it for what it is. the plastic in the pacific thanks to the success of The Coca-Cola Company. was it worth it? we ask. time will tell. as it always does. the numbers: $330 billion billys. ~26,000 A.I. start-ups 3 years. so why does this matter? well that's 2/3rds more than over 2018-2020 so what i say? this isn't news. no more than benchmarking the speed of a Tesla against it's ev peers. who cares? the underlying story is the de-coupling from oil dependancy and all those countries out there that have been provided by the good grace of g-d it's natural resource. misaligned with washington politics. america is addicted to oil. still is. addicted. now. we have Tesla. next will be other things that make up our modern life. robots. electric of course that become the cheap labour. the workshop of the world. that was/is china. they still hold this position. although we cannot help to witness when we observe the landscape that electrification is a big middle finger pose to all those that are f'ing with the price of oil. you know who you are f'ers. actually. it's all of them together. bedfellows they be. so while this journalist decides to scribe a story that points to the $, we on the other hand are acutely paying attention to innovation. or as a recent friend put it, th engineer creates the 'plane'. i the seats. yeah. whoever creates the seats gets the $$$$$. that's the natural order of 'tings. i get the feeling of the wanna be here. ask yourself what team the ny times plays for. they control 'a' narrative. i'm sure that these guys are intimately aware that their scribing influences social thought around (ai) and derivatively the investment by way of the everyman. or rather the 2nd degree removed from the wall street journal. that's scribing for the money proessionals. the ceos. the cfos. there's also their anglo sister the financial times. usually in lock and step between each other. so much to observe in these wranglings. the article is completely off. a few facts strung together. i wonder if their creative writing was born from princeton, yale, perhaps usc. some liberal college that deeply imbeds the beauty of our words. it's not informative. it's entertainment masked as contextul knowledge of what's happening in (ai) in this moment. sad truly. wasted opportunity. there is no beginning. there is no end. this is pollution. a distraction. inconsequential it is. have a laugh. i do ;) source: https://lnkd.in/eSbhQH76 < . >

This morning I was building a financial model and it gave me 𝗲𝗻𝗼𝗿𝗺𝗼𝘂𝘀 𝗽𝗹𝗲𝗮𝘀𝘂𝗿𝗲. That's right, I just said that financial modelling gives me "𝘦𝘯𝘰𝘳𝘮𝘰𝘶𝘴 𝘱𝘭𝘦𝘢𝘴𝘶𝘳𝘦" 😎 Why doesn't it give more people pleasure? There are two recurring themes that give financial models a bad name in early stage startups: 1. "This is nonsense" thinking - many investors will proudly say that modelling early stage companies is a nonsense, when you're pre-product, how can you possibly know what's going to happen in 2 years time? 🤔 2. "Jobs to be done" thinking - many founders see their model as a tick in a box in a fundraising deck. Not important but necessary in case someone asks ✅ The reason models are valuable isn't because they are likely to be "right" or "wrong" or because they tick a box, it's because the process of building a model forces the model builder to think deeply about the business, its key drivers, the merits of various revenue models, overlooked costs (and therefore hurdles), the realistic people requirements and it therefore helps the builder develop clarity and conviction 🚀 In this sense, like writing a memo or an essay, building a model is a journey (of enlightenment) rather than a destination 🛳 As I was building this morning, it occurred to me that the number of AI tools that help build models might actually 𝗱𝗲𝘁𝗿𝗮𝗰𝘁 from the purpose since they accelerate the builder to the finish line (jobs to be done) and away from the journey. But then one of my formulae wouldn't work and I was spinning wheels debugging it. One quick lean on an AI tool later and the bug was resolved. And this is the pertinent point: AI tools should not detract from the main thinking of building a model but they should debug them - there is nothing, 𝗮𝗻𝗱 𝗜 𝗺𝗲𝗮𝗻 𝗻𝗼𝘁𝗵𝗶𝗻𝗴, in spending 30 minutes debugging a typo in a formula. At TMA we help founders get their model 𝘁𝗼 𝘄𝗼𝗿𝗸 𝗳𝗼𝗿 𝘁𝗵𝗲𝗺, to save them money and time and to give them purpose and clarity.

Why is Real-Time Reporting is Crucial for Early-Stage Startups? -> Quick Decisions: Founders need rapid adaptation to market changes. Real-time reporting supports swift, data-driven decisions. -> Cash Flow Monitoring: Essential for understanding cash runway and burn rate with limited reserves, ensuring financial stability. -> Investor Confidence: Provides transparency and control, building investor trust with real-time insights. -> Assessing Pivots: Facilitates quick assessment and forecasting of business model changes for data-driven decisions. -> Resource Allocation: Helps prioritize initiatives, control costs, and align resources with strategic goals. ~~~~~~~~~~~~~~~~~~~~ This is how dayX AI uses #AI to Automate your Financial Operations 🚀 -> Generates investor-ready financial and operating metrics in real-time within minutes. -> Automates #accounting to reduce manual operations, prevent delays, and minimize errors. Say goodbye to spreadsheets! -> Leverages autonomous #FP&A for accurate financial projections and real-time insights. -> No more back and forth with your accountants. #dayXAI, #AI, #startups, #founders, #accounting, #planning, #reporting, #forecasting, #investors, #automation, #realtime

US$4 Mln Funding Businesses depend on information. Information enables decision-making and is critical to record-keeping. Since the time of the Mesopotamians, people have recorded or “documented” information, first in analog and then digital forms. Business requires not just digital documentation but digital data. But much of digital data is in unstructured documents, especially in Finance operations. The earliest documents recording inventory and the movement of goods—accounting ledgers—were written in clay in proto-cuneiform, before the written language called Cuneiform. These clay documents had rows and columns of pictograms representing items with holes impressed to indicate quantity. That start of business documentation eventually developed into ink-and-paper and finally electronic ledgers. With the advent of computers in the 20th century, companies needed to record documented information differently: digital data. For decades that has meant the tedious process of manually keying data into digital format on a computer. NICHE TO MAINSTREAM Processing unstructured finance documents has been a challenge. Because the extraction and conversion of data from analog and digital unstructured finance documents to structured digital data has, up to now, been painful. Artificial Intelligent is changing that. By unlocking the data in unstructured public and private financial documents, it will enable users to get specific answers, generate research reports, and uncover insights that would have taken hours of investigation in the past. There's a massive market opportunity for startups offering AI solutions. One of the startups emerging from the space is Finpilot. Finpilot is a startup providing an AI fintech platform for financial analysts. The startup provides financial analysts with a financial research co-pilot to SEC filings, financial reports and more, which is now available in public beta. The public beta gives users the ability to query data in a conversational style and receive back detailed answers. Beyond a platform for querying financial data, the platform will support a personal agent that enables the automation of many of the common workflows for analysts, such as generating reports, completing many-step, complex analyses, including comparing companies, analyzing years of trend data scattered across a trove of documents, and extracting specific segment data hidden in charts and text. Founded by Lakshay Chauhan and John Alberg, Finpilot has raised $4 million in Seed funding. The company intends to use the funds to expand operations and its business reach. #funding #ai #fintech #startup #copilot #financial #analysts #vcdeal

Meet Unseen, one of Antler Australia’s portfolio companies and the latest feature in the Antler Investor Memo Series. 💥 Co-founded by Joanna Marsh and William Cosby, Unseen is making enterprise-grade market intelligence more accessible, initially targeting the real estate sector. Unseen's solution is not just about enhancing data accessibility; it’s about transforming the way businesses interact with data, enabling a more intuitive, efficient, and cost-effective process across every data-driven sector. Their approach, combining a custom template language with a proprietary data processing engine and AI, aims to extend the benefits of data analytics beyond the traditional confines providing streamlined access to critical market intelligence. For more details on Unseen and their pioneering work, read the full article in Startup Daily here: https://lnkd.in/g5MXWXjr

As we wrap up the first week of 2024 - there is a lot to be excited about this coming year, especially since we believe the #RealEstate Tech sector will be one of the dominant winners. Not only will generative AI unlock $180B in value as McKinsey & Company points out in the interesting report below, but also the upcoming Fed interest rate cuts will boost the RE market as a whole. Disruption to the legacy real estate world is possible, as has already been proven by a number of our portfolio companies such as Daisy in property management, Covercy in CRE banking, and Tough Leaf in public construction. Most importantly RE Angels is always looking for more great ideas and hungry to invest in bold entrepreneurs. 💪 Cheers to a successful & peaceful 2024! 🙏 #proptech #contech #refinance #retech https://lnkd.in/efbUyCBy