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Dealwise, an investment bank that scales with AI instead of analysts

Hacker News

Dealwise, an investment bank that scales with AI instead of analysts

Hi hacker news, We’re a former PM and software engineer from Robinhood who decide to start an investment bank for startups. In 2023, we had just shut down our previous YC-backed startup Psychic ( https://news.ycombinator.com/item?id=36032081 ). We were one of many startups building generative AI infrastructure long before it had become apparent what the applications were going to be, and it turns out the bet we made was wrong. This might sound familiar to anyone who’s been through the web3 hype cycle, but it was a big learning for us. Around the same time, we noticed a lot of interest in M&A activity from our founder friends, and informally advised one of our batchmates in the sale of his startup. We started learning about what it takes to get deals done, and that’s when we realized there was a massive gap in advisory services for founders who want to step off the venture path (or were never on it in the first place) that existing service providers don’t fill. The problem: if you’re a founder with less than $10mm in annual revenue who wants to sell their software startup, investment banks won’t work with you because the fees won’t cover their costs. This leaves you with few good options: - there are “business brokers” in the lower end of the market who will try to sell your company for a commission. 95% of them actually have negative value because they don't have a good network in the software industry, while locking you into multi-year exclusivity agreements. If they were any good, they’d go upmarket and just become investment bankers. - marketplaces like Flippa or Acquire.com are great for four, five and six figure transactions but serious corporate and institutional buyers tend to avoid these platforms. There’s also significant negative signaling if your startup is being listed next to the latest a flappy bird app. - most founders choose to DIY their acquisition process, but it’s a LOT of work. We see many founders get stuck in a viscous cycle of try to sell → get distracted → growth declines → can’t find buyer → selling gets even harder → they ultimately shut down. The median founder sells 0 companies in their lifetime, so it makes no sense to spend months becoming a M&A expert when you have a business to run. Our solution We started Dealwise in December 2023 to be the good option for startup founders looking to get acquired. We’re new, but our track record is phenomenal. Traditional M&A advisors typically take a minimum of 6 months to close a deal, while we went from launch → 7 figure deal closed in just 3 months, with several more companies under offer. The fact that our background is in engineering and not investment banking helped a lot. The finance mindset is to throw bodies (usually analysts) at a problem, whereas the engineering mindset is to invent better ways of solving a problem. That’s why as we scale, we’ll be applying our experience from building LLM tooling for Psychic to automate the majority of back office tasks so we can focus our time on supporting founders overlooked by the traditional investment banking industry.

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
99%99% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, activity, tasks · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, hacker news · Missing: https docs, excited, just released
70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month, way · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, growth · Missing: arr, mrr, profit
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
16%16% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: web3 · Missing: chat, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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