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Why AI SaaS Fails: Enterprise Workflow Automation

AI SaaS is going to fail. 90% of (VC-funded) companies that are building single-function SaaS, for example AI SDR, AI Marketer, AI Outbound, AI Bookkeeping, etc, are all missing the point. Sentiment in enterprise has been shifting to being jaded towards AI because these generalized SaaS plays can't solve their problems, or introduce more of a headache than they're worth. SaaS is built with everyone in mind, meaning it does not fit 100% for anybody. The problem is enterprise clients want their EXACT workflow automated. They aren't going to be satisfied with 80%, because the person you just convinced them to fire was already doing 100%. Each 'customer' then has different specifications: I want X data-source, augmented in Y way, with the output formatted as Z. I get my bills on A software, I want them approved at B threshold, and I want summaries formatted as C at D cadence. You can't possibly service all of these people with one single SaaS solution - you need some level of forward-deployed engineering per client to REALLY solve their needs. And no one is doing this, which is why enterprise is starting to turn their backs on AI software. I built Varick Agents with this exact thesis in mind 6 months ago. We are the Palantir for enterprise-agents. We custom build agents per workflow, ensuring that we actually solve our clients' pain-points instead of feeding them the same software that only half-worked for someone else. This is why our clients' are saving 1000s of hours a month, and millions of dollars a year already. If you're an operator or own a business and want Varick's solutions, shoot me a DM - let's chat about bringing AI to your company.

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