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ScaleFactor is a cautionary tale of overpromising and underdelivering with AI.
The Austin, TX, startup set out to automate bookkeeping, financial forecasts, and other back-office tasks. Last month, it told Forbes it was shutting down because the pandemic had wiped out nearly half of its annual recurring revenue. After more digging, Forbes reported Monday that the startup’s problems predated the pandemic.
The backstory
ScaleFactor’s efforts to automate away the accountant didn’t work.
Customers say ScaleFactor didn’t deliver the automated, real-time bookkeeping tools it promised. In fact, it often relied on traditional bookkeepers and hired a Filipino contract accounting firm. Investors realized ScaleFactor was “more of a services business than a software platform,” per Forbes.
In January, ScaleFactor pivoted to an Uber-esque marketplace model where it would serve as an intermediary between accountants and companies. Investors pulled the plug a few months later.
Artificial artificial intelligence
Plenty of founders, sales departments, and marketers slap the AI label on their products. This was especially popular in the 2010s as AI took off as a technology and a buzzword.
But there are fresher examples. From 2019, to wit:
- Engineer.ai, a SoftBank-backed startup, claimed to automate mobile app development. In reality, the WSJ reported it primarily relied on outsourced developers.
- Forty percent of European “AI startups” didn’t actually use the technology, according to a London VC’s survey.
- Every FAMGA company was caught using contractors or employees to transcribe voice snippets meant for virtual assistants or automated transcription tools.
For FAMGA, the human legwork makes natural language processing and voice recognition systems better (through labeled data). It’s a controversial means to an end, but humans were in the loop to improve AI that exists.
In the other cases, startups exaggerated capabilities they didn’t have. It’s disingenuous, but also unsustainable. The business can’t achieve the unit economics or scalability of AI software, unless it’s bought itself time to build the tech stack it’s describing.