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I worked for years as a freelance contractor in NLP. Clients and agencies generally consider sentiment analysis a simple matter. But the reality is off-the-shelf packages, like TextBlob are rule-based. When you put together an app, like a chatbot for customer services, they rarely work well. The cost to improve is nothing short of reinventing a new system, which most wouldn't accept. Plus, the consensus is that people prefer self-hosted in-house solutions they can improve. Reasons to avoid sending texts to an external API are 1, privacy, and 2, per-call pricing. So I have this idea. I create an open-source toolkit for sentiment analysis. It will be data-driven, not rule-based. So it can fit most use cases well. It'll be a full package with GUI, for labeling, training, and an API server to self-host the model. I keep a private repo of data to generate a good-enough model for a niche: customer service chatbots. A part of which is curated (scraped), and a part is labeled by myself. I sell a subscription to the model, during which period, I try to gather and label more data to improve the model. I can design the system to support partial training. That is, the customer can improve based on my model, using just hundreds of lines of their own data. I figured if I priced it the right way (10-20% of hiring someone to create one), I can sell it to dev shops and agencies. I can go to Linkedin or Upwork to approach my customers. Does this sound like a viable idea for a one-man shop? |
To proof me wrong, just try to sell the idea as a not yet existent or as a fake product. Build a landing page where people can subscribe to get further information, lead a few prospects to this page and count the subscriptions.