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Likely Startup Ideas

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A startup that provides a service for companies to help them figure out which employees are likely to leave the company


A ride-hailing company that lets people find a ride based on the route they’re most likely to take.


Using AI to help brands reach their customers with the most relevant ad campaigns. The startup offers a “personalized” message algorithm that’s meant to deliver ads that are more likely to be clicked.


Retail startup that works with retailers to get merchandise into the hands of customers on an evening delivery service, making it more likely that customers will buy.


A marketing tool that lets you track your social media interactions, and see which customers are most engaged, most likely to buy, or engaged at all. The company has raised $2 million in funding.


A personal assistant that helps you organize your life by helping you keep an eye on the things you are most likely to forget.


A company that wants to help you manage your network of colleagues, friends, and customers. The startup wants to build a smarter network of people to keep up with connections and build a community with. It plans to focus on small companies because they tend to have more existing relationships to build on, and are more likely to use social networks.


A startup that is using data analytics to help small businesses make better decisions. The company says it can help a company make a better marketing decision by determining which of their customers are the most likely to buy, or which of their products are most likely to be sold, based on behavioral data.


This startup is building a tool for banks to determine whether their customers are likely to pay back their loans.


A digital health platform for employees that allows them to book medical appointments, track usage, and get feedback from a doctor. The company wants to use machine learning to predict when employees are likely to need care, and to allow for more timely and personalized care, making it more efficient for employers.


A SaaS platform that helps B2B companies figure out when their employees are most productive and when they are most likely to leave. The startup says that their clients have saved a net of $20 million over the past two years.


A startup that allows users to automate their interactions with Uber. A spin on the existent “Uber for X” category, Upply pulls in Uber data and uses a predictive algorithm to help predict what a user is likely to say in an Uber interaction and then use that to automate the interaction.


A way to automatically sell your old stuff on eBay, using big data to determine what you’re likely to buy again.


A tech company that creates a platform for companies to market their apps and services, in a way that is more likely to catch the attention of consumers.


A startup trying to make the creation of a new app as simple as asking a friend to help you. The idea is that creative people will be more likely to give their own time free to help others who may need it, and the startup hopes to eventually help with getting new users on their apps.


A machine learning tool that helps companies assess which employees are most likely to be able to transfer to a new job.


The company uses machine learning for risk management, identifying which customers are likely to default on their debt and which loans are more likely to default on their debt.


A Tinder for the runway, using an algorithm to find the looks that are most likely to be the next big thing.


NOTE: These projects are not ranked in order of how likely they are to succeed.


B2B companies are more likely to use YC-backed startups as employees, as compared to one where the founders are located in the Bay Area.


A data science tool that automatically turns data into “actionable, knowledge-rich insights” about any given user, looking for insights like “which users are most likely to convert to customers, or which users spend the most money”.


A startup that wants to bust the myth that just because you’re over 40, you’re not likely to find a job.


This company is building a platform to help merchants in the UK identify which of their customers are most likely to close a sale. It’s a tool for retailers to get better at selling to their customers.


A personal assistant that helps people figure out which of their friends is most likely to be on Twitter and Instagram.


The other factor is the service-based nature of B2B companies. B2B companies typically spend on services, such as accounting or legal services. The most common B2B service businesses include accounting, banking, and legal services. B2B marketing startups are therefore more likely to be targeting B2


 A company that collects data from credit cards to build a predictive model of which cardholders are likely to pay back their debts (and which ones are likely to default). It’s looking to offer a free model to banks for their riskiest customers.


A fitness-centric social network, with fitness-centric content, for people who are content-first, not fitness-first. The startup wants to use AI to recommend activity, food, and other content that people are likely to enjoy.


An AI-powered product that helps you determine whether you’re likely to succeed at something, like getting into a top university.


A data-driven platform that helps brands find new customers on Instagram. Each week, it finds tens of thousands of new customers that are likely to buy based on data such as recent activity and location.


A startup that wants to improve the way health insurance companies use data to find people who are likely to need health care.


A startup that uses artificial intelligence to help companies set up software development programs that will be more likely to succeed.


A dating app for people with mental illness. The app asks you to rate your symptoms and asks you how you interact with people, giving you a score between 0 and 10 based on how likely you are to get into a fight or be abusive.


This is a software platform that allows call center workers to find out which of their client’s questions are likely to be answered by a computer and which ones need a human operator.


In 2014, Y Combinator’s summer program accepted 14 companies, with four eventually being launched as companies. In 2015, Y Combinator saw 20% more applicants than 2014, with the startups 35% more likely to succeed. In 2016, the number of companies accepted has been set at 14 by Y Combinator.


A software company that starts by building a predictive model for which loans are more likely to default and then uses that model to predict which loans are particularly risky. The company then buys up those loans and uses them as collateral for insurance on other loans.


A good way to get more consumers to buy more from you is to make them feel more confident about buying from you. We’re all more likely to buy from companies we feel like we can trust, so this startup wants to help companies make their websites a better place for customers to interact with them.


This startup wants to make it easy for anyone with a bad credit score to get a loan. The company’s co-founder says that when running a small business, it’s likely that they know the person they’re dealing with personally. The company uses that advantage to provide a personalized loan experience.


Idea: A startup that wants to use machine learning to solve the problem of sifting through job applications to find the candidates who are likely to be a good fit for your company