The future of business: 50 AI startups you should invest in for 2024

The unprecedented development of technology both excites and scares me, especially in the field of artificial intelligence. Everyone predicted that 2024 would be the golden age of AI startups as companies push the boundaries in a variety of sectors, from healthcare and fintech to automation and blockchain. Businesses are investing in startups, looking for ways to integrate AI and other ways to use the technology to their advantage.

In this article, I decided to reflect on which startups should be concentrated for investment and argue this with my IMHO.

HealthTech AI: AI on guard of diagnostics

All startups in this field want the same thing: to revolutionize patient care, diagnostics, and drug development. They all work according to a familiar scenario since hospitals have a standardized workflow, regardless of specialization. For example, Olive AI, one of the most popular tools in the field of AI in healthcare, not only optimizes the work of hospitals but also provides significant financial savings. According to last year's research, hospitals that actively use AI-based systems were able to reduce administrative costs by as much as 20%.

This allows hospital staff to focus on improving patient care and outcomes. The global AI market in healthcare is expected to grow at a CAGR of 42.4% until 2030, which means that we can expect even more transformations in the healthcare sector.

The main features of such startups, in addition to the use of AI, of course:

• Focus on personalized medicine: Genetic profiling is a decisive factor in individualizing approaches, and such startups are currently targeting this. Telemedicine and remote care: The pandemic has given us these changes as a vector of development. This has not only increased patients' comfort but also allowed them to access treatment regardless of their place of residence.
• Regenerative medicine and biotechnology: There is a revolution going on here, without exaggeration. Startups in this sector are expanding the boundaries of stem cell therapy, gene editing (CRISPR), and tissue engineering. Thus, the root causes are eliminated rather than the consequences treated.
• Data security and integrity: as soon as healthcare data has gone digital, startups have turned to an increased level of cybersecurity.

Who to watch in this space:

• LeanTaaS: More of an operational thing that helps to properly allocate hospital resources (e.g., use of infusion chairs and OR time spent), which ultimately helps to reduce patient wait times and improve hospital productivity. It has direct analogs - Corti.ai and CloudMedX- which also enhance the hospital's work and help personalize the experience, for example, sending reminders to patients about check-ups and other such things.
• Tempus: Here, AI is used to personalize the experience rather than the treatment. AI analyzes clinical and molecular data to provide more targeted treatment options.
• Viz.ai: This is probably the coolest AI application. The service uses real-time AI to detect urgent medical conditions like strokes. It is literally accelerating diagnosis and treatment through data processing.

I would also recommend reading about the following startups: 

• PathAI (improve the accuracy and efficiency of pathology diagnosis); 
• Insitro (combines AI and biology for drug discovery and development);  
• Butterfly Network (provides portable AI-powered ultrasound technology);  
• Tempus (uses AI to analyze clinical and molecular data for personalized cancer treatment); 
• Zebra Medical Vision (leverages AI for medical imaging diagnostics, offering a variety of algorithms); 
• Eko (uses AI for cardiovascular disease detection through digital stethoscopes);
• Atomwise (employs AI for small-molecule drug discovery); 
• Aidoc (AI-powered software for radiology, providing real-time support for medical imaging); 
• Qventus (AI platform for real-time hospital operations optimization); 
• Owkin (combines AI and medical research for personalized medicine, particularly in oncology); 
• Babylon Health (AI-driven platform for virtual healthcare consultations and diagnostics); 
• Freenome (applies AI to detect early-stage cancers through blood testing);
• Biofourmis (AI-driven platform for remote monitoring of patients with chronic conditions).

FinTech AI: everything is fast and safe

The main tasks here are to secure and optimize banking operations, improve fraud detection, and personalize customer experience. Another pressing issue is security. Banks are gradually strengthening their security, moving to new technologies, and wanting to automate processes, and AI helps them with this. For example, Zest AI uses machine learning algorithms to help financial institutions improve loan underwriting decisions. In fact, financial institutions are subject to 300 times more cyberattacks than other industries, highlighting the truly high need for advanced security measures.

Today, machine learning algorithms are greatly helping financial institutions make more accurate loan underwriting decisions, thereby reducing risks and increasing customer satisfaction.

Today, Fintech startups have some key characteristics:

• Focus on embedded finance: This refers to the direct integration of financial services directly into non-financial platforms and services. This means that there is an increasing integration of APIs that simplify processes such as payments and lending. Plaid and Stripe are prime examples of this.
• The rise of decentralized finance (DeFi): This is now the main focus of Fintech startups, which provides the ability to carry out peer-to-peer financial transactions without traditional intermediaries such as banks. For example, DeFi applications based on blockchain technology allow users to lend, borrow, trade, and earn interest on crypto assets, creating a more open and accessible financial ecosystem.
• Focus on financial inclusion: These startups target markets that lack traditional banking infrastructure, offering digital wallets, mobile payments, and microcredit services.
• RegTech and compliance: This is about using AI, data analytics, and blockchain to automate compliance tasks and reduce regulatory risks. For example, companies like Trulioo and ComplyAdvantage offer solutions that streamline KYC and AML processes using AI and blockchain.

Who to watch in this space:

• LenddoEFL: A well-intentioned project that uses alternative data to predict the creditworthiness of financial institutions, allowing them to provide loans to low-income groups.
• Provenir: At its core, it’s an excellent risk forecasting tool that helps financial services companies make smarter lending decisions. Its specialty is real-time risk analysis, meaning it’s also a way to detect fraud and more.
• Kensho (S&P Global): This AI-powered platform benefits financial markets by providing risk management and trend forecasting information for investing and underwriting.

I would also recommend reading about the following startups:

• Klarna (a global buy-now-pay-later provider leveraging AI for personalized financial solutions);
• Brex (provides AI-driven corporate credit cards and financial management tools);
• Plaid (uses AI to connect consumer bank accounts with fintech applications);
• Sentieo (AI-powered financial research platform for investment professionals);
• Upstart (AI-driven lending platform aiming to improve access to affordable credit);
• Nubank (digital bank using AI to offer financial products in Latin America);
• Tractable (applies AI to financial services like insurance, particularly in damage assessment);
• Shape Security (AI-driven solutions to protect financial services from cyber threats);
• BlueVine (provides AI-powered small business banking and lending solutions);
• Affirm (offers AI-backed consumer financing and buy-now-pay-later options);
• Ocrolus (uses AI to automate financial document analysis for lenders);
• Figure (uses AI and blockchain for faster financial services, focusing on loans and home equity);
• Kasisto (AI-powered virtual assistants for banks to improve customer engagement);
• Cerebro Capital (AI platform to streamline the commercial loan process and underwriting). 

AI in ClimateTech: Changing the World, Saving Whales

These startups prioritize climate change, help companies reduce emissions, and make more sustainable decisions. These approaches help build a long-term vision and combine progress with environmental stewardship by providing hyper-localized data and predictive models. I can immediately recall a startup named Climavision, which is actively using advanced weather forecasting technologies to benefit agriculture and logistics.

By mid-2023, 90% of businesses have already started incorporating sustainability into their business strategy, recognizing that environmentally conscious practices benefit their brand and improve operational efficiency. These startups also have unexpected applications. For example, global supply chain optimization using more accurate weather forecasts can help reduce 15% of emissions from logistics operations.

sustainability.

So here are the key characteristics of these startups that I would highlight:

• Focus on carbon reduction and sustainability: This is a global goal for these startups to address the root causes of climate change.
• Scaling clean energy solutions: These startups are at the forefront of the ClimateTech movement. Their goal is to scale technologies like solar, wind, and battery storage to help meet growing energy demand while reducing dependence on fossil fuels.
• Circular economy and waste management: Startups in this space are developing technologies to turn waste into resources, reduce plastic pollution, and extend the life cycle of products.
• Collaboration with industries: Startups in this space often collaborate with established industries like agriculture, energy, and transportation. This helps scale their impact.
• Funding and policy support: ClimateTech is seeing extreme interest from venture capital and government incentives.

Who to pay attention to in this field:

• The Weather Company (IBM): This company provides AI-based weather data and forecasting. Its main clients are media, aviation, and energy, where detailed forecasts, data analytics, and tools for business operations are especially relevant.
• AccuWeather: the main focus in this case is risk mitigation tools in industries such as transportation, agriculture, and insurance.
• WeatherBug (parent company Earth Networks) is a unique project using its weather sensors and advanced models network to provide real-time data and forecasts. It also detects lightning and monitors the environment.
• Sferic by AEM: This service's primary purpose is weather monitoring and alerting relevant industries (particularly utilities and public safety).

I would also recommend reading about the following startups:

• Jupiter Intelligence  (AI for predicting and mitigating climate risks);
• Cervest  (uses AI to assess climate risks and impacts on assets);
• CarbonChain  (AI-driven carbon accounting and emissions tracking for supply chains);
• Sequest  (AI-powered platform for scaling nature-based carbon removal solutions);
• Sylvera  (AI for assessing carbon offset quality and impact);
• Emrgy  (AI-driven hydropower technology for renewable energy generation);
• Regrow  (AI tools to help agriculture reduce carbon emissions and improve sustainability);
• Spire Global  (AI-powered satellite technology for climate and environmental data analysis);
• Envirosuite  (AI-driven environmental intelligence for air and water quality management);
• Raptor Maps  (uses AI to optimize solar energy generation and monitor equipment health);
• Watershed  (AI-driven platform for managing and reducing companies' carbon footprints);
• Tomorrow.io  (AI-based climate intelligence for weather forecasting and climate adaptation);
• ClimateAI  (predictive AI for agriculture to combat climate variability and optimize crop yields);
• Demex  (AI tools for managing climate risks and optimizing financial decision-making for businesses).

AI and Blockchain: The Future is Here

I believe the convergence of AI and blockchain is the core of innovation. The combination of AI and decentralized networks creates entirely new approaches and allows devices to communicate and transact autonomously. One of the key players in this space today is Fetch.AI, which will enable devices and algorithms to perform complex tasks such as data exchange, asset trading, and resource optimization without a central authority.

The ability of AI to process massive amounts of data and make intelligent decisions, combined with the security and transparency of blockchain, opens up possibilities that were unimaginable just a decade ago.

The combination of AI and blockchain enables the creation of more sophisticated automated trading algorithms, which in turn can analyze market trends, predict price movements, and execute trades autonomously. A recent report from Accenture predicts that by 2025, around 75% of financial companies will use AI-based solutions, so by automating resource allocation and managing assets without intermediaries, startups are leading us into a new era.

Here are some of the defining characteristics of these startups:

• Communication and data sharing: The main focus of these startups is secure data sharing on decentralized networks, allowing organizations to share and monetize data in a trustless environment.
• Smart contracts and automation: This simplifies complex tasks such as supply chain management, legal agreements, or insurance claims processing. This all reduces costs and human errors, making industries like finance and law ripe for change.
• Increased investment and market growth: According to CB Insights, AI-related startups alone will raise $94 billion in 2023, and much of this money is going into AI-blockchain integration.
• Ethical AI and governance: This is an exciting aspect. Many of these startups are also solving ethical issues related to AI, such as bias, fairness, and accountability. This is a critical aspect in sectors like legal tech and healthcare.
• Use in IoT and Edge Computing: AI blockchain is increasingly being used in the Internet of Things (IoT) space. That is, decentralized networks allow IoT devices to communicate, transact, and perform tasks autonomously.

Who to watch in this space:

• IOTA: This is essentially a distributed ledger designed explicitly for the IoT. It aims to exchange data between machines and focuses on providing a secure and free environment for device-to-device transactions. The technology is called Tangle, and it enables scalable, free microtransactions.
• SingularityNET: This fully decentralized platform for AI services allows developers to build, share, and monetize AI technologies. It uses blockchain technology to connect AI algorithms and applications, making sharing autonomous agents and decentralized AI much more accessible. 
• Hedera: Another decentralized public network for fast, transparent, and secure transactions. The main goal of the technology is to support applications that require decentralized computing and data exchange. Hedera offers unique consensus mechanisms to maintain trust and security, especially for enterprise-level applications, which large companies often use.

I would also recommend reading about the following startups:

• Ocean Protocol (data sharing and monetization via decentralized AI models);
• Cortex (AI-driven decentralized applications (dApps) on the blockchain);
• Numerai (decentralized hedge fund using AI to make financial predictions);
• DeepBrain Chain (blockchain-based AI computing network for training models);
• dKargo (uses AI and blockchain for logistics and supply chain optimization);
• Endor Protocol (predictive analytics platform using AI and blockchain);
• Velas (AI-enhanced blockchain platform for scalability and speed);
• Blockchain AI (combines AI and blockchain to improve digital security);
• FetchPark (Autonomous parking management using blockchain and AI);
• Artificial Liquid Intelligence (ALI) (AI avatars powered by blockchain);
• SingularityDAO (decentralized finance (DeFi) platform for managing AI-powered crypto funds);
• Neureal (predictive market intelligence and decentralized predictions);
• VAIOT (combines AI and blockchain to create intelligent virtual assistants for legal and insurance services).

AI and Education: Everything You Need to Become Superintelligence

The education landscape has not remained unchanged either. Most often, there is a focus on tools that improve the learning process, increase administrative efficiency, and facilitate personalized education. Such developments not only automate the work of educational institutions but also help make the learning process more accessible. Tutors and AI-powered chatbots also make learning more adaptive by providing 24/7 support. For example, the startup Squirrel AI focuses on personalized adaptive learning with the help of AI-powered learning systems. It can also adjust content depending on the progress and pace of each student. McKinsey's research suggests that adaptive learning can improve student performance by 10-20%.

Thus, the rapid adoption of AI and digital tools is shaping a future in which education is more personalized, effective, and accessible. This means that both students and teachers will benefit, a win-win strategy. Combining AI, automation, and adaptive learning helps students achieve better results and makes education more flexible to meet the needs of individuals and institutions.

Key features of these startups include:

• Gamification and engagement: This greatly increases interest in learning by making it more interactive and enjoyable. For example, I would mention platforms like Kahoot!, which use game mechanics to motivate students and provide instant feedback.
• Remote and hybrid learning solutions: The demand for remote learning tools skyrocketed during the pandemic, and this trend is still ongoing. Famous players like Outschool and Coursera are successful examples. According to HolonIQ, this shift is expected to lead to the global EdTech market reaching $404 billion by 2025.
• AI-powered automation and analytics: Here, I am talking about the educational institutions' side. Startups for them help automate grading, track student progress, and provide data analytics to improve course delivery.
• Increased accessibility: The main focus of such startups is to create equal access to education for everyone, including the underprivileged. Read, for example, about Khan Academy, which provides free resources worldwide.

Who to watch in the field:

• Riiid: This product aims to prepare for various standardized tests, such as the GMAT. Machine learning studies user behavior and adapts lessons accordingly.
• Querium: This platform is focused on STEM education, and its primary purpose is to help students improve their math skills. AI helps personalize lessons and get real-time feedback. It is already widely used in high schools and colleges.
• Carnegie Learning: Another adaptive platform that helps rebuild everything in real-time based on student performance and provides personalized feedback.

I would also recommend reading about the following startups:

• Carnegie Learning (AI-driven tutoring systems for mathematics);
• Century Tech (personalized learning platforms powered by AI);
• Knewton (adaptive learning technology for higher education);
• Content Technologies, Inc); (AI-generated personalized textbooks);
• Cognii (AI-powered virtual assistants for personalized learning and assessment);
• Kidaptive (adaptive learning platforms for early education);
• Osmo (AI-driven learning games for children);
• Mindspark (adaptive learning software for math education);
• DreamBox Learning (AI-powered learning platform for K-8 math);
• Quizlet (AI-driven flashcards and study tools);
• Smart Sparrow (adaptive e-learning technology that customizes lessons).

Hiring: Unitecode's personal story

The labor market is completely transforming. My team at Unitecode has been using AI in candidate selection for several years, relieving people of most of the burden and helping to evaluate conditions comprehensively.

We have developed a multi-level candidate search system, and AI integration is an alternative to ineffective filters on various platforms. AI analyzes the candidate's experience in detail and compares it with the client's request. Thus, during personal interviews, we can examine the candidate in terms of potential tasks, language knowledge, and soft skills. The client gets ideal candidates and does not waste time on specialists with whom a match will never happen.

Why these startups are essential

Above all, we are discussing innovations that solve real problems by innovatively implementing AI. So, suppose you, as an investor, want to be on top of innovations and get the most out of them. In that case, the above startups are ahead of their time and invest not only in overall progress but also in scalability, sustainability, and long-term profitability.

Each startup on this list has demonstrated how a good idea can thrive in favorable conditions. The role of AI in automation, healthcare, fintech, education, and sustainability is increasing, and this is just the beginning. I believe that combining AI and blockchain promises a future where security and intelligence come together. And we are amazingly close to this new, incredible world.