What’s a good mental model to understand where we’re going next in AI ecosystem development?
The AI Convergence explains which areas will be critical to look at in the next 10-30 years:
In the three layers of AI, I’ve explained a good mental model to leverage to understand what’s going on and where to keep an eye on when it comes to the nascent AI ecosystem.
In addition, and that’s a very tricky one, how can we judge whether a company has some moats or is building any sustainable ones in the AI industry?
I’ve put together this whole piece to explain how AI companies might be able to build a long-term moat on top of a very competitive industry that is just developing.
A caveat here:
The research below is not intended to find out who will be the next unicorn, the AI landscape is still quite fluid. Instead, it’s more to emphasize in which areas of development of the ecosystem we might expect new major companies to emerge, as these verticals are the ones where there might be more traction, both from enterprise and consumer standpoint.
With that in mind, these are some of the patterns we found out as the research was undertaken:
Convergence of Hardware and Software: Integration of cutting-edge hardware and advanced software to enable scalable and efficient AI solutions.
Agentic and Autonomous Systems: Development of AI agents capable of independent reasoning, task execution, and decision-making.
Domain-Specific Innovations: Tailored AI applications addressing high-value problems in healthcare, legal, transportation, and other verticals.
Democratization and Accessibility: Open-source platforms and user-friendly tools driving broader adoption of advanced AI capabilities.
Cross-Industry Applications: Versatile AI solutions seamlessly integrating across diverse sectors like climate, space, and enterprise data management.
AI Safety and Ethical Alignment: Focus on reliability, transparency, and regulatory compliance to ensure ethical AI operations.
Generative AI Beyond Text: Expansion of generative AI into creative domains like music, design, and visual applications.
Real-Time and Context-Aware AI: AI systems delivering dynamic, contextually relevant insights and actions in real time.
Rapid Infrastructure Growth: Scaling AI cloud and computing infrastructure to meet growing demand for processing power.
Collaborative Ecosystems: Shared frameworks and platforms fostering innovation within the AI developer and user communities.
Infrastructure (Hardware and Chips)
1 – CoreWeave
Year founded: 2017
Location: Roseland, New Jersey, USA
What they do
CoreWeave provides cloud-based GPU infrastructure designed for the intense demands of AI and machine learning.
Initially a cryptocurrency mining venture, the company pivoted in 2019 to focus on delivering powerful, scalable computing solutions.
Today, CoreWeave supports cutting-edge AI applications across industries, and, in May 2024, secured $7.5 billion in debt financing to expand its infrastructure and meet growing demand.
2 – Cerebras Systems
Year founded: 2015
Location: Sunnyvale, California, USA
What they do
Cerebras Systems is revolutionizing AI computing with the world's largest processor, the Wafer-Scale Engine (WSE-2).
Designed for deep learning and high-performance AI, their CS-2 system accelerates workloads that would take traditional processors months to complete.
This technological advancement has positioned Cerebras as a leader in the AI hardware sector. In November 2021, the company raised $250 million in a Series F funding round to become valued at over $4 billion.
In late 2024, the company announced plans to hold an IPO which some analysts believe could value it at around $8 billion.
AI Models (Software)
3 – OpenAI
Year founded: 2015
Location: San Francisco, California, USA
What they do
OpenAI is a leading AI research organization dedicated to developing and promoting AI technologies that benefit humanity.
The company is responsible for groundbreaking models like GPT-4 and DALL-E, which have significantly advanced natural language processing and image generation.
The Sam Altman-led company’s innovations are widely adopted across various industries and enhance applications from customer service to creative design.
In October 2024, OpenAI raised $6.6 billion in funding to be worth around $157 billion. The company noted that the raise would allow it to “double down on our leadership in frontier AI research, increase compute capacity, and continue building tools that help people solve hard problems.”
4 – Anthropic
Year founded: 2021
Location: San Francisco, California, USA
What they do
Anthropic is an AI safety and research company dedicated to developing reliable and interpretable AI systems.
Their flagship product, Claude, is a conversational AI assistant designed to perform a wide range of tasks while adhering to relevant safety protocols. Anthropic emphasizes AI alignment and transparency, which sets the company apart from others in the industry.
In November 2024, Anthropic secured an additional $4 billion investment from Amazon. This brought Amazon's total investment to $8 billion and strengthened their strategic partnership in the process.
5 – Mistral AI
Year founded: 2023
Location: Paris, France
What they do
Mistral AI is redefining AI accessibility by creating open-weight large language models like Mistral 7B and Mixtral 8x7B.
These models offer powerful AI capabilities without the constraints of proprietary systems, which makes these advanced tools more accessible to businesses.
The company’s competitive pricing and open-source approach to LLMs have quickly positioned it as a standout in the competitive AI landscape. In June 2024, Mistral secured €600 million in Series B funding, boosting the then-one-year-old company's valuation to an impressive €5.8 billion.
6 – Hugging Face
Year founded: 2016
Location: New York, USA
What they do
Hugging Face is a leading open-source platform that enables developers and organizations to build, train, and deploy machine learning models collaboratively.
Their extensive repository includes over a million models and datasets that work to foster innovation across the AI community.
Like Mistral, Hugging Face has become a central hub for AI development by democratizing access to advanced AI tools. It has also earned the attention of major tech companies such as Salesforce, Google, and Nvidia.
In August 2023, the company raised $235 million in Series D funding to become valued at $4.5 billion.
Applications (Enterprise)
Agentic AI
7 – /dev/agents
Year founded: 2024
Location: San Francisco, California, USA
What they do
/dev/agents is the developer of an operating system tailored for AI agents that aims to simplify the creation of digital assistants capable of autonomous task execution and decision-making.
Founded by former Google executives, CEO David Singleton claimed the company was seeking to deliver an "Android-like moment for AI" by providing a unified platform that enables seamless interaction between AI agents and users across various devices.
In November 2024, /dev/agents raised $56 million in seed funding to advance their innovative platform. Notable participants included Index Ventures and CapitalG—Alphabet’s independent growth fund.
8 – Sierra
Year founded: 2023
Location: San Francisco, California, USA
What they do
Sierra is redefining customer service with advanced conversational AI platforms that allow businesses to create personalized, responsive AI agents.
Led by industry heavyweights Bret Taylor (ex-Salesforce) and Clay Bavor (ex-Google), the company’s solutions are already used by top brands like ADT and Sonos to deliver seamless customer experiences.
Sierra’s innovative approach to AI-driven customer engagement earned it $175 million in funding in October 2024. The company—which recently crossed $20 million in annualized revenue—is now worth an estimated $4.5 billion.
9 – Imbue AI
Year founded: 2021
Location: San Francisco, California, USA
What they do
Imbue (once known as Generally Intelligent) is pushing the boundaries of AI by building LLMs that can think, reason, and make decisions in real-world environments.
Unlike typical AI tools, Imbue’s agents aim to truly understand user goals and solve complex problems autonomously.
This bold vision for practical, goal-oriented AI has set them apart in a crowded field. In September 2023, Imbue reached unicorn status after it secured $200 million in Series B capital.
10 – Adept AI
Year founded: 2022
Location: San Francisco, California, USA
What they do
Adept AI is transforming human-computer interaction by developing AI models that execute complex tasks across various software applications and APIs using natural language commands.
Their flagship ACT-1 model serves as an AI teammate that streamlines workflows and enhances productivity. This innovative approach has attracted significant attention and saw the company raise $350 million as part of a Series B funding round in March 2023.
CEO David Luan noted that the cash would be spent on productization, model training, and recruitment.
11 – LangChain
Year founded: 2022
Location: San Francisco, California, USA
What they do
LangChain has quickly become a developer favorite for building AI-powered applications thanks to its versatile framework that integrates with LLMs and diverse data sources.
Whether it’s powering chatbots or advanced analytics tools, LangChain’s open-source platform is now used by over 50,000 organizations around the world (including notable tech players).
In a Series A round led by Sequoia Capital, LangChain raised $25 million in February 2024. Accompanying the announcement was the launch of LangSmith—the company’s first paid LLMOps product with general availability.
12 – Cognition Labs
Year founded: 2023
Location: San Francisco, California, USA
What they do
The flagship product of Cognition Labs is Devin, an AI engineer that can independently code, debug, and deploy applications. Devin streamlines development processes and reduces reliance on human intervention, which increases speed and accuracy.
The potential to automate entire projects has captured industry attention and cemented Cognition Labs as one to watch.
In April 2024, after just six months in operation, the startup secured $175 million and became worth around $2 billion.
Data and Analytics
13 – Databricks
Year founded: 2013
Location: San Francisco, California, USA
What they do
Databricks offers a unified data and AI platform that simplifies data engineering, collaborative data science, and machine learning across various industries.
Their open lakehouse architecture combines the best features of data lakes and data warehouses, enabling organizations to process and analyze vast amounts of data efficiently and cost-effectively.
Databricks counts many industry behemoths among its clients, including AT&T, Warner Bros. Discovery, and Rivian Automotive.
The company announced in late 2024 that it hoped to raise as much as $8 billion—an amount that if successful, would represent the largest venture capital funding round ever.
14 – Arthur AI
Year founded: 2018
Location: New York, USA
What they do
Arthur AI specializes in monitoring and optimizing machine learning models, ensuring they perform accurately and fairly.
Their platform provides real-time insights into model behavior to help businesses detect issues like data drift and bias. This capability will become crucial as companies increasingly rely on AI for decision-making.
In September 2022, Arthur AI raised $42 million in a round led by Acrew Capital. The company is extremely well placed to meet future demand for its services. Indeed, Gartner predicts the AI software market will be worth $124 billion by 2025 thanks to organizations having thousands of AI models deployed.
“Some of the largest and most important companies in the world rely on Arthur to improve the performance and fairness of their critical AI models”, explained Acrew Capital partner Theresia Gouw.
Workplace Productivity
15 – Glean
Year founded: 2019
Location: Palo Alto, California, USA
What they do
Glean’s AI-powered search platform for enterprise productivity enables employees to swiftly locate information across various applications and databases.
By integrating data from multiple sources, Glean provides a unified search experience and substantially reduces time spent searching for information.
Glean raised over $260 million in a Series E funding round in September 2024 and doubled its valuation to $4.6 billion. The startup more than tripled its business over the previous 12 months with a product that addresses a shortfall of AI-powered enterprise productivity solutions.
16 – Moveworks
Year founded: 2016
Location: Mountain View, California, USA
What they do
Moveworks is transforming how companies handle employee requests with its cutting-edge AI platform “Copilot”.
Utilizing natural language understanding (NLU), the platform automates tasks like IT support, HR inquiries, and onboarding. It also seamlessly integrates with existing enterprise tools, which means employees spend less time waiting and more time being productive.
Trusted by over 300 companies and 5 million employees, Moveworks has solidified its place in AI-driven workplace solutions. The company was also recognized by Gartner in its 2024 Gartner Magic Quadrant for Artificial Intelligence Applications in IT Service Management.
Human Resources
17 – Eightfold
Year founded: 2016
Location: Santa Clara, California, USA
What they do
Eightfold AI is reshaping how companies attract and retain talent with its Talent Intelligence Platform.
Using advanced deep learning, it analyzes global workforce data to match candidates with roles that best suit their skills and potential. The platform also helps businesses improve diversity and streamline hiring.
With a growing global client base that includes the likes of Siemens, Vodafone, Coca-Cola, and Ernst & Young, Eightfold AI has become a key player in HR technology.
Legal and Compliance
18 – Evisort
Year founded: 2016
Location: San Mateo, California, USA
Evisort is a key player in legal tech with its end-to-end contract lifecycle management platform. Using AI, the startup automates time-consuming tasks like drafting, reviewing, and tracking contracts, freeing up teams to focus on more strategic priorities.
From legal to sales, businesses across industries rely on Evisort to streamline operations and reduce risk. The company’s $100 million Series C funding round in October 2023 was especially notable when one considers that venture backing (and indeed innovation) in the legal space are uncommon.
19 – Harvey
Year founded: 2022
Location: San Francisco, California, USA
What they do
Harvey is also reshaping the legal industry with its AI-powered personal assistant designed to assist lawyers in drafting contracts, analyzing documents, and conducting research.
By automating time-intensive tasks, Harvey helps law firms improve efficiency and focus on more important work. It is also well suited to professional service providers and the Fortune 500.
The company secured $100 million in a Series C funding round in July 2024. The round—which involved heavyweights like OpenAI, Google Ventures, and Sequoia Capital—took the startup’s valuation to $1.5 billion.
Applications (Consumer)
Search and Information Retrieval
20 – Perplexity AI
Year founded: 2022
Location: San Francisco, California, USA
What they do
Perplexity AI integrates large language models, chatbots, and real-time data retrieval to provide direct answers to user queries.
Their AI-powered search engine delivers concise, accurate responses complete with source citations, which promotes much-needed trust and efficiency in information discovery.
Perplexity has experienced substantial growth in its user base in recent times, with the startup now boasting around 10 million active monthly users. In November 2024, the company was in the process of finalizing additional capital that would see it valued at around $9 billion.
Creative Tools
21 – DeepL
Year founded: 2017
Location: Cologne, Germany
What they do
DeepL delivers some of the most accurate AI-powered translations on the market. Its platform leverages advanced neural network technology to translate complex texts with precision, and it can also be used to enhance writing or communicate across languages in real-time.
Known to outperform competitors in linguistic nuance, DeepL has become a favorite for users worldwide. It also has a customer network of more than 100,000 businesses, governments, and organisations such as Zendesk, Coursera, and Deutsche Bahn.
22 – Uizard
Year founded: 2017
Location: Copenhagen, Denmark
What they do
Uizard democratizes design by enabling users to transform simple sketches into interactive app prototypes without requiring design expertise.
The startup offers a platform that utilizes advanced machine learning models trained to convert textual descriptions into functional UI designs. This, in turn, makes design accessible to non-designers and fosters innovation across various industries. Demand for such services is likely to increase as more companies recognize the importance of product design to revenue and require an AI tool to power their creativity.
In August 2021, Uizard raised $15 million in Series A funding led by Insight Partners. Some of Uizard’s major clients include Samsung, IBM, Meta, Uber, Accenture, Logitech, and Adidas.
Development Tools
23 – Codeium
Year founded: 2021
Location: Mountain View, California, USA
What they do
Codeium enhances coding productivity with advanced machine learning models that provide intelligent code suggestions, real-time search, and conversational support.
By analyzing patterns in over 70 programming languages, Codeium’s tools anticipate developer needs, automate repetitive tasks, and help coders focus on creativity and problem-solving.
In August 2024, the company raised $150 million in Series C funding and reached a valuation of $1.25 billion.
The company’s growth (and indeed potential) is the result of identifying a key gap in the market. Specifically, that coders were still struggling with tedious tasks despite the influx of generative AI tools for other purposes.
Music and Art
24 – Suno
Year founded: 2022
Location: Cambridge, Massachusetts, USA
What they do
Suno democratizes music creation by enabling users to generate original songs through simple text prompts. The startup’s platform utilizes advanced machine learning models trained on diverse musical data to compose unique tracks across various genres and styles.
Suno’s was founded by a team whose members previously worked at Meta, TikTok, and Kensho and came out of stealth in December 2023. It was also around this time that Suno was incorporated into Microsoft’s AI software platform Copilot.
The startup has attracted a significant amount of funding in the months since, with a $125 million Series B round in June 2024 the highest.
Adjacent Industries
Autonomous Transportation
25 – Waymo
Year founded: 2009
Location: Mountain View, California, USA
What they do
Waymo—which started life as the Google Self-Driving Car Project—develops autonomous driving technology aimed at enhancing transportation safety and efficiency.
The startup’s Waymo Driver system combines sensors and machine learning to enable vehicles to navigate real-world environments without human intervention.
After years of setbacks, Waymo is poised for massive growth. It secured $5.6 billion in funding to be worth over $45 billion in November 2024, with the capital used to expand the Waymo-One robotaxi service and an existing partnership with Uber.
26 – Aurora Innovation
Year founded: 2017
Location: Pittsburgh, Pennsylvania, USA
What they do
Aurora Innovation is the developer of Aurora Driver—a self-driving system designed to operate multiple vehicle types, from freight-hauling trucks to ride-hailing passenger vehicles.
With a suite of self-driving hardware, software, and data services, Aurora aims to make transportation safer and more efficient.
In July 2023, the startup raised approximately $820 million through a public offering and private placement, bolstering its financial position to support the commercial launch of its autonomous trucks.
Biology and Healthcare
27 – Freenome
Year founded: 2014
Location: South San Francisco, California, USA
What they do
Freenome is at the forefront of early cancer detection, developing blood tests that identify cancer in its initial stages.
Freenome’s multi-faceted approach employs machine learning to analyze data to detect cancer-related patterns. This approach aims to make routine screenings more accessible and less invasive.
The startup has also developed a blood test for early detection of colorectal cancer—the world’s second deadliest cancer that claims over 50,000 lives each year in the United States alone.
In February 2024, Freenome raised $254 million in a round led by pharmaceutical giant Roche.
28 – Abridge
Year founded: 2018
Location: Pittsburgh, Pennsylvania, USA
What they do
Abridge offers a generative AI solution for clinical conversations.
Their platform records and transcribes medical conversations, organizes the information into electronic health records (EHRs) and reduces administrative burdens for clinicians.
This innovation addresses physician burnout while also improving patient care and health outcomes.
Abridge is poised for growth in an industry known for inefficiencies in communication, services, and various clinical processes. In October 2024, it was reported that the company was seeking to raise $250 million from Elad Gill, VC firm Institutional Venture Partners, and Alphabet’s CapitalG growth fund.
This would see the healthcare AI startup valued at $2.5 billion—up from just $200 million in 2023.
29 – Memora Health
Year founded: 2017
Location: San Francisco, California, USA
What they do
Memora Health is transforming healthcare delivery by digitizing and automating complex care workflows.
Memora’s platform enables clinicians to focus on patient care by streamlining administrative tasks and providing patients with proactive, two-way communication. It can be used across various contexts such as cancer care, surgical care, chronic care management, and transitions of care.
Like Abridge, Memora strives to increase the likelihood of favorable patient outcomes while also reducing clinician burnout.
In April 2023, the startup announced a $30 million investment led by General Catalyst, with participation from Northwell Holdings and several major health systems.
Space Technology
30 – Planet Labs
Year founded: 2010
Location: San Francisco, California, USA
What they do
Planet Labs operates a fleet of Earth-imaging satellites that capture daily, high-resolution images of the planet. AI is then used to analyze the imagery and track changes that may reflect deforestation, urban development, and climate change, among other applications.
This enables industries like agriculture, forestry, and disaster response to make informed decisions based on ever-changing environmental conditions—including in real time.
Planet Labs’ ability to provide near-instant insight into global changes has positioned them as a key player in climate tech and geospatial intelligence.
After going public via a merger with dMY Technology Group in December 2021, Planet Labs reached a valuation of $2.8 billion. Future growth will be fuelled by the increased need for actionable, real-time climate and related data.
31 – SpaceX
Year founded: 2002
Location: El Segundo, California, USA
What they do
SpaceX is redefining space exploration with reusable rockets and autonomous spacecraft. AI plays a crucial role in its operations, powering the autopilot systems that guide Falcon 9 rockets during navigation and landing.
These AI-driven systems process real-time data to execute precision landings on drone ships and ground pads. AI also supports spacecraft management, analyzing satellite data to enhance mission planning and efficiency.
While SpaceX does not disclose its financial data, industry analysts believe the company is worth around $350 billion—an impressive increase over an initial estimate of $210 billion in early 2024.
When one considers that the space economy is predicted to grow to $1.8 trillion by 2035, there is potential the Elon Musk-led company will reach a higher valuation in the near future.
To conclude
These 31 rising AI startups showcase the future of artificial intelligence across hardware, software, and industry-specific applications.
From breakthroughs in AI chip technology to advancements in healthcare, transportation, and creativity, the impact of these forward-thinking companies is set to reshape industries, streamline workflows, and redefine the role of AI in everyday life.
Recap: In This Issue!
Convergence of Hardware and Software:
Startups like CoreWeave, Cerebras, and Nvidia demonstrate how AI hardware innovation is pivotal for enabling more efficient and scalable AI applications.
Simultaneously, software-focused companies like OpenAI, Anthropic, and Hugging Face are leveraging this infrastructure to push the boundaries of AI capabilities, especially in reasoning, creativity, and real-time applications.
Agentic and Autonomous Capabilities:
Companies such as Imbue, Adept AI, and /dev/agents are focusing on AI agents that can independently perform complex reasoning and task execution, moving beyond simple automation to proactive problem-solving and decision-making.
This trend is a step toward realizing fully autonomous systems in various domains like customer service (Sierra) and enterprise workflows (Moveworks, Cognition Labs).
Domain-Specific Innovations:
Many startups are targeting specific verticals to solve niche problems, such as:
Healthcare: Freenome and Abridge address early diagnosis and administrative burdens.
Legal: Harvey and Evisort streamline contract management and legal research.
Transportation: Waymo and Aurora focus on autonomous driving solutions.
This highlights a trend toward tailored AI solutions for high-value, complex industries.
Democratization and Accessibility:
Companies like Mistral AI, Hugging Face, and Uizard aim to make advanced AI tools and models more accessible through open-source platforms, affordable pricing, and user-friendly interfaces. This fosters broader adoption across industries and skill levels.
Cross-Industry Applications:
AI startups are increasingly integrating their technologies across multiple industries:
Planet Labs and SpaceX AI bring AI to climate monitoring and space exploration.
Databricks and Arthur AI apply advanced analytics to enterprise data management, emphasizing the cross-sector relevance of AI.
Focus on AI Safety and Alignment:
Startups like Anthropic and Arthur AI emphasize ensuring that AI models operate reliably, ethically, and transparently. This focus is critical as regulatory scrutiny of AI systems intensifies.
Expansion of Generative AI Beyond Text:
Startups like Suno (music generation) and DeepL (translation and writing enhancement) demonstrate how generative AI is moving beyond text into domains like music, design, and visual creativity.
Rapid Infrastructure Growth and Scaling:
Companies like CoreWeave and Vultr highlight the growing demand for AI cloud infrastructure, which is essential for scaling AI applications. This is further evidenced by massive investments in GPU clusters and data centers.
Real-Time and Contextual AI:
Startups like Perplexity AI and Cognition Labs are advancing AI systems that provide real-time, context-aware insights and solutions, catering to dynamic environments like enterprise workflows and consumer search.
Collaborative and Ecosystem-Oriented Models:
Platforms like Hugging Face and LangChain promote collaboration by enabling developers to build on shared tools and frameworks, accelerating innovation within the AI community.
With massive ♥️ Gennaro Cuofano, The Business Engineer