4 Notable Funding Rounds on June 4, 2025

On June 4, 2025, a series of notable funding rounds took place across various sectors. These include Bolttech, an InsurTech firm aiming to streamline existing markets; Rosebud, which is challenging the AI-powered self-improvement app market; Thunder Code, an African generative AI startup; and TAE Technologies, which is raising capital at the forefront of clean energy. Each of these companies is taking an approach different from existing players in their respective fields, holding the potential to influence future market growth. This article discusses the background, funding amounts, and investor composition of each company's round, while also examining their business model characteristics, competitive landscape, and market impact.

1. Bolttech's Funding and the Embedded Insurance Market

1-1. Company Overview and Business Model

Bolttech (Singapore) is an InsurTech startup that provides a platform connecting insurance companies with product distributors to embed "insurance" into the customer purchase experience (Embedded Insurance). Founded in 2020, its co-founders are Eric Gewirtzman and insurance industry veteran Rob Schimek. By adopting a B2B2C model and presenting appropriate insurance options at the right time for each product, they aim for that "moment when a customer won't regret spending an extra dollar."

With the global advancement of e-commerce, attention is shifting toward business models like Bolttech's, where technology companies handle the "last mile" of insurance delivery rather than traditional insurance companies attempting digital transformation on their own. Currently, they connect approximately 700 distribution partners with over 230 insurance companies, supporting more than 6,500 products globally.

1-2. Series C Details and Investor Composition

On June 3, 2025, Bolttech raised $147 million in a Series C round, bringing its post-money valuation to approximately $2.1 billion. This follows the first close of the Series C round (approximately $100 million) in December 2024, making this an extension of that round. Key lead investors include the following:

• Dragon Fund

• Baillie Gifford

• Generali

• Sumitomo Corporation (Japan)

• Iberis Capital (Portuguese investment firm)

• Existing investors such as Tokio Marine and MetLife (insurance-affiliated)

According to Bolttech, based on the belief that "in a world with a growing protection gap, the industry can provide insurance to more customers by working together" (Rob Schimek), they emphasize a stance of expanding the market while engaging in "coopetition" with competitors.

1-3. Market Trends and Outlook

• Background of Embedded Insurance Growth
  Traditionally, insurance was often purchased separately. However, if insurance can be automatically suggested and purchased at the exact moment just before payment—such as when buying home appliances or booking travel—it significantly reduces customer effort. Bolttech argues that by refining the technology to "show the right insurance at the right time," they can increase insurance penetration rates.

• Merger and Partnership Trends
  Simultaneously with the Series C, they announced a joint venture with Sumitomo Corporation, planning to provide Embedded Insurance products and end-to-end services for the Asian market. This could lead to a rapid expansion of "insurance embedded in the purchase experience" using Bolttech's technology across Asian countries, including Japan.

• Metric Trends
  While Bolttech handled approximately $55 billion in annual premiums as of 2022, they announced that as of April 2025, they are covering approximately $60 billion in annual premiums. Although the number of distribution partners and insurance companies has not changed significantly since the Series B (as of 2022), the fact that the total amount of premiums handled has increased by approximately 9% year-over-year is noteworthy.

• Competitive Landscape
  In the Embedded Insurance space, venture companies such as Qover (Belgium), Neat (UK), and Synctera (US) are also emerging. While Bolttech positions both traditional insurance companies and technology ventures as competitors, it emphasizes the aforementioned "coopetition." With the mission of closing the protection gap, they aim to expand the market through partner companies.

2. Rosebud's Funding and the AI Journaling Market

2-1. Service Overview and Growth Background

Rosebud is an AI-powered journaling app designed to support "self-reflection" and "personal growth." The AI analyzes the text recorded by users and provides appropriate questions and insights based on over 1 billion words of communication data. Specifically, it compares entries with past records to extract "trends" and provides feedback that encourages behavioral change and goal achievement.
Founded in 2023, the founders are Chrys Bader (a Y Combinator alumnus and former co-founder of Secret) and Sean Dadashi (a UC Berkeley Cognitive Science graduate). Both have a strong interest in mentoring and coaching, aiming to support users while ensuring psychological safety.

2-2. Seed Funding Utilization Plan and Investors

In June 2025, Rosebud closed a $6 million seed round. The lead investor was Bessemer Venture Partners, with participation from 776, Initialized Capital, Fuel Capital, Avenir, Tim Ferriss, and others.

• Funding Amount: $6 million

• Key Investors: Bessemer Venture Partners / 776 (a fund managed by Reddit co-founder Ajit Nagarathnam and others) / Initialized Capital / Fuel Capital / Avenir / Tim Ferriss (notable investor/entrepreneur), and others.

Use of Funds is as follows.

1. Strengthening Engineering/Product Talent: Currently, the core team consists of 4 people, including the 2 founders. With this funding, they will hire several engineers to accelerate app improvements and feature additions.

2. Marketing Investment: Plans include strengthening advertising and partnerships to acquire users.

3. Investment in Proprietary Memory Technology: Focusing on the development of a "long-term memory function" that accumulates and utilizes the user's past data over time, rather than just being a simple chatbot.

4. Channel Expansion: Exploring partnerships with academic institutions, companies, clinics, etc., with an eye toward a B2B2C model.

2-3. Expectations as a Mentoring AI and Competitive Landscape

Rosebud explicitly states, "We are not aiming to replace therapists, but rather to lower the barrier to self-coaching." Chrys Bader said the following in an interview with TechCrunch:

In other words, its major advantage is the ability to freely change feedback methods according to the user's personality and situation, unlike conventional uniform chatbots. Currently, a total of over 500 million words have been entered into journals, and user time spent has exceeded 30 million minutes. Given that this level of engagement has been achieved in less than two years since launch, it can be said that there is a definite need.

• Competitive Landscape
  The AI journaling market is still in its infancy, but there are many apps in the US like Reflectly, Journey, and Day One that digitize analog recording methods. On the other hand, Rosebud is differentiated by its focus on "personal mentoring" features with AI at its core. While it is sometimes mentioned alongside Woebot and Replika, which apply AI to psychological counseling and mental health, Rosebud's strength lies in its focus on record-based self-exploration.

3. Thunder Code and African Generative AI Startups

3-1. Founding Background and Lessons from Expensya

The African startup Thunder Code raised $9 million in seed funding in May 2025, just six months after its founding. The founders are Karim Jouini and Jihed Othmani. They previously launched the expense management SaaS "Expensya" based in France and Tunisia, which was sold to Sweden's Medius in 2023 for approximately $120 million. Through this experience, they said that while they felt the difficulty of starting a business and the challenges of fundraising, they were driven by the urge to start a business again.

Jouini stated the following:

His experience with technical integration at Medius, which already spans multiple countries, became the source of his own idea for "Generative AI x Software Testing." He says he was convinced that "test automation" is a common pain point for every product and that it could be significantly streamlined by using AI.

3-2. Product Features and Market Opportunities

The core product of Thunder Code is one where AI agents mimic human testers to detect and report UI/UX bugs. Specifically, it has the following features:

1. Automated testing by AI agents: AI automatically generates and executes test scenarios for web applications. Unlike traditional code-based automated testing (e.g., Selenium, Tricentis, etc.), it can simulate UI operations and experiences from a "human perspective."

2. Rapid MVP development and market validation: The first MVP was released in just six weeks, and features have been significantly enhanced over the following six months. In contrast to the multi-year development phase of the Expensya era, the company is thoroughly committed to product creation that prioritizes speed above all else.

3. Multilingual/Multi-location support: The headquarters is in Paris, and the office is in Tunis. Starting with web app testing, the company plans to expand to mobile, desktop, and API testing by the end of 2025.

According to reports from research firms, the software testing market is projected to reach $100 billion by 2027, and the majority of that market relies on traditional code-based automation. Platforms utilizing generative AI are still new, and they can be an attractive solution for companies with strong needs to "get fast feedback" and "increase scenario coverage."

3-3. Significance of Funding and Future Strategy

The following have participated in this $9 million round:

• Silicon Badia, Janngo Capital (both have provided continuous support since the Expensya era)

• Titan Seed Fund

• Roxanne Varza (Director of Station F)

• Karim Beguir (CEO of Instadeep, one of Africa's largest AI startups)

• Former and current employees of Expensya

Jouini states, "We want to allocate significant capital to talented people at an early stage. Many African entrepreneurs fear equity dilution, but to create a unicorn, you should secure top talent early." This can be considered a strategy based on the current situation where the competition for top engineers and data scientists is intensifying in AI startups.

• Competitive Landscape
  In the web app testing domain, there are various players of all sizes, such as UIPath (mainly RPA), BrowserStack (cloud-based testing environment), Jetify, and Nova AI. However, Thunder Code differentiates itself by specializing in "test scenario creation using generative AI agents." Additionally, by selling the benefit of rapid feedback across multiple languages and locations, they have already acquired pilot users in the US, Canada, France, and Tunisia.

• Future Plans
  The company plans to officially launch mobile, desktop, and API testing by the end of 2025, expanding the customer base from web testers to the entire development team. Furthermore, by adding features that cover "predicting causes when failures occur" and "quality assurance before release" through AI analysis of test results, they aim to become a full-stack testing solution.

4. TAE Technologies's Funding and the Forefront of Fusion Energy Development

4-1. Company Overview and Progress in Technology Development

TAE Technologies (formerly Tri Alpha Energy) is a veteran company that has been aiming to realize a "next-generation fusion reactor" since the 1990s, having raised approximately $1.8 billion to date. In the latest round announced in June 2025, it secured $150 million, led by existing investors Google, Chevron, and New Enterprise Associates. With this latest funding, the company has reached a cumulative total of nearly $2 billion.

TAE previously initiated reactions by colliding two plasma balls (anode and cathode), but in April 2025, it demonstrated a "technology capable of generating, heating, and stabilizing plasma using only particle beams." This enables a reduction in device size and cost, making the path to a commercial machine clearer.

4-2. Collaboration with Google and AI Utilization

Since 2014, TAE has been working with Google on "plasma optimization using machine learning." Previously, plasma optimization required about 1,000 experiments and took two months; after the introduction of AI, the same optimization process was achieved in just a few hours. "AI-based optimization has increased efficiency by more than two orders of magnitude and contributed to a significant reduction in experimental costs," TAE CEO Michl Binderbauer said in a 2022 interview.

Google has participated in this round again, continuing to support the R&D structure centered on AI technology. Specifically, the following are anticipated:

1. Advancement of plasma generation and maintenance algorithms: Further stabilizing existing particle beam-only technology and aiming for long-term operation for commercial reactors.

2. Automation and analysis of experimental data collection: AI processes vast amounts of data obtained from various sensors in real-time, utilizing it for fine-tuning the device and predicting failures.

3. Cost model optimization: Simulating the cost structure required to realize a commercial reactor using AI, and using it as a basis for decision-making regarding funding and partner selection.

4-3. Future Funding Plans and Practical Outlook

TAE has set a roadmap to "supply electricity to the power grid with its first commercial reactor in the early 2030s." In addition to this $150 million round, Binderbauer mentioned the following:

This additional funding is expected to be used for the following:

• Construction costs for the final prototype: Device improvement and facility construction costs to complete the "final demo machine" that ensures the performance required at this stage.

• Scaling up AI optimization software: Infrastructure investment to transition plasma stabilization algorithms to a mass-production reactor level.

• Compliance with international regulations and safety standards: Certification process costs to clear legal regulations regarding fusion reactors in various countries (especially the US, Europe, Japan, and Taiwan).

Furthermore, experiments have already succeeded in reaching a plasma temperature of 70 million degrees Celsius, and ultimately, reaching "1 billion degrees Celsius" is considered the milestone for a commercial reactor. If successful, it will increase the reaction efficiency of fusion fuel (deuterium and tritium) and enable sustainable power generation, potentially triggering a paradigm shift in clean energy.

As described above, the funding news for the first half of 2025 tells the story of accelerating innovation across a wide range of fields, including InsurTech, self-care AI, generative AI, and clean energy. The vision depicted by each company shares a common message of "significantly improving existing mechanisms and creating new market opportunities," holding the potential to drive the transformation of future industrial structures and social infrastructure.

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