Climatiq uses AI to automate carbon emission data. See the pitch deck it used to raise $11.6 million.
Berlin startup Climatiq raised a $11.6 million Series A led by Alstin Capital.
Climatiq's AI platform automates carbon emissions data for companies.
BI got a look at the 11-slide pitch deck used to secure the fresh funding.
Climatiq, a startup that's built an AI-enabled platform for companies to collect and automate their carbon emission data, has secured a $11.6 million Series A led by Alstin Capital.
The Berlin startup's tool analyzes everything from supply chain data to purchase orders to calculate a company's scope 3 emissions, which measure its indirect carbon footprint.
"If you're building any other kind of software, there are existing APIs — but not for carbon emissions. So we've built an infrastructure for carbon tooling," Climatiq's cofounder and CEO, Hessam Lavi, told Business Insider in an interview.
Scope 3 emissions, which typically represent around 90% of a company's carbon footprint, are often hard to reliably measure because they are collated from a fragmented set of data points. Climatiq's AI platform automates the collection of this data from various sources, such as NGOs, the Intergovernmental Panel on Climate Change, and universities.
These carbon metrics can then be integrated into companies' emissions reports.
"There's going to be a need for a trusted source on carbon data. If everyone is reporting data, how do you have confidence in their methodology? That got us interested in building an infrastructure platform for carbon accounting," Lavi said.
Some companies in the US and Europe are required to calculate their emissions data to ensure they're complying with ESG regulations. Climatiq charges clients, which include the likes of Celonis and Siemens, based on their usage.
Lavi gave the example of feeding the transport records of a freight company into its platform. "We process it, and provide a carbon estimate to our partners — and charge for that API request," Lavi added.
President Donald Trump's second term has triggered a wave of backlash against ESG incentives, which has had a knock-on effect on climate startups. In Q1, VC funding into climate tech dried up 50% year-on-year, per PitchBook data, and high-profile climate startups such as Climeworks have announced layoffs in 2025.
Amid this environment, Lavi found the fundraising process considerably more difficult than Climatiq's $5.8 million seed in 2022.
"It was much tougher than I expected. Compared to our pre-seed and seed, it's definitely a different chaos," he told BI, adding that the startup spoke to around 70 VCs for this funding round.
The Series A was led by Munich-based venture capital firm Alstin Capital, with backing from Singular and Cherry Ventures.
With the cash injection, Climatiq plans to grow its engineering head count and develop its AI product.
We got a look at the 11-slide deck used to secure the fresh funds.
Read the original article on Business Insider
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Forbes
10 minutes ago
- Forbes
Why Companies Need To Institute Stricter AI Policies
As the hype grows around AI and more people try it out, many are using it at work to see how it can help them become more efficient. But there's a real problem: Some employees are using public instances of chatbots, putting proprietary company data at risk by giving an open LLM access. Others use the company's access to AI, but input highly sensitive and personal data, like Social Security numbers and financial data. A new study from technology security company Kiteworks found that 27% of companies reported that nearly a third of all of the data sent to AI systems is the type of information that should be kept private, like company records, employee information and trade secrets. (It could be more; 17% of companies don't know how much private data ends up getting sent to AI.) It's a problem that's growing. A Stanford University report on AI found a 56.4% increase in security incidents with the technology last year. While it may seem obvious to the tech savvy, many employees might not know the risks of this kind of AI sharing, and 83% of companies only rely on training or warning emails to let them know. Kiteworks found that just 17% have automatic controls that keep employees from uploading sensitive information to public AI tools. Further, most companies don't have much of an AI governance structure—only 9%, according to Deloitte research cited by Kiteworks. The study results show that companies need to add policies and infrastructure to control employee use of AI and protect their own data. This kind of use can cause real damage to companies—not to mention their employees and clients. The study concludes that companies need to acknowledge the threat, deploy controls that can be verified, and ensure that they can stand up to regulatory scrutiny. 'With incidents surging, zero-day attacks targeting the security infrastructure itself, and the vast majority lacking real visibility or control, the window for implementing meaningful protections is rapidly closing,' Kiteworks CMO Tim Freestone said in a statement. Many people still haven't grasped how to truly use AI to benefit their company—we all know its practical business functions go beyond asking a chatbot for advice. I talked to Lindsay Phillips, cofounder and COO of tech change coaching firm SkyPhi Studios, about how to bring AI to your company and get people using it. An excerpt from our conversation is later in this newsletter. This is the published version of Forbes' CIO newsletter, which offers the latest news for chief innovation officers and other technology-focused leaders. Click here to get it delivered to your inbox every Thursday. STOCK MARKET NEWS Nvidia founder and CEO Jensen Huang speaks at the VivaTech technology startup and innovation fair in Paris earlier this month. Mustafa Yalcin/Anadolu via Getty Images Nvidia is back on top, pulling ahead of Microsoft as the world's most valuable company. A research note on Wednesday from Loop Capital analyst Ananda Baruah raised his price target for Nvidia's stock from $175 to $250. Baruah wrote that Nvidia will lead the next 'Golden Wave' for generative AI, and will see 'stronger-than-anticipated demand.' The research note—as well as Nvidia's annual shareholder meeting, where CEO Jensen Huang laid out an optimistic view of the company's future—drove the company's stock to hit a record high of $154.43. While share prices dropped somewhat before markets closed, it was a banner day for the chips company. Chips and robotics company, that is. At the annual meeting, Nvidia positioned itself squarely in the robotics and physical industrial AI spaces. In the company's annual report, Huang wrote that so far this year, Nvidia has fundamentally transformed itself from a chip maker to a builder of infrastructure. While AI data centers will continue to be important, AI-powered robots in factories, hospitals, farms and cities will be what moves society forward in the not-so-distant future. 'We stopped thinking of ourselves as a chip company long ago,' Huang said at the meeting, according to CNBC. CYBERSECURITY An Iranian man stands in his apartment in Tehran, which was destroyed by Israeli attacks. Morteza Nikoubazl/NurPhoto via Getty Images While it seems for now that the physical conflict between Iran and Israel—which the U.S. inserted itself into by bombing Iranian nuclear facilities—is on hold, the war will likely still be bitterly fought online. Forbes' Thomas Brewster writes that Iran, which has a 'robust cyber apparatus' according to Middle East cybersecurity experts, is likely to launch disruptive attacks on U.S. and Israeli interests. For the U.S. government, this could be especially challenging. Since the start of President Donald Trump's second term, the Department of Homeland Security's Cybersecurity and Infrastructure Agency has lost many experienced employees and does not even have a permanent director. Insiders told Forbes that CISA already is stretched thin, but coordinated attacks from Iran could make it much worse. The PR war over how the attacks are seen is also riddled with conflicting imagery. AI-generated Iranian propaganda showing a rocket launch and a convoy of tanks and missiles have racked up millions of views, writes Forbes' Emily Baker-White. These videos, which were seen throughout social media, abruptly disappeared. None of the platforms have any policies against releasing propaganda, and the videos didn't appear to be labeled as AI-generated. NOTABLE NEWS getty AI can be a force for good, but it can also be nefarious. New research from Barracuda, Columbia University and the University of Chicago found that AI writes more than half of all spam email now, writes Forbes senior contributor Davey Winder. This includes the vast majority of messages in your personal account's spam folder—but it's also getting prevalent in business emails as well. About 14% of business inbox attacks, in which often senior people in organizations are targeted with requests for financial transactions, are written by AI. Winder writes that it makes sense to use AI for spam. It tends to do a passable job of writing with proper grammar and spelling across a variety of languages. It can also write in a convincing way to provoke a recipient to respond. The study found that attackers seem to be using AI to draft different versions of spam and hacking emails, searching for the best way to get a recipient's attention. BITS + BYTES How To Get Your Company To Use AI To Its Full Potential SkyPhi Studios cofounder and COO Lindsay Phillips. SkyPhi Studios AI truly can transform the way we do business, but in order for it to make a difference, employees actually need to use it. AI is unlike any other tech shift in recent years, and it can be difficult for everyone at a company to embrace it. I talked to Lindsay Phillips, cofounder and COO of tech change coaching firm SkyPhi Studios, about the best way to get your employees through these challenges. This conversation has been edited for length, clarity and continuity. What is the biggest hurdle that you see to widespread AI adoption in companies? Phillips: The biggest hurdle is companies approaching AI as a software shift, and AI is really a mindset shift. It's not just about teaching people how to do the same work in a different tool. They have to completely change how they think about work, how they think about the value that they're bringing to the workplace, how they approach their workflows. Companies that are just trying to make tools available and don't help people understand how to use it, how to adopt it successfully and how to integrate it, are running into adoption challenges. How do you get past that roadblock? Understanding how you want people to change to use the tool. Understanding how roles and responsibilities need to change, the RACI [responsibility matrix] that's required so that folks adopt this tool and integrate it into their workflows. You want to also make sure that leadership across the org understands that strategy. Most folks want to get guidance from their manager, so you want to leverage leadership cascades and really make sure they're carrying that message forward and reinforcing it. The other thing that we're seeing with companies that are successful is a community of practice: Creating ambassadors throughout the org, at the ground level, boots on the street, that are supporting their team members and adopting these tools and helping them make that mindset shift. How does the move toward AI compare to other technology shifts in the past, like moving to the cloud and increasing cybersecurity? It definitely feels like we're driving the car while we're building the car, so we need our team members to be very collaborative in helping us figure out how to use these tools. Experts are going to be able to tell you how AI is going to be able to make their jobs more productive and be able to help them do their work better. Leadership's not necessarily going to know that, so it really does need to be a lot more collaborative and agile than it needed to be in the past. In the past, you find requirements, you help people adopt those new ways of working, you meet those requirements. This we're figuring it out as we go, and it's much more experimental. What sets the companies that are most successfully integrating AI apart? A comfort with experimentation and a certain amount of comfort with uncertainty of saying, 'We're going to give it a try. We're going to see how it goes, and we'll pivot as we need to.' Companies that are very attached to clarity and certainty and always having the right answer are going to struggle with AI adoption. It's not a linear straight path. It is going to be something you have to figure out as you go. What advice would you give to executives that are trying to get their employees to use AI? The more accessible we can make it, the better. There's companies doing weekly challenges. Just start to encourage your folks to incorporate it into their daily lives. Encourage folks to share wins. You want to hear about how other people are using these tools so that it can give you ideas of how you can also use it in your day-to-day. It is a massive mindset shift. Approach it with little tiny bites that you can take to start to shift habits daily. COMINGS + GOINGS Defense contractor Lockheed Martin appointed Dr. Craig Martell as its new vice president and chief technology officer, effective June 23. Martell previously worked as chief AI officer for Cohesity, and as the first chief digital and AI officer for the U.S. Department of Defense prior to that. appointed as its new vice president and chief technology officer, effective June 23. Martell previously worked as chief AI officer for Cohesity, and as the first chief digital and AI officer for the U.S. Department of Defense prior to that. Convenience store chain Love's Travel Stops hired Tim Langley-Hawthorne as chief technology officer, effective June 23. Langley-Hawthorne steps into the role after working as Hertz's executive vice president and chief information officer. hired as chief technology officer, effective June 23. Langley-Hawthorne steps into the role after working as Hertz's executive vice president and chief information officer. Newspaper chain Gannett selected Joe Miranda for its chief technology and data officer role, effective June 23. Miranda joins the firm after working as executive vice president and chief digital and technology officer of Herbalife, and has also held leadership roles at Thomson Reuters and Voya Financial. STRATEGIES + ADVICE As more companies adopt enterprise AI packages, several trends in what they are using and how are coming to the surface. Here are 10 trends that are shaping enterprise LLM use today. While part of business advancement today is all about personal branding and showing the world your expertise and strategic viewpoint, you may feel more comfortable quietly sitting in front of a screen. The good news is that you don't have to be an extrovert. Here are some tips for shy people who want to build personal brands. QUIZ After Meta's deal to take a 49% stake in data-labeling company Scale AI, another company with a very different main business stepped up as a potential giant in data labeling. Which company is it? A. Priceline B. Uber C. Instacart D. Electronic Arts See if you got the answer right here.
TechCrunch
12 minutes ago
- TechCrunch
Elon Musk reportedly fires Tesla's top sales exec
Omead Afshar, Tesla's vice president in charge of sales and manufacturing in North America and Europe, has reportedly been fired by CEO Elon Musk, according to Forbes. It's not immediately known why Musk fired Afshar, who was one of his top lieutenants and closest confidants at the company. Afshar, Musk, and Tesla did not respond to requests for comment. Afshar's departure was first reported by Bloomberg News. Afshar was posting support for the limited rollout of Tesla's robotaxi service in Austin, Texas, as recently as Tuesday. 'Absolutely historic day for Tesla,' he wrote on June 23 on X, the social media platform his former boss owns. 'Thank you, Elon, for pushing us all!' Afshar's departure comes at a time when the company's sales growth has vanished. Tesla sold fewer cars in 2024 than it did in 2023, the first annual drop since it started mass producing EVs more than a decade ago. Musk's involvement in U.S. politics has not helped, despite his recent pledge that he was leaving the Trump administration. Sales continued to struggle through the first half of 2025. The company's industry-leading profits fell 71% year-over-year in the first quarter. European sales fell nearly 28% percent year-over-year in May. Tesla will report global delivery figures for the second quarter next week, and financial results for the period in mid-July. Afshar was not a particularly public-facing executive at Tesla. He joined the company in 2017 and spent years working in the 'office of the CEO.' He took on increasing responsibilities ever since; Musk has previously credited Afshar with leading the construction of Tesla's massive factory in Austin, Texas. Not long after that, though, Afshar found himself in hot water. In 2022 he became a subject of an internal probe after he was allegedly involved in a plan to purchase special material for a glass building Musk reportedly wanted. Both the Department of Justice and the Securities and Exchange Commission began investigating those purchases in 2023. Techcrunch event Save $200+ on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Save $200+ on your TechCrunch All Stage pass Build smarter. Scale faster. Connect deeper. Join visionaries from Precursor Ventures, NEA, Index Ventures, Underscore VC, and beyond for a day packed with strategies, workshops, and meaningful connections. Boston, MA | REGISTER NOW Afshar moved over to SpaceX during some of that time period and reportedly was involved with X for a while. Musk elevated him to the role of vice president in late 2024 after another top executive, Tom Zhu, moved back to China. Bloomberg News also reported Thursday that Tesla's director of HR for North America, Jenna Ferrua, is no longer with the company. She did not immediately respond to a request for comment.
Forbes
24 minutes ago
- Forbes
A Quadruple Bottom Line. Can ProSocial AI influence Business For Good?
Pink 3d number 4 on mint background. 3D rendering. Best for anniversary, birthday party, ... More celebration. getty In boardrooms and beyond an interesting shift has begun to reshape how some enterprises measure success. The traditional singular focus on profit is evolving into a more nuanced framework that balances four dimensions: people, planet, profit and purpose — the quadruple bottom line . At the intersection of this trend lies an emerging paradigm of artificial intelligence designed not just to optimize efficiency, but to optimize for humanity itself. This transformation is still in its early stages. While the potential is compelling and early experiments show promise, the widespread adoption of ProSocial AI and quadruple bottom line thinking remains more of an aspiration than a reality across most industries. What we are witnessing are pioneering initiatives and foundational work being laid by forward-thinking institutions and entrepreneurs who recognize that the future of business may depend on getting this balance right. The quadruple bottom line concept evolves from the " Triple Bottom Line " (people, planet, profit) coined by John Elkington in 1994. It adds a fourth 'P': Purpose, recognizing that sustainable business success requires intentional alignment between technological innovation and human flourishing. While the triple bottom line prompted firms to consider their environmental and social impacts, purpose introduces a deeper sense of mission that transcends quarterly earnings and has the potential to inspire staff and customers. This evolution is particularly relevant as AI becomes more integrated into business operations. Rather than viewing AI as merely a tool for efficiency and effectiveness, a small but growing number of organizations are exploring its potential as an instrument for social good.. ProSocial AI represents a shift from the traditional take on technology as an endeavor that is driven primarily by commercial interests. It refers to AI systems that are deliberately tailored, trained, and targeted to bring out the best in and for people and planet. Unlike conventional AI that optimizes for narrow metrics, ProSocial AI is architected with human welfare and environmental sustainability as primary objectives, not afterthoughts. The distinction is important. Classic AI might optimize a supply chain for cost efficiency alone, potentially at the expense of worker welfare or environmental impact. In contrast, ProSocial AI would optimize for a holistic outcome that treats supply chain resilience, fair labor practices, environmental sustainability, and profitability as interconnected objectives. Real-World Applications: ProSocial AI In Practice Brewing Social Impact Win Win Coffee exemplifies the ProSocial AI approach by combining a social mission with technology. The company aims to "bring equity to the coffee supply chain, centering the African diaspora." This mission is powered by its technology platform, ViaNexa, which uses AI and machine learning to remove bottlenecks and waste from the coffee supply chain. It leverages AI to implement dynamic pricing models, ensuring fairer compensation for farmers and more efficient, transparent transactions. This direct link between a consumer-facing brand and its purpose-built AI platform demonstrates a cohesive quadruple bottom line strategy in action, though its market share remains small compared to industry giants (for now). Intelligent Procurement with Purpose Stimulus represents an interesting example of ProSocial AI in a B2B context. Its AI-powered "relationship intelligence platform" helps companies make optimal purchasing decisions by factoring in a wide array of metrics beyond cost. Stimulus's algorithms analyze and score suppliers based on diversity, sustainability, and ethical practices, enabling companies to build supply chains that reflect their values while maintaining a competitive edge. Financial Inclusion Through AI Some established fintech companies are also leveraging AI for social good. For example PayPal uses machine learning to assess creditworthiness for small businesses, particularly in underserved communities that traditional banks might overlook. By analyzing business performance data rather than relying solely on conventional credit scores, PayPal can provide capital to a broader range of entrepreneurs. During economic uncertainty, its AI systems can also help identify businesses at risk and proactively offer support, demonstrating how profit-driven companies can simultaneously drive positive social impact. Challenges To Widespread Prosocial AI Adoption Despite these promising examples, developing integrated systems remains technically challenging, as most current AI implementations still optimize for traditional business metrics. Selected factors hindering the widespread adoption of ProSocial AI: Measurement Complexity: Social and environmental impacts are often difficult to quantify and integrate into algorithms. (Often 'measure what we treasure' turns into 'treasure what we measure', as investors – and in the case of nonprofits – donors, cherish hard metrics.) Competitive Pressures: Companies may hesitate to adopt solutions that could increase short-term costs, even if they offer long-term benefits. Technical Hurdles: Balancing multiple, sometimes competing, objectives requires sophisticated AI capabilities that many organizations lack. Cultural Resistance: Shifting from a profit-maximizing mindset requires fundamental changes in organizational culture and incentives. The Systems Thinking Advantage What distinguishes prosocial AI is its foundation in systems thinking. Rather than optimizing individual components in isolation, these systems recognize the interconnectedness of social, environmental, and economic factors. For example, a traditional AI in customer service might optimize for the lowest cost and fastest resolution time. A prosocial AI logic optimizes for customer satisfaction, agent well-being, and long-term relationship building and planetary footprint, recognizing that the interplay of these factors ultimately drive sustainable profitability. The Economic Case For ProSocial AI While critics may argue that adding social and environmental considerations increases costs, emerging evidence suggests the opposite. Companies that integrate ProSocial AI principles tend to discover new revenue streams, reduce operational and regulatory risks, and build more resilient business models. Adopting a more holistic perspective to business does not represent a trade-off between profit and purpose;, but a more sophisticated understanding of how meaningful benefits can be generated and scaled. Done deliberately it is a win-win-win-win for the people we are, the institutions we are part of, the countries we belong to and the planet we depend on. Scaling Impact: The Institutional Imperative A transition to mainstream prosocial AI requires more than individual company initiatives; it demands systemic change. Universities, industry associations, and regulatory bodies must collaborate to create an environment where quadruple bottom line thinking becomes the norm. Programs like Wharton's executive education courses on responsible AI exemplify this approach, coupling technical proficiency with ethical reasoning. The Quadruple Bottom Line: The FOUR Framework To move from concept to reality, organizations can use the practical FOUR framework: F - Focus on Stakeholder Integration: Identify all stakeholders—employees, customers, communities, and environmental systems—and incorporate their perspectives into AI development. O - Optimize for Multiple Variables: Redesign success metrics to include social and environmental indicators alongside financial ones. U - Understand Through Measurement: Invest in robust systems to track social and environmental impact with the same rigor as traditional business metrics. R - Reflect and Adapt Continuously: Implement regular review processes to assess the real-world impact of ProSocial AI initiatives and create feedback loops for continuous improvement. A Call For Bottomline Intentionality The quadruple bottom line is a strategic necessity for businesses seeking to thrive in an increasingly hybrid and ever more interconnected world. As consumers, employees, and investors increasingly demand purpose-driven organizations, companies that master this integration will not just be doing good, but doing exceptionally well. Making the switch from purely pro-profit to a 4P-perspective makes businesses future-proof. It actually adds an additional 'P' - with prepared leadership as stressed by Wooten and James. Business schools can be champions of such an integrated approach, with examples like the Wharton AI Human Research Lab and the Wharton Accountable AI Lab which look at the intersection of intelligent technology, business strategy and human behavior, while addressing AI's ethical, regulatory and governance considerations. The transition will be gradual, driven by a combination of regulatory pressure, consumer demand and proven competitive advantage. Ultimately the future belongs to organizations that recognize technology's power to amplify human potential, strengthen communities and nurture the planet. In this future, the quadruple bottom line is not just a measurement framework. It is a pathway to shared prosperity. It's time to start walking, prosocial AI can accelerate our pace.
