Kindo, a Venice Beach, California-based company, recently announced that it has secured $20.6 million in funding. The funding round was led by Drive Capital, with participation from existing investors including RRE Ventures, Marlinspike Partners, Riot Ventures, Eniac Ventures, New Era Ventures, and Sunset Ventures. Additionally, Kindo has acquired WhiteRabbitNeo, an open-source security project.
Ron Williams, CEO of Kindo, shared that the company was started to help enterprises adopt and manage AI technologies, including generative AI. The latest funding round, led by Drive Capital, brings Kindo’s total funding to $27.6 million.
Investor Name | Role |
---|---|
Drive Capital | Lead Investor |
RRE Ventures | Existing Investor |
Marlinspike Partners | Existing Investor |
Riot Ventures | Existing Investor |
Eniac Ventures | Existing Investor |
New Era Ventures | Existing Investor |
Sunset Ventures | Existing Investor |
Drive Capital’s Managing Partner, Chris Olsen, emphasized the critical need for AI security in the enterprise market and highlighted Kindo’s innovative approach. Olsen believes Kindo is poised to become an essential partner for enterprises navigating the complex landscape of AI security and governance.
Founded in October 2022 by Ron Williams, former CTO of Subspace, Kindo focuses on providing a secure platform for enterprises to integrate and manage various AI capabilities. Kindo aims to simplify the process for enterprises to control access to AI models and data sources, ensuring centralized control.
Williams described Kindo as an orchestration platform that allows enterprises to integrate any AI capabilities or models available in the market. This includes their own models, with centralized control over who can access these models and what data sources they can interact with.
Kindo’s recent acquisition of WhiteRabbitNeo aims to enhance its AI security capabilities. WhiteRabbitNeo is an open-source cybersecurity AI model, created by Migel Tiserra. Tiserra will join Kindo as an advisor. The acquisition will allow Kindo to integrate WhiteRabbitNeo’s AI-powered security features into its platform, offering enterprises advanced security tools to identify and address vulnerabilities in their AI deployments.
Tiserra expressed excitement about the acquisition, noting that Kindo is serious about solving security challenges for enterprises. He highlighted that developers and security team members will now have access to state-of-the-art open-source cybersecurity models to test and secure their infrastructure.
The new capital will be used to accelerate product development and enhance Kindo’s AI security and management capabilities. This includes advanced research and development to stay ahead of evolving AI risks. Kindo also plans to expand its sales and marketing efforts and grow its team with top-tier talent in AI security and enterprise software.
Williams mentioned that Kindo aims to provide a centralized platform for CIOs to deploy and control any AI capability across their organization securely. The platform supports various AI models, including commercial, open-source, and private models. It offers use cases such as coding assistants, chatbots, and no-code AI agents.
Centralized AI Governance and Security Controls:
Kindo is designed to address the unique challenges faced by enterprises adopting AI technologies. These challenges include securing AI models against data leakage and adversarial attacks, ensuring compliance with AI regulations, managing shadow AI tools used by employees, and integrating AI tools with existing enterprise systems.
Williams emphasized the importance of centralized control for enterprises using multiple AI models. He noted that Kindo’s platform simplifies the process for IT and security leaders, allowing them to manage AI capabilities without needing AI experts within their organizations.
Kindo’s customer base includes publicly traded companies, leading consumer mobile application developers, and open-source software organizations. The company targets enterprises that use multiple AI models and need a centralized solution to manage and secure these capabilities.
Williams believes Kindo is ahead of the competition due to its focus on being an orchestration platform rather than a platform company that aims to own all applications. He noted that Kindo’s leaders bring credibility and experience, making it easier for companies to adopt their platform.
Kindo plans to continue supporting the open-source community and expanding the reach of its platform. The company aims to provide enterprises with the tools they need to leverage AI safely and responsibly, ensuring security and compliance while enabling innovation.
With its recent funding and acquisition of WhiteRabbitNeo, Kindo is well-positioned to address the growing demand for secure AI solutions in the enterprise market. Williams and his team are committed to building a platform that meets the evolving needs of enterprises as they navigate the complex landscape of AI adoption.
In summary, Kindo’s latest funding round and strategic acquisition mark significant milestones in the company’s mission to provide secure AI solutions for enterprises. By integrating advanced security features and expanding its platform capabilities, Kindo aims to become a trusted partner for enterprises seeking to leverage AI technologies safely and effectively.
Alphabet, Google’s parent company, is reportedly in advanced negotiations to acquire Wiz, a cybersecurity startup, for $23 billion. This information comes from a person close to the company who shared details with TechCrunch. The potential deal was initially reported by The Wall Street Journal.
Wiz, founded in 2020, has experienced phenomenal growth since its inception. The company was approached a few weeks ago by Thomas Kurian, the head of Google’s cloud division, according to the source. Following this initial approach, negotiations have moved swiftly, and the two parties have tentatively agreed on the purchase price.
The source mentioned that a deal of this size faces numerous hurdles and details that need to be sorted out, although specifics were not provided. It is estimated that negotiations could take another week to 10 days, with a 50% chance that the deal might fall apart.
In May, Wiz achieved a private valuation of $12 billion after raising $1 billion in a Series E funding round. If the deal with Google goes through at $23 billion, it would more than double this valuation.
Below is a table summarizing Wiz’s financial milestones:
Financial Metric | Value |
---|---|
Last Private Valuation | $12 billion |
Series E Funding Raised | $1 billion |
Current Annual Recurring Revenue (ARR) | $500 million |
Projected ARR for Next Year | $1 billion |
Offered Purchase Price | $23 billion |
Valuation Multiple on Current ARR | 46 times |
Valuation Multiple on Projected ARR | 23 times |
Wiz’s exponential growth is a significant factor in Google’s interest. The startup has consistently outpaced its own growth targets, making it an attractive acquisition target. Despite its rapid growth, Wiz had planned to go public eventually, but not until after 2025. The company was not actively seeking a buyer when Google approached it.
The potential acquisition by Google Cloud is seen as beneficial for both parties. For Wiz, integrating with Google Cloud could provide substantial revenue synergies, potentially making it easier for Wiz to sell its products to Google’s vast customer base.
If the deal is finalized at $23 billion, Wiz would be valued at 46 times its current ARR and 23 times its projected 2025 ARR. For context, Wiz’s main competitor, Palo Alto Networks, is trading at just above 14 times its trailing 12 months revenue. Google appears willing to pay a nearly 300% premium compared to Wiz’s closest competitor.
Wiz has garnered substantial support from several high-profile investors, including:
These investors have backed Wiz through its various funding rounds, contributing to its rapid growth and significant market valuation.
While the proposed deal is promising, it’s important to note the complexities involved in closing a transaction of this magnitude. Regulatory approvals, integration challenges, and aligning strategic goals are just a few of the potential hurdles that could arise.
However, if successful, this acquisition would mark one of the largest deals in the cybersecurity sector. It would not only bolster Google Cloud’s security offerings but also position it strongly against competitors in the rapidly evolving cloud services market.
As the discussions progress, industry observers will be closely watching how this potential acquisition unfolds and its impact on the cybersecurity landscape.
In the era of artificial intelligence (AI), enterprises are eager to leverage large language models (LLMs) to optimize critical internal functions. Despite significant investments, achieving a substantial return on investment (ROI) remains a challenge. Today, New York-based startup Hebbia, which focuses on simplifying information retrieval through AI, announced it has secured $130 million in Series B funding from notable investors including Andreessen Horowitz, Index Ventures, Peter Thiel, and the venture capital arm of Google.
Hebbia is developing a straightforward yet powerful LLM-native productivity interface that streamlines the extraction of value from data, regardless of its type or size. The company is already collaborating with major financial services firms, including hedge funds and investment banks, and plans to extend its technology to more enterprises soon.
“AI is undoubtedly the most important technology of our lives. But technology doesn’t drive revolutions– products do. Hebbia is building the human layer – the product layer – to AI,” George Sivulka, the founder and CEO of Hebbia, stated in a blog post. Prior to this funding round, the company raised $31 million through several rounds.
While LLM-based chatbots can utilize internal documentation or be prompted with documents, they often fail to answer complex questions about business functions accurately. This can be due to limitations in the context window, which may not handle the size of the document provided, or the sheer complexity of the query itself. Such errors can erode teams’ confidence in the capabilities of language models.
Hebbia, founded in 2020, addresses these challenges with its LLM-linked agentic copilot called Matrix. This tool operates within the business environment of companies, enabling knowledge workers to pose intricate questions related to internal documents—ranging from PDFs and spreadsheets to audio transcripts—with an infinite context window.
The Matrix platform allows users to input queries and associated documents/files. The system then decomposes the prompt into smaller, manageable actions that the underlying LLM can execute. This process enables the platform to analyze all the information contained in the documents simultaneously and extract the necessary data in a structured format. Hebbia claims that its platform can process and reason over any volume (from millions to billions of documents) and modality of data, while also providing relevant citations to help users trace each action and understand the platform’s decision-making process.
“Designed for the knowledge worker, Hebbia lets you instruct AI agents to complete tasks exactly the way you do them – no task too complex, no dataset too large, and with the full flexibility and transparency of a spreadsheet (or a human analyst!),” Sivulka elaborated in the blog post.
Feature | Description |
---|---|
Infinite Context Window | Handles extensive data volumes, ideal for enterprises with vast documentation. |
Comprehensive Data Analysis | Processes various data formats simultaneously. |
Actionable Intelligence | Breaks down complex queries into manageable tasks for accurate results. |
Transparency and Traceability | Provides citations for every action, ensuring decision-making transparency. |
Versatility | Adapts to various industries, including financial services and beyond. |
Initially, Sivulka created the platform to streamline the workload of financial industry workers who spent substantial time sifting through documents for relevant information. Over the years, Hebbia has expanded its reach, gaining traction in other sectors as well. Currently, the company boasts over 1,000 use cases in production with several major enterprises, including CharlesBank, American Industrial Partners, Oak Hill Advisors, Center View Partners, Fisher Phillips, and the U.S. Air Force.
“Over the last 18 months, we grew revenue 15X, quintupled headcount, drove over 2% of OpenAI’s daily volume, and laid the groundwork for customers to redefine how they work,” Sivulka noted. It remains uncertain whether OpenAI is the sole model used within the Matrix platform or if users have the option to select other LLMs.
With the recent funding, Hebbia aims to build on its successes and attract more large enterprises to its platform, simplifying how their workers retrieve knowledge. “I’m excited for a world of unbound progress– one where AI agents contribute more to global GDP than every human employee. I believe that Hebbia is going to get us there,” Sivulka added, highlighting that the company is developing what he considers the most important software product of the next 100 years.
Despite its innovative approach, Hebbia is not alone in the AI-based knowledge retrieval space. Other companies are also exploring similar technologies. For instance, Glean, a Palo Alto-based startup, achieved unicorn status in 2022 and has developed a ChatGPT-like assistant specifically for workplace productivity. Additionally, Vectara is working on enabling generative AI experiences grounded in enterprise data.
Hebbia’s recent funding round and its expanding list of enterprise clients underscore its potential to significantly impact the field of AI-driven knowledge retrieval. As the company continues to innovate and enhance its platform, it is well-positioned to lead the market and drive substantial improvements in how businesses manage and utilize their data.
With its focus on creating practical, product-driven AI solutions, Hebbia is poised to help enterprises navigate the complexities of data management and retrieval, ultimately unlocking new levels of efficiency and productivity.
Synthflow, a Berlin-based startup, has announced a $7.4 million seed round to further develop its no-code AI voice assistance platform designed for small and medium-sized enterprises (SMEs). The company, which focuses on automating repetitive tasks for busy business owners, has raised a total of $9.1 million since its inception around spring last year, highlighting the increasing investor interest in generative AI applications.
Investor Confidence and Customer Growth
Synthflow has made significant strides since its launch, approaching 1,000 customers and boasting “double-digit” monthly growth rates since unveiling its browser-based no-code tool in December 2023. This rapid adoption suggests a strong demand among SMEs for generative AI tools that can enhance productivity through automation.
The latest funding will be dedicated to research and development, with CEO and co-founder Hakob Astabatsyan emphasizing the importance of maintaining the startup’s early momentum. “We have very many ideas. We know exactly what the customers need,” Astabatsyan told TechCrunch, indicating a clear vision for the future of AI in the SME sector.
The Founding Team
Astabatsyan, an ex-Rocket Internet entrepreneur, co-founded Synthflow with his brother Albert and Sassun Mirzakhan-Saky. Albert brings experience from a previous no-code startup, while Mirzakhan-Saky contributes his software engineering expertise as CTO. Together, they aim to make AI technology accessible to non-technical users, particularly SMEs.
Multi-Language Capabilities
Initially, Synthflow’s product focused on English-language call handling, catering to its largest markets. However, the startup has since introduced beta versions in German and French, signaling an expansion into European markets.
End-to-End Experience for SMEs
Synthflow’s no-code platform targets service industry SMEs, offering an end-to-end experience that automates core tasks like appointment scheduling. This allows business owners, who might otherwise miss calls and potential business, to benefit from AI-driven efficiency. Astabatsyan explains, “The AI can do it in a more affordable manner, more reliably, and humans can do other stuff.”
Key Benefits of Synthflow’s AI Voice Assistance
Technology and Integration
Synthflow builds on OpenAI’s GPT language models, incorporating its own AI models fine-tuned to specific customer needs. The startup has developed a “voice orchestration layer” that converts speech to text, processes it with AI, and converts responses back to speech. This technology ensures that even non-technical users can design voice agents tailored to their business requirements.
Future Developments
Looking ahead, Synthflow plans to enhance its capabilities with features like “live actions” or “connections,” allowing AI to check live inventory or pull requested information during a call. The startup envisions a scenario where task-focused AI systems could collaborate, handing off calls to other specialized AI agents or human operators as needed.
Challenges and Opportunities
Astabatsyan acknowledges that while AI can increase productivity, it also raises questions about resource allocation. “If there’s so much capacity — and productivity gets unleashed — how do we channel this human resources in other sectors of the economy?” he pondered, highlighting a key challenge for managers and leaders.
Funding and Investor Participation
The $7.4 million seed round was led by Singular, with participation from existing investor Atlantic Labs and AI-focused investors, including the founders of Krisp AI. This robust financial backing underscores the confidence in Synthflow’s potential to transform SME operations through AI.
Summary of Synthflow’s Progress
Aspect | Details |
---|---|
Funding Raised | $9.1 million total, including $7.4 million seed round |
Founding Date | Around spring last year |
Customer Base | Approaching 1,000 customers |
Growth Rate | Double-digit monthly growth since December 2023 |
Core Focus | Automating repetitive tasks for SMEs |
Technological Foundation | OpenAI’s GPT, proprietary AI models |
Languages Supported | English (main), German and French (beta) |
Key Takeaways
Synthflow’s innovative approach to AI voice assistance positions it as a promising player in the SME sector, with substantial backing from investors and a clear roadmap for growth and development.
When Ironspring Ventures launched in 2020 to back startups in industrial sectors like construction and manufacturing, it was one of very few early-stage venture firms paying attention to these capital-intensive sectors. Now, the firm is doubling down on its initial commitment.
The Austin, Texas-based firm raised $100 million for its second fund, focusing exclusively on industrial startups. This marks a significant increase from the firm’s $61 million debut fund that closed in 2021. The latest raise has enabled Ironspring to expand its team by hiring its first principal, Colleen Konetzke, and a head of platform, Stephanie Volk. With Fund II, the firm plans to invest in 20 startups, supporting four to five companies annually.
“What we saw back then was as true as we see today,” Ironspring co-founder and general partner, Ty Findley, told TechCrunch. “There is a big gap in the venture industry that deeply studies and has genuine GP market fit with these industrial markets and can help them navigate a pretty challenging go-to-market process. When you really roll these industries up, they are over half of the U.S. GDP. My strong opinion is, we as a country simply cannot afford to let the U.S. get left behind.”
Findley refers to industries including manufacturing, construction, transportation, and energy. The firm backed 16 companies in its first fund, among them Solvento, a payments infrastructure startup for trucking companies in Mexico; OneRail, a last-mile logistics startup; and Prokeep, a communications platform for distributors.
Ironspring has already backed six companies with Fund II and has deployed about a quarter of the fund. Findley notes that the main difference between Fund I and Fund II is the additional capital, which allows the firm to write larger checks, ranging from $2 million to $4 million. This financial capability helps Ironspring stay competitive as seed rounds have grown larger.
Fund | Amount Raised | Number of Companies Backed | Check Size |
---|---|---|---|
Fund I | $61 million | 16 | Smaller initial checks |
Fund II | $100 million | 20 (planned) | $2 million to $4 million |
Findley expresses enthusiasm for having a fresh pool of capital to invest now, given the macroeconomic tailwinds affecting the industries they focus on. Supply chain constraints that began during COVID-19 persist, and new challenges have emerged due to conflicts in the Middle East. Policies like the Inflation Reduction Act and CHIPS and Science Act are also bringing attention and government funding to these sectors. Additionally, advancements in AI could significantly impact these industries.
“We are seeing more top-tier tech and innovation talent flood into these industries,” Findley said. “Whether they are recirculating from recent tech unicorns, or just other tech talent that simply wants to make a big impact on their career that’s not based on photo sharing or adtech or chasing the next crypto coin, that is what the macro trends are.”
GoodShip, a freight orchestration and procurement platform started by former operators at Convoy, exemplifies the type of company Ironspring is keen to support. Ironspring co-led the firm’s 2023 seed round alongside Chicago Ventures and re-upped at the Series A earlier this year.
While Ironspring was one of the first early-stage firms focused on industrial startups, the space has become more crowded as deep-pocketed firms like Andreessen Horowitz, General Catalyst, and Bessemer have entered. However, Findley views the entrance of these name-brand firms not as competition but as a positive development.
“I’m a believer that the more capital flowing into these industries, the better,” Findley said. “Those are great allies. We wouldn’t be able to do our job at the seed stage if we didn’t have great downstream growth.”
Findley emphasizes the collaborative nature required for these types of startups to grow successfully, appreciating the different perspectives other firms can bring to their portfolio companies. Ironspring even invites these other firms onto its podcast, Heavy Hitters, to create a valuable resource for their portfolio companies and beyond. Notable VCs such as Katherine Boyle, a general partner at a16z; Aaron Jacobson, a partner at NEA; and Lior Susan, the CEO and founder of Eclipse Ventures, have been featured.
Findley believes Ironspring stands out among the growing competition due to its sector expertise and unique LP base. The firm’s LP base includes operators in the industries they invest in, such as owners of construction companies and manufacturing plants. These LPs can provide guidance and advice to companies and serve as potential customers.
Being based in Austin is also a significant asset for Ironspring, according to Findley. Contrary to the perception that Austin is merely an emerging tech hub, he points out that many of the industries Ironspring focuses on have deep roots in the area. With Tesla moving its headquarters to Austin and the recent approval of $6.4 billion from the infrastructure act for Samsung to build semiconductor chips there, the city has the right talent to drive the digital industrial revolution.
Findley’s commitment to ensuring that critical U.S. industries are not left behind is unwavering. “The U.S. can’t allow these critical industries to be left behind,” he said. “We are here for the long haul in ensuring that will never happen.”
With a fresh pool of capital and a strategic focus on industries vital to the U.S. economy, Ironspring Ventures is poised to make a significant impact on the industrial startup landscape. The firm’s approach, combining sector expertise and collaborative investment strategies, ensures that it remains a key player in fostering innovation in these critical sectors.