Secoda, a Toronto-based company specializing in AI-powered data search, cataloging, lineage, and documentation, has recently announced a successful Series A funding round, securing $14 million in investment. This capital infusion is earmarked for the advancement of its AI solutions, with the ultimate goal of enabling any enterprise user, regardless of their technical expertise, to seamlessly access, comprehend, and utilize company data. The user experience is designed to be as effortless as conducting a Google search.
This funding round brings Secoda’s total funding to $16 million and is spearheaded by its existing investor, Craft Ventures, with notable participation from Abstract Ventures, YCombinator, and Garage Capital. Distinguished figures from the data ecosystem, including Jordan Tigani (CEO of MotherDuck), Scott Breitenother (CEO of Brooklyn Data), and Tristan Handy (CEO of dbt), have also joined in this round.
Jeff Fluhr, co-founder and partner at Craft Ventures, emphasized the growing significance of data lineage understanding and data utilization for companies. He stated, “It has become increasingly important that companies not only have a full understanding of the lineage of their data from disparate sources but also harness their data to make more efficient and informed decisions. Secoda has built a powerful AI-powered data copilot for companies to do just that.”
In today’s enterprise IT landscape, numerous systems are designed for diverse functions, creating a complex web of technologies that are essential for organizational efficiency. However, this complexity often results in disconnected data sources, with applications failing to communicate effectively and data remaining isolated.
Consequently, employees face challenges when seeking answers related to data. They must navigate through convoluted applications or seek assistance from the data team, diverting attention from other tasks. Etai Mizrahi, who encountered similar issues while working at Acadium, described the frustration: “Questions that seem simple enough to answer end up feeling like a huge, frustrating game of broken telephone.”
Addressing the Knowledge Gap: To bridge this knowledge gap, Mizrahi collaborated with colleague Andrew McEwen to launch Secoda in 2021, offering an all-in-one platform for data management and search. Secoda seamlessly integrates with business intelligence and transformation tools, as well as data warehouses, effectively connecting all components of a team’s fragmented tech stack to establish a single source of truth for company data.
To simplify the process further, Secoda employs a ChatGPT-powered assistant, enabling users to create documentation that adds contextual information to metadata. Users can also search their company’s consolidated data catalog using natural language queries. Mizrahi highlighted the platform’s capabilities, stating, “Secoda does not simply give you information but gives you answers, much like Google… Our customers have been able to leverage the platform to reduce the volume of inbound data requests by over 40%, reduce onboarding times by 50%, and reduce time teams spend on documentation by 90% — huge time savings for data teams.”
With the recent funding injection, Secoda plans to bolster its engineering team and intensify research and development efforts, particularly in the area of AI enhancements. Additionally, the company intends to introduce “Secoda Monitoring” to assist data teams in ensuring the quality and accuracy of the data they use. This feature will provide insights into how changes affect assets and reduce data quality errors. Monitoring will also enable companies to track the operational efficiency of their data teams and identify potential cost savings.
Over the past year, Secoda has experienced substantial growth, expanding its customer base by a factor of five and managing over 100 million metadata resources, including tables, dashboards, columns, and queries. On the integration front, the data search tool currently supports 36 popular data warehouses, business intelligence tools, and productivity platforms, including Snowflake, dbt, and Looker. The company is committed to continually adding more connectors based on popularity and user demand.
Voyager Capital is in the process of securing funds for yet another investment fund aimed at supporting early-stage business-to-business startups situated in the Pacific Northwest.
This latest development comes to light through a recently filed document with the SEC, marking this as Voyager’s sixth fund since its inception 25 years ago.
Diane Fraiman, the Managing Director at Voyager, confirmed this news following an inquiry from GeekWire. The goal for this sixth fund is to amass $100 million, with a “hard cap” set at $125 million, according to Fraiman.
Notably, Voyager had previously raised $100 million for its fifth fund back in 2019, following an earlier $50 million fund in 2013.
Established in 1997, Voyager has provided support to over 75 companies within the Pacific Northwest, accumulating assets under management exceeding $520 million.
With offices in Seattle and Portland, Voyager concentrates its investments in startups hailing from Washington, Oregon, British Columbia, and Alberta. These startups primarily focus on developing software-as-a-service, cloud infrastructure, artificial intelligence, and machine learning-related products and services.
Some of the companies currently within Voyager’s portfolio include Carbon Robotics, Treasury4, WellSaid Labs, Hiya, Syndio, among others. Notable exits include Zipwhip, acquired by Twilio in 2021, and Yapta, acquired by Coupa Software in 2020.
The venture capital landscape has faced challenges recently due to higher interest rates and a tech market slowdown. PitchBook reported a total of $33.3 billion raised across 233 venture funds in the first half of the year, compared to over $167 billion raised in 2022.
During a panel discussion in downtown Seattle earlier this summer, Bill McAleer, Managing Director at Voyager Capital, offered insights into factors he believes will rejuvenate the venture capital market. These factors include tech professionals laid off from larger companies seeking opportunities in startups, the revaluation of early-stage companies offering advantages to venture capitalists, and the growing adoption of generative AI, with McAleer predicting that the AI tools market will soon rival or even surpass the impact of cloud technology.
Several other Pacific Northwest firms have also announced new funds this year, including PSL Ventures, Ascend, Madrona Venture Labs, and AI2.
Today, Google unveiled a significant upgrade to its Bard conversational AI system, broadening its functionality to seamlessly interact with Google’s most popular productivity apps and services. These improvements are designed to enhance Bard’s utility in daily tasks while also addressing concerns regarding its accuracy.
Effective immediately, Bard gains the ability to directly tap into information from apps such as Gmail, Docs, Maps, Flights, and YouTube. This empowers it to deliver more comprehensive and personalized responses during conversations. For instance, when planning a trip, Bard can now autonomously retrieve pertinent dates, flight details, directions, and sightseeing recommendations, all within a single conversation.
This upgrade follows Bard’s somewhat lackluster public debut in March, which exposed factual inaccuracies in many of its responses. Google aims to bolster Bard’s accuracy by integrating it with its search engine. Users now have the option to fact-check Bard’s responses against web information indexed by clicking a “Google it” button within the chat.
Google emphasizes its unwavering commitment to safeguarding users’ personal information with this update. Those who choose to utilize the Workspace extensions can rest assured that their content from Gmail, Docs, and Drive remains confidential, unseen by human reviewers, not utilized for ad targeting by Bard, nor employed in training the Bard model. Users retain full control over their privacy settings.
Additionally, Google has simplified the process of building upon others’ interactions with Bard. From today onwards, if someone shares a Bard chat via a public link, the recipient can continue the conversation, pose further inquiries to Bard about the topic, or use it as a starting point for their own discussions.
Furthermore, Google extends access to existing English language features, including the ability to upload images using Lens, receive Search images in responses, and adapt Bard’s responses to over 40 languages.
Although Bard’s capabilities are still somewhat limited, these new features hint at a future where AI assistants seamlessly combine conversational skills with email and document services to enhance productivity. As Bard continues to advance, it may integrate further with other Google offerings, such as calendar, photos, and analytics.
The rollout of these Bard upgrades begins today, with Google planning to introduce additional languages and integrations in the months ahead, all while upholding responsible technology refinement.
HiddenLayer, a cybersecurity startup based in Austin, Texas, emerged in response to a cyberattack that exploited machine learning code at the founders’ previous company. Today, HiddenLayer has announced a successful $50 million Series A funding round aimed at bolstering the defenses of the ever-expanding array of AI models adopted by enterprises.
This funding round was spearheaded by M12, Microsoft’s Venture Fund, and Moore Strategic Ventures, with participation from Booz Allen Ventures, IBM Ventures, Capital One Ventures, and Ten Eleven Ventures.
HiddenLayer’s CEO and Co-Founder, Chris Sestito, expressed, “The rapid adoption of AI inspires us to accelerate our mission, ensuring that every security professional possesses the necessary tools and expertise to embrace AI securely.”
HiddenLayer already plays a crucial role in safeguarding AI/ML models for numerous Fortune 100 companies across various sectors, including finance, government, defense, and cybersecurity.
What HiddenLayer Offers:
Previously covered by VentureBeat, HiddenLayer has developed a suite of tools as part of its “MLSec” Platform, designed to safeguard enterprise machine learning (ML) and AI models. These tools do not directly access the models or compromise clients’ proprietary data and technology. Instead, they actively monitor the performance and operations of enterprise ML/AI models and associated applications in real-time. They scan for overarching vulnerabilities, provide recommendations for fortifying security, and detect the injection of malicious code/malware. Furthermore, they deploy defense mechanisms to thwart attackers and isolate intrusions.
HiddenLayer’s MLSec Platform includes an intuitive yet powerful dashboard, granting security managers immediate access to essential information about the security status of their enterprise ML/AI models. It automatically lists security issues and alerts in order of priority based on severity and stores data for compliance, auditing, and reporting purposes.
Additionally, HiddenLayer offers consulting services provided by their team of Adversarial Machine Learning (AML) experts, who remain up-to-date with the latest security trends and threats. These services encompass threat assessments, training for cybersecurity and DevOps personnel, and “red team” exercises to verify the effectiveness of clients’ defenses.
Earlier this year, HiddenLayer established a partnership with the prominent enterprise data lakehouse provider, Databricks. This collaboration enables Databricks enterprise customers to directly utilize HiddenLayer’s MLSec Platform for their models running on Databricks’ lakehouses. The integration is model-agnostic and covers model scanning, detection, and response. It empowers Data Scientists and ML Engineers to enhance their models’ security without altering their code or environment. As models are loaded, HiddenLayer’s model scanner ensures integrity and security. If an attack is detected, the integration responds automatically without human intervention.
Future Goals for Enterprise AI Security:
HiddenLayer’s inception traces back to an incident at its co-founders’ prior company, Cylance, where ML models fell victim to a cyberattack. Attackers exploited Cylance’s Windows executable ML model, revealing vulnerabilities and enabling the production of evasive binary files. While this event was concerning, it prompted the realization that attacks on ML/AI would escalate as more enterprises adopted generative AI to boost efficiency and performance.
Presently, HiddenLayer is experiencing rapid growth, having quadrupled its workforce in the past year. With the Series A funding secured, the company plans to hire an additional 40 personnel by year-end and continue expanding its client base.
Seattle’s tech leaders claim their city is a hub for AI innovation, but recent assessments of promising AI startups paint a different picture:
While there were two Seattle companies on the IVP Enterprise AI 55 list, they were overshadowed by Bay Area competitors.
Salesforce CEO Marc Benioff proclaimed, “San Francisco & California serve as the headquarters for AI companies and the talent pool,” referencing the IVP list.
Seattle’s modest presence and limited recognition beyond its borders could hinder its ability to attract leading entrepreneurs and AI executives. This poses potential challenges as the AI industry, fueled by advancements in generative AI, is expected to yield trillions of dollars in economic impact.
Matt McIlwain, managing director at Seattle VC firm Madrona, emphasized that Seattle should be considered “one of the premier centers of excellence for AI.” However, he acknowledged, “sometimes we are too understated.”
Perhaps the city’s AI innovators are quietly at work in Seattle, a place not known for self-promotion.
Ultimately, the perception of Seattle as an AI hub could play a pivotal role in attracting AI talent and bolstering the city’s innovation ecosystem. As Kirby Winfield, founding general partner at Seattle venture firm Ascend.vc, noted, “Perception certainly matters in attracting talent and other resources to a region.”
Heather Redman, managing partner at Seattle VC firm Flying Fish, urged the city to address its underselling of its AI capabilities and prioritize collaborations between the tech and non-tech sectors. She emphasized the transformative potential of AI across various industries and aspects of society.
Seattle’s AI clout
Many acknowledge that Silicon Valley serves as the focal point for AI startups.
According to PitchBook, AI and machine learning companies based in San Francisco raised an impressive $12.8 billion across 219 deals through August, putting their performance in a league of its own. In contrast, Seattle-based AI and machine learning firms secured a modest $170 million in funding across 24 deals during the same period.
Nevertheless, Seattle claims the second spot nationally in terms of AI talent density, a metric that gauges the number of professionals specializing in AI, according to data from SeekOut, a Seattle-based recruiting platform.
Vivek Ramaswami, a partner at Madrona in San Francisco, commented, “Ultimately, what matters most for these startups is the ability to attract exceptional talent and deliver outstanding products. I believe that Seattle stands out among most other cities outside of the Bay Area in this regard.”
Seattle boasts an impressive tech landscape, with cloud computing giants Microsoft and Amazon headquartered in the region, offering vital tools and services that drive AI and machine learning applications. Griffin noted, “The investments made by these two companies in AI are massive by any standard.”
In addition to Microsoft and Amazon, Meta, Google, and Apple maintain substantial engineering centers in the Seattle area, employing thousands of top AI researchers and engineers.
Seattle’s allure extends to academia, attracting prominent AI researchers to the University of Washington’s computer science school and the Allen Institute for AI (AI2). Notably, the AI2 Incubator, which recently secured $30 million for its latest fund, has spawned over 20 AI startups, some of which were later acquired by tech giants like Apple and Baidu.
Seattle’s AI community also received recognition on Time’s recent list of 100 leading AI influencers, with seven individuals linked to the city, including Microsoft’s Kalika Bali, Kate Crawford, Kevin Scott, and Jaime Teevan, sci-fi author Ted Chiang, and UW professors Emily Bender and Yejin Choi.
Ed Lazowska, a longtime computer science professor at the University of Washington, proudly declared, “We are unquestionably an AI hub, particularly if we define it by ‘AI expertise’ rather than just ‘buzzworthy startups’.”
Seattle boasts a thriving AI startup scene, with a multitude of rapidly expanding ventures making their mark. Notable inclusions in this burgeoning landscape, as highlighted in lists such as NFX’s AI Hot 75 and the IA40, encompass a diverse array of innovators:
Moreover, Seattle’s AI-focused startups extend beyond these select few, with the GeekWire 200 ranking providing additional insights into the region’s vibrant private sector:
In the summer months, several Seattle-area AI startups, including A-Alpha Bio, DropZone AI, and Protect AI, secured substantial capital investments, further fueling the city’s AI innovation ecosystem.
Ramaswami, an advocate for Seattle’s AI prominence, emphasized that the city’s continued elevation as an ‘AI hub’ hinges on both startups and established companies expanding, making astute hires, and delivering top-tier AI products to the market.
McIlwain stressed the importance of effective storytelling for industry giants like Amazon, asserting that it’s crucial for everyone to actively share and amplify Seattle’s compelling AI narrative.