Bloomberg Beta is an early-stage venture capital firm with $375M under management, capitalized solely by Bloomberg. The fund exists to expand Bloomberg’s horizons by investing in companies built by extraordinary founders that make business work better, with a focus on machine intelligence.

Bloomberg Beta

Heavybit is the leading investor in developer-first startups that turn visions into movements, products into platforms, and contributors into communities. Our partnership, team, and community of technical founders and 600+ domain experts have an unequaled track record of nurturing developer-first startups.

Heavybit

Xfund is the early-stage venture firm designed to back lateral thinkers. Partnering with Harvard University and others of the world’s preeminent universities, Xfund looks beyond the stereotypical technical pedigrees to seek out extraordinary people who are being systemically ignored by traditional venture capital: technically-gifted liberal arts entrepreneurs. We believe it’s our responsibility to help these unconventional, high potential founders align their ambition and passion with opportunity we help them create, to build the sort of ground-breaking companies that can create a better tomorrow. Xfund has offices in Palo Alto, California, and in Cambridge, Massachusetts. For more about Xfund, please visit http://www.xfund.com.

Xfund

A founder-centric early-stage fund investing in enterprise data opportunities.

Octave

Notable Capital is named for the founders we invest with, the ideas they pursue, the causes they champion, and the remarkable companies they build. Notable is a U.S.-based venture capital firm focused on early-to-growth stage companies in cloud infrastructure and business and consumer applications across the U.S., Israel, Europe, Latin America, and select go-global opportunities. Notable portfolio companies include Affirm, Airbnb, Block, Brightwheel, Drata, Handshake, HashiCorp, Ibotta, Orca Security, Quince, Slack, Slice, StockX, Stori, Vercel, Zendesk, and more.

Notable Capital

Silicon Valley CISO Investments (“SVCI”) is a group of Chief Information Security Officers (“CISO”) that operate as an angel investor syndicate. Founded in 2019, SVCI is already successfully pursuing its mission of fuelling the next generation of cybersecurity innovation. The group identifies promising startups, invests in them and leverages its members’ unmatched industry expertise to help the companies thrive.

Silicon Valley CISO Investments

Insight Partners is a global software investor that partners with growth-stage technology and software companies. Insight has a deep focus in Fintech, Cybersecurity, AI/ML, DevOps, and Healthcare sectors. Across their people and their portfolio, they encourage a culture around a core belief growth equals opportunity. As of December 31, 2022, the firm has over $75B in regulatory assets under management. Insight Partners has invested in more than 750 companies worldwide and has seen over 55 portfolio companies achieve an IPO.

Insight Partners

Tonic.ai

Tonic empowers developers while protecting customer privacy by enabling companies to create safe, synthetic versions of their data for use in software development and testing. Founded in 2018 with offices in San Francisco and Atlanta, the company is pioneering enterprise tools for database subsetting, de-identification, and synthesis. Thousands of developers use data generated with Tonic on a daily basis to build their products faster in industries as wide ranging as healthcare, financial services, logistics, edtech, and e-commerce. Working with customers like eBay, Flexport, and PwC, Tonic innovates to advance their goal of advocating for the privacy of individuals while enabling companies to do their best work. For more information, visit Tonic.ai.

Tonic.ai provides a platform for application developers to create synthetic datasets for use in building and testing software applications. The synthetic data is generated from and mimics actual production data, using techniques such as differential privacy. This allows the retention of the actual data’s utility. The platform also allows for automatic scanning and de-identification of sensitive data and is deployed on-premise, ensuring that sensitive data does not leave the source and risks from external threats are mitigated. Tonic.ai’s solution also enables organizations to achieve compliance with privacy regulations such as GDPR and CCPA.

New data privacy regulations have opened up space for a new wave of compliance-focused startups.

Digital Privacy Tools

Tonic helps to create synthetic datasets for use in model building and AI application testing by leveraging deep neural network generative models through variational autoencoders (a type of deep learning technique). The synthetic data mimics actual production data based on techniques such as differential privacy, while ensuring the retention of original data utility. The platform also supports semi-structured data such as NoSQL databases. It also allows automatic scanning and de-identification of sensitive data, ensuring that sensitive data does not leave the source to mitigate risks from external threats. This also enables organizations to achieve compliance with privacy regulations such as the GDPR and CCPA.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Tonic

Tonic.ai Named to Rising in Cyber 2024

Tonic.ai provides a platform for application developers to create synthetic datasets for use in building and testing software applications. The synthetic data is generated from and mimics actual production data, using techniques such as differential privacy. This allows the retention of the actual data’s utility. The platform also allows for automatic scanning and de-identification of sensitive data and is deployed on-premise, ensuring that sensitive data does not leave the source and risks from external threats are mitigated. Tonic.ai’s solution also enables organizations to achieve compliance with privacy regulations such as GDPR and CCPA.Key customers and partnershipsThe company serves customers in industries such as healthcare, financial services, EdTech, logistics, and ecommerce. Key clients include eBay, Philips, Walgreens, American Express, Signify Health, NHL, Volvo, and United Health Group.

OneTrust provides compliance solutions that leverage AI tools and automation across all areas of privacy compliance. The company’s AI-powered solution sees widespread use, providing automation in the areas of data discovery, data subject rights management, consent management (with a user-facing preference center for greater control), data protection impact assessments, third-party risk management, incident response reporting, and monitoring.The company also provides regulatory research software that companies can use to train staff and even benchmark their own privacy programs. The company’s Government Records Request Automation solution helps government organizations intake requests, automate data discovery and redaction, and provide a secure two-way communication portal that demonstrates compliance with FOIA, PRR, and the Privacy Act. OneTrust’s products were backed by over 200 patents as of September 2024.OneTrust has strengthened its position in the digital privacy space through several acquisitions in recent years. In March 2021, OneTrust acquired DocuVision, an AI-powered data redaction platform to bolster its data subject rights capabilities through automatic redaction of non-relevant sensitive information. During the same month, OneTrust acquired Convercent to enhance its platform through advanced ethics and compliance capabilities, and helpline and disclosure management. OneTrust acquired the security assurance and certification platform Tugboat Logic in September 2021, to automate its InfoSec assurance and certification processes. Other notable acquisitions include Privacy Core e-learning, DataGuidance, and Integris Software.In March 2023, OneTrust announced the addition of certification automation to the OneTrust GRC and Security Assurance Cloud. This solution which combines automation, pre-built policies and controls spanning 29 industry frameworks, over 100 integrations, compliance content, and expert guidance enables customers to simplify and streamline compliance tasks according to OneTrust.Key customers and partnershipsAs of September 2024, OneTrust said it served over 14,000 active customers, including 75 of the Fortune 100. The company claims it serves notable organizations from all industries, with Adobe, Walgreens, Samsung, and Mearsk among its customer base.OneTrust entered a partnership with Dow Jones Risk and Compliance in April 2023, to incorporate risk and compliance data into its third-party due diligence solution.

OneTrust

CENTRL provides automated risk management and privacy management solutions. Through its Privacy360 platform, the company provides solutions to identify compliance gaps, automate data discovery, manage data subject rights requests, consent management (with a user-facing preference center), carry out impact assessments, third-party risk management, monitoring, and reporting.

CENTRL

HighSide provides a secure communications platform for organizations, enterprise archiving solutions, data discovery, and supervision tools in compliance with GDPR, CCPA, etc. In 2019, the company announced the acquisition of Hotshot Technologies, a secure team messaging platform.

HighSide

SecuPI provides a patented platform enabling organizations to achieve compliance with regulations such as GDPR and CCPA. The platform achieves this by providing multiple features to protect data such as pseudonymization, consent controls, audit logs, streamlining breach notifications, etc. SecuPI’s platform is deployed in organizations in the banking, insurance, telecommunications, and health industries.

SecuPi

JoinPrivacy is a B2C solution that allows users to manage their personal data from the websites they use, all from one place.

JoinPrivacy

Solutions to prevent the tracking and collection of the personal data of end-users.

Encrypted communications and data exchanges for internal and external collaboration around sensitive data.

Tools to provide compliance with privacy regulations, such as GDPR and CCPA, and carry out tasks such as data discovery, data governance, consent management, Data Subject Rights (DSR) management, Data Protection Impact Assessments (DPIA) and managing incident response as mandated by these privacy regulations.

Synthetic data generation, data de-identification and anonymization, and other solutions for managing sensitive data.

Storage infrastructure for holding data in compliance with regulations such as GDPR or data residency requirements.

Central management of data access and data privacy and security policies.

Uses AI/ML to automate workflows such as data discovery and data classification

Uses generative AI to provide conversational recommendations to users to remain compliant with privacy regulations

Solutions in this industry hub are offered under a B2B SaaS model

Tonic helps to create synthetic datasets for use in model building and AI application testing by leveraging deep neural network generative models through variational autoencoders (a type of deep learning technique). The synthetic data mimics actual production data based on techniques such as differential privacy, while ensuring the retention of original data utility. The platform also supports semi-structured data such as NoSQL databases. It also allows automatic scanning and de-identification of sensitive data, ensuring that sensitive data does not leave the source to mitigate risks from external threats. This also enables organizations to achieve compliance with privacy regulations such as the GDPR and CCPA.In addition, Tonic offers a solution to anonymize data to train LLMs that ensure data privacy and compliance. The company also offers a solution called Ephemeral to instantly create shareable data environments to equip developers with necessary data. It allows users to quickly create copies of existing databases for testing, bug reproduction, and demos.The company offers its platform through a subscription and usage-based model.Key customers and partnershipsAs of January 2024, the company served over 50 customers across the healthcare, financial services, EdTech, logistics, and ecommerce industries. Its notable customers include eBay, The Motley Fool, Flexport, VMware, Everlywell, Kin Insurance, and Scalapay.Tonic partnered with <a href="https://sp-edge.com/companies/241548">Snowflake</a> in June 2022 to allow joint customers to develop AI applications in the Snowflake Data Cloud platform with realistic, de-identified data as well as tokenize data to ensure regulatory compliance.Funding and financialsIn September 2021, the company raised USD 35 million in a Series B funding round led by Insight Partners. The company utilized the funds to accelerate product development, improve developer relations, invest in customer acquisition and retention, and expand its team to 100.The company reported that its revenue grew by more than 600% YoY in 2020 and was on track to achieve a 500% YoY increase in revenue in 2021.

Datagen provides a self-service synthetic data platform that generates visual synthetic data of humans for computer vision applications. The platform allows users to write their own code to generate labeled synthetic data for faces, full body, and humans in motion in the form of images and videos to test and train AI models while retaining complete control over the data. The data covers a range of computer vision tasks including face landmark detection, face and hair segmentation, facial recognition and identification, full body pose estimation, full body segmentation, and behavior detection.Key customers and partnershipsThe company serves three of the top five global technology companies and Fortune 500 companies across the automotive, smart fitness, AR/VR/metaverse, smart office, and home security industries. Its notable customers include Google, Toyota, NVIDIA, IBM, and Intel.Funding and financialsIn March 2022, the company raised USD 50 million in a Series B funding round led by Scale Venture Partners. The funds were utilized to bolster its position in the market.Datagen reported to have recorded 8x growth in revenue in 2022.

Datagen

Weights &amp; Biases offers a platform that allows users to build models with experiment tracking, data set and model versioning, data visualization, hyperparameter optimization, and model management. The platform enables users to automatically retrain and re-evaluate models and centrally manage all model versions through every lifecycle stage—from development to staging to production. It also helps to visualize comparisons between model versions to evaluate performance and identify regressions before model deployment. It also offers toolkits such as <a href="https://sp-edge.com/updates/19172">W&amp;B Weave and W&amp;B Production Monitoring </a>to build and monitor data- and ML-powered applications, respectively, through interactive visualizations.The company also offers a <a href="https://sp-edge.com/updates/17880">suite of tools (W&amp;B Prompts) </a>to support large language model operations (LLMOps). W&amp;B Prompts includes tools and features for experiment tracking, debugging, and collaboration, as well as a one-click method to evaluate and score prompts through the OpenAI Eval’s framework.The company provides the platform through a free tier and under a subscription model for up to USD 50 per user per month.Key customers and partnershipsWeights &amp; Biases served more than 700,000 ML practitioners as of August 2023. Its notable include NVIDIA, Toyota, BMW Group, Samsung, Fujifilm, Truebill, and Clear Capital.The company has <a href="https://sp-edge.com/updates/18663">partnered with Lambda </a>, a GPU cloud computing provider, to offer its MLOps platform integrated with the infrastructure services of the latter, catering to enterprises dealing with AI and deep-learning workloads.Funding and financialsIn August 2023, the company raised <a href="https://sp-edge.com/updates/20874">USD 50 million in a strategic investment </a>round at a valuation of USD 1.25 billion, led by Daniel Gross and Nat Friedman. The round also saw participation from Sapphire Ventures, Coatue, Insight Partners, and other investors. The company aimed to utilize the fresh funds to further develop its ML tools, including the launch of W&amp;B Prompts.

Weights & Biases

BentoML offers an open-source platform called Bento Cloud, for the deployment and scaling of AI applications. It is a fully managed platform that handles the complexities of AI infrastructure, providing serverless autoscaling as required during the development and production stages. The platform helps to ship models to production with advanced deployment options including online and shadow A/B testing, while also providing visibility through model performance monitoring. The platform integrates with an organization’s existing data stack and enables users to continuously deploy and improve models in production. The company offers its platform through a combination of subscription and usage-based model.In addition, BentoML also provides the following open-source platforms: 1) Yatai, for model deployment on Kubernetes and 2) bentoctl, for model deployment on any cloud platform.Key customers and partnershipsAs of January 2024, BentoML reported that over 1,000 organizations, comprising more than 3,000 members, use its platform. Its notable customers include Koo, Open Layer, Line, and Naver.The company entered into a strategic partnership with TomTom, a developer of location technology, to help integrate with various models as well as in LLM deployments.Funding and financialsThe company raised <a href="https://sp-edge.com/updates/19684">USD 9 million in seed funding </a>in June 2023 led by DCM Ventures, with participation from Bow Capital. It aimed to channel the newly acquired funds to enhance its platform and offer developers a range of tools for building, deploying, and scaling AI applications efficiently.

BentoML

Iguazio provides a serverless platform based on its open-source Nuclio framework that helps users to develop, deploy, and manage real-time AI applications without requiring them to manually manage underlying infrastructures such as servers and storage. The platform creates real-time intelligence for applications located at the edge, public cloud, and on-premise data centers and reduces bandwidth constraints by consolidating data into a repository and making it available for applications as required. The platform can ingest and transform data from any source, which is then used to train, evaluate, deploy, and monitor models in production.The company leverages Big Data and ML software such as Apache Spark, TensorFlow, and Kubernetes to manage software containers that enable applications to run across different computing environments.Key customers and partnershipsIguazio serves customers in the financial services, telecommunications, smart mobility, manufacturing, retail, AdTech, gaming, healthcare, energy, and utilities sectors. Notable customers include Samsung, Microsoft, NVIDIA, AWS, Google, and Intel.Funding and financialsIn January 2020, the company raised USD 24 million in a funding round led by INCapital Ventures. The funds were utilized to accelerate its growth, expand its reach into new global markets, grow sales, and facilitate new sales channels that include companies such as Dell Technologies

Iguazio

Cogito Tech provides image and video annotation to generate computer vision training data sets for ML &amp; deep learning (DL). The video annotation solution leverages AI-powered tools to convert video into a sequence of images and generates training data sets for ML-based AI models, including self-driving cars and drones. The AI model understands and derives insights from visual data to detect, identify, classify, and track objects in an image or video. Cogito also provides virtual assistants and chatbots to help users in the process of training ML algorithms. Cogito Tech also provides high-quality, ethically sourced datasets that are compliant and reliable to train ML models.In addition, the company provides services to fine-tune LLMs and GenAI applications through reinforcement learning techniques as well as stress test models through red teaming.Key customers and partnershipsAs of December 2022, the company served more than 150 customers across 25 countries in the retail, medical, automotive, agriculture, robotics, smart cities, security, and manufacturing industries. Notable customers includes Verizon Media, The University of Sydney, National Geographic, Tumblr, and Vimeo.

Cogito Tech

Platforms and frameworks that help developers build and train ML models.

Platforms that deploy and host the trained and tested models in production and integrate them into applications through APIs.

Platforms that generate artificial data that mimics the characteristics of real data, which is then used to train ML models at scale.

Platforms that help monitor and manage ML models in training and deployment to track performance, conduct variance analysis, and optimize performance.

Makers of hardware such as CPUs, GPUs, and other application-specific hardware required to train and run ML workloads.

Integrated solutions that handle the end-to-end processes of developing, training, deploying, and monitoring ML models.

Data exchange providers and platforms that offer data labeling services via manual and/or software methods, which are used as input to train ML models.

Includes companies that provide infrastructure to build AI/ML applications

Provides tools to build, monitor, and deploy GenAI applications

Industry is focused on offering platforms for other businesses to build AI-/ML-powered apps

Data Infrastructure & Analytics

ANALYST_QUICK_TAKE

PROMINENT_CATEGORY

<div>

 Snowflake, a firm focused on cloud-based data and artificial intelligence (AI) infrastructure, has announced partnerships with multiple AI companies at the Snowflake Data Cloud Summit 2024. The objective of these collaborations is to provide AI and machine learning (ML) development capabilities to Snowflake's customers via the Snowflake Marketplace.
 The company has teamed up with Mindtech, a platform that generates synthetic data. This partnership sees the launch of synthetic data training packs on Snowflake Marketplace, allowing joint customers to use synthetic data document packs to train AI vision systems quickly and with greater accuracy for particular applications.
 Snowflake has also formed a partnership with Tonic.ai, another platform that produces synthetic data. Together, they have released the Tonic Textual Native App on Snowflake Marketplace. The application ensures seamless and secure data redaction, tokenization, and synthesis of unstructured free-text data within the Snowflake accounts of joint customers.
 Furthermore, Snowflake has collaborated with Kumo AI, a platform dedicated to AI/ML model development. They have launched Kumo as a Snowflake Native App in the Snowflake Marketplace as part of a private preview. Eligible customers can pay for the app with Snowflake Capacity commitment. It is developed using the Snowflake Native App Framework, offering data scientists the tools necessary to create predictive models.

</div> Analyst QuickTake: 
 Snowflake’s CEO announced that these collaborations are part of the company's strategic plan to stay competitive in the data and AI infrastructure space by enhancing its capabilities. The company is also actively seeking acquisitions and hiring new AI talent. Additionally, it released its own LLM, <a href="https: 
//sp-edge.com/updates/28792"> Arctic </a> , in April 2024, designed for generating database code.

Tonic

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