Moonshots Capital makes seed stage investments in technology startups led by exceptional founders who are building products that “re-imagine” work and personal life in large and growing markets. We bring a disciplined approach to the investment process to identify companies with “moonshot” potential.

Moonshots Capital

Village Capital uses the power of peer support to change the traditional dynamics between investors and entrepreneurs, providing access to entrepreneurship for everyone.  We recruit entrepreneurs solving specific problems in agriculture, energy, education, financial inclusion, and health. We then put the power of investment in the hands of the entrepreneurs, who award pre-committed seed funding to the two ventures ranked highest by the entrepreneurs at the end of every program. Our programs connect high potential, early-stage entrepreneurs with the people, institutions, and capital they need to succeed. We support early-stage ventures with a 501c3 nonprofit that operates training programs for founders, investors, and communities. We also manage a for-profit, managed investment fund that provides early-stage capital to top graduates of each program, as selected by their peers. Our unique peer-selection model received McKinsey/Harvard Business Review’s prestigious M-Prize for innovation in 2013, and we have supported more than 550 enterprises across 51 programs in 9 countries. Since 2009, Village Capital has supported more than 1,000 entrepreneurs through our programs and partnered with affiliated investment funds, including VilCap Investments, that have invested seed capital in more than 90 program graduates. Over the past 8 years, our program graduates have gone on to generate $61.5M in revenue, reach 8.5 million customers, and create over 11,500 jobs. 96% of our alumni would recommend our program to other entrepreneurs, and to date and 91% of our entrepreneurs are still in business.

Village Capital

Greylock Partners invests in entrepreneurs that focus on consumer and enterprise software companies. The firm invests in companies that define new markets, including Airbnb, AppDynamics, Apptio, Arista Networks (NYSE: ANET), Cloudera, Docker, Dropbox, Facebook (Nasdaq: FB), LinkedIn (NYSE: LNKD), Medium, Nextdoor, Palo Alto Networks (NYSE: PANW), Pandora (NYSE: P), Pure Storage, and Workday (NYSE: WDAY). It was founded in 1965 and headquartered in Menlo Park, California.

Greylock

Anthos, founded in 2007, invests in emerging consumer and technology companies that drive innovation and shape the future. Anthos provides strategic and operational support to entrepreneurs, enabling its portfolio companies to achieve their full potential and become industry leaders.

Anthos Capital

Section 32, the new venture fund launched by Bill Maris, was named in homage to Section 31, an intelligence agency from the Star Trek universe.  Maris, the GV (Google Ventures) founder/former-CEO, has raised $150 million for the project that will focus on various investments.  The fund will be run directly by Maris and primarily based out of San Diego.

Section 32 Gretel

Gretel is a multimodal synthetic data platform that leverages advanced generative AI and privacy-enhancing technologies. Developers use Gretel to generate artificial datasets with the same characteristics as real data, so they can develop and test AI models without compromising privacy.

Gretel.ai offers a Software-as-a-Service (SaaS) platform that enables organizations to evaluate their existing datasets to identify personally identifiable information (PII) and create synthesized data that match the characteristics of the original data. The platform also allows anonymization of data and provides encryption features to enable secure sharing between teams and organizations in order to ensure the privacy of the underlying data.

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

Digital Privacy Tools

Gretel.ai offers a platform that allows developers to generate synthetic data. It allows organizations to evaluate their existing datasets to identify sensitive data, such as personally identifiable information (PII), and create synthesized data that matches the characteristics of the original data. The platform uses a combination of its models including: 1) tabular GAN models for numeric and categorical data; 2) language models for tabular data, such as mixed categorical, numeric, time-series, and text fields; 3) statistical models for tabular data; 4) DoppelGANger model for time-series data; and 5) pre-trained transformer models for natural language text. The platform also generates reports to evaluate and validate the quality of the synthetic data produced. In addition, it provides a feature to automatically and continuously detect and label sensitive data and anonymize data to preserve privacy.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

Gretel.ai

Gretel Open Sources 100,000 Text-to-SQL Samples

Amazon Web Services

Gretel and AWS collaborate to promote responsible generative AI using synthetic data, offering selected enterprises support, access to state-of-the-art synthetic data generation models, and tools to safely develop AI systems at scale while protecting sensitive information.

Empowering Tomorrow's Innovations with Generative AI Infrastructure

Generative AI Infrastructure

Platforms that enable safe, responsible, and ethical GenAI deployment, ensuring compliance with regulations and/or protection against GenAI-based cybersecurity threats.

Gretel.ai offers a Software-as-a-Service (SaaS) platform that enables organizations to evaluate their existing datasets to identify personally identifiable information (PII) and create synthesized data that match the characteristics of the original data. The platform also allows anonymization of data and provides encryption features to enable secure sharing between teams and organizations in order to ensure the privacy of the underlying data.The company has over 50 employees.Key customers and partnershipsGretel.ai serves organizations across the finance, healthcare, and public sectors with notable customers as of September 2024 including Fujitsu, Google, HSBC, Ilumina, MedStar Health, Riot Games, SAP, and Snowflake.Gretel partnered with Google Cloud in March 2023 to allow the latter’s customers to incorporate Gretel’s synthetic data into their enterprise applications.

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

Gretel.ai offers a platform that allows developers to generate synthetic data. It allows organizations to evaluate their existing datasets to identify sensitive data, such as personally identifiable information (PII), and create synthesized data that matches the characteristics of the original data. The platform uses a combination of its models including: 1) tabular GAN models for numeric and categorical data; 2) language models for tabular data, such as mixed categorical, numeric, time-series, and text fields; 3) statistical models for tabular data; 4) DoppelGANger model for time-series data; and 5) pre-trained transformer models for natural language text. The platform also generates reports to evaluate and validate the quality of the synthetic data produced. In addition, it provides a feature to automatically and continuously detect and label sensitive data and anonymize data to preserve privacy.Gretel also offers <a href="https://sp-edge.com/updates/30442">Gretel Navigator</a>, an agent-based compound GenAI system built to automate data creation and curation processes for AI development. It allows users with an easy mechanism to create, edit, and augment tabular data to build realistic test and training datasets. It is equipped with an ensemble of pre-trained AI models, offers an array of data formats, and brings context-specific optimizations to streamline workflows for AI projects.The company provides its platform under a subscription model, which includes a free plan with limited features.Key customers and partnershipsAs of January 2024, more than 110,000 developers were using Gretel’s platform. Its notable customers include Google, HSBC, Fujitsu, Snowflake, and the US Department of Justice.The company partnered with Google Cloud to expand its platform for Vertex AI and BigQuery developers, as well as list it on the Google Cloud Marketplace. In addition, it partnered with AWS to accelerate responsible GenAI development that protects sensitive and personal data.

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

PROMINENT_CATEGORY

<div>
 
 Gretel, a company providing a synthetic data generation platform, recently made Gretel Navigator available. This system has been designed to automate data creation and curation for AI development.
 Through Gretel Navigator, users can easily create, modify and enhance tabular data to produce realistic test and training datasets. Furthermore, it incorporates a number of pre-trained AI models and various data formats, along with specific optimization features meant to expedite workflows for AI projects.&nbsp;
 In essence, the tool helps developers to produce high-quality, privacy-preserving synthetic data with efficiency.&nbsp;
 
</div>

Gretel.ai

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