Participated · Series A · Mar 2024

Tennr built an orchestration platform and specialized language models (RaeLM) to automate the labor-intensive workflows of referral-based care. The company processes referrals that arrive by fax, email, or e-portal and evaluates documentation against complex payer criteria to flag potential denials. Tennr is launching Tennr Network, a coordination layer that gives referring providers, receiving providers, and patients real-time visibility into referral status. The product is designed to work with existing workflows—no EMR rip-outs or retraining—and aims to convert more patients, cut denials, and deliver care without growing teams. Tennr has processed millions of patients across hundreds of providers and says it has more than tripled revenue since its Series B two quarters ago. Cofounders Trey Holterman, Tyler Johnson, and Diego Baugh (who met at Stanford) emphasize building software that fits how healthcare already operates. Tennr focuses on automating document processing and workflow management specifically for the healthcare industry. The platform reads every document passing through healthcare practices and automates clinical and operational tasks — such as scheduling and qualifying patient visits — to input data into practice systems automatically. Tennr uses machine learning and document scanning technologies to streamline how referrals are handled by healthcare providers. The company plans to use new funding to grow its research team and expand sales and marketing efforts. Tennr was founded in 2021 by Trey Holterman, Diego Baugh, and Tyler Johnson and is based in New York. Its total funding now exceeds $61 million after the latest round. Tennr is a NYC-based startup that automates manual administrative work for healthcare organizations. Its platform cleans incoming fax data and automates patient intake and insurance communications by reading faxes, extracting needed information, and routing it to the right systems. Tennr automates referral processing, payment posting, claims auditing, and medical record management. Commercial health plans such as Prominence Health have begun using the technology. Co-founded by Trey Holterman, Diego Baugh, and Tyler Johnson, the company raised an $18M Series A led by a16z and has now raised over $25M in total. Tennr intends to use the proceeds to grow its team and scale operations.

Participated · Seed · Oct 2023

Gradient is an API platform that enables enterprises and developers to build large-scale custom AI models using private data and LLMs such as Llama2. The platform lets developers create and combine thousands of tuned LLMs and offers proprietary domain models for healthcare, finance, and law. Public usage is billed on a pay-per-token basis, while enterprises can opt for dedicated deployments. Gradient emphasizes security and privacy for production environments and is SOC2 and HIPAA compliant. The company was founded by Christopher Chang, Mark Huang, and Forrest Moret, who previously worked on AI products at Netflix, Google, and Splunk, and has nearly 20 employees. Gradient is based in Burlingame, California, and says the new capital will further development of its enterprise-focused developer platform and democratize access to AI.

Participated · Seed · Sep 2023

Gable provides a shift-left data management platform built around API-based "data contracts" that define, enforce, and automatically surface context and constraints across structured, semi-structured, and unstructured data. The platform connects software developers who own upstream data with downstream data developers and analysts to reduce broken pipelines, missing data, and contextual gaps. Early adopters report up to 70% faster incident resolution and nearly 50% faster development cycles for data-dependent features. Customers mentioned in the articles include Glassdoor, Grab, and x15ventures. The company will use the new capital to accelerate product development and expand teams, including hiring across engineering, product, and customer success. Gable was founded in 2023, is based in Seattle, and serves a community of over 15,000 engaged data practitioners; it is backed by $27 million in aggregate funding. Gable.ai is developing a data collaboration platform that enables software and data developers to iteratively build and manage high-quality data assets. The system uses "data contracts," API-based agreements between upstream software owners and downstream data developers and analysts, which are defined, enforced, and discovered through the platform. Key features include data asset recognition by connecting a data source, data contract creation to set constraints and owners, and contract enforcement via CI/CD checks within GitHub. The company is currently in product development and has raised $7M in Seed funding. Leadership includes CEO and co-founder Chad Sanderson and co-founders Adrian Kreuziger and Daniel Dicker. Sanderson is a data industry thought leader who runs Data Quality Camp (8,000+ practitioners) and writes the Data Products newsletter (11,000+ subscribers).

Participated · Seed · May 2023

WorkHack develops a controlled-AI layer and components that let enterprises deploy generative AI without creating in-house AI teams. The platform is designed to minimize the risk and difficulty of using LLMs in complex business scenarios and to enable safe, responsible AI adoption. It provides infrastructure for businesses to build conversational agents and deploy them on delivery stacks such as web, mobile, and WhatsApp. Founded in 2021 and based in Bengaluru, the company has handled over a million users and conducted over a million talks for its clients. In May 2023 WorkHack secured $1.5M to further develop its AI tech layer and help organizations deploy safe and responsible AI services. Founder Akshat Tyagi emphasizes the company’s focus on identifying human-interaction areas that can benefit from technology that appears to think and reason.

Participated · Series A · Jun 2022

Continual offers a cloud platform that lets data teams build and deploy predictive models directly on top of existing data warehouses (e.g., Snowflake, Redshift) using familiar skills like SQL and dbt. The company focuses on predictive use cases such as inventory forecasts, risk mitigation, and supply chain logistics. Its service is not a low-code/no-code tool but emphasizes accessibility by enabling data teams to leverage existing workflows and tooling. Continual announced its platform is generally available after exiting beta and has a preview of extensible MLOps for custom models. The company plans to add automated feature engineering and later this year introduce real-time feature and model serving. In the last three months it doubled active users, deployed models, and booked annual recurring revenue. To support growth and product development, Continual plans to double its team by the end of 2022. Continual offers an AI-powered platform that lets data teams build and maintain predictive models directly on top of cloud data warehouses. The service integrates with Snowflake, Amazon Redshift, BigQuery and Databricks and stores predictions back in the warehouse for immediate access. Data teams can reuse existing SQL and dbt skills to declaratively define features and models. The company opened a public beta after testing with select customers. Continual raised a $4 million seed round to fund growth and plans to use the investment to double its team over the next year. The team plans to expand the platform to support natural language processing, personalization and real-time use cases; co-founders Tristan Zajonc and Tyler Kohn bring experience from startups that were acquired.