Participated · Seed · Aug 2026

Attestable develops zero-knowledge proof technology intended to verify which calculations an AI system performs and what data it uses while keeping models and sensitive information confidential. The founders—CEO Yogev Bar-On, CTO Shahar Papini and VP of R&D Shahar Samocha—are mathematicians with backgrounds including Unit 8200, StarkWare and Safe Superintelligence. The company says it has achieved a mathematical breakthrough enabling rapidly verifiable proofs applicable to AI labs and critical organizational uses. Attestable’s stated longer-term ambition is to become part of the infrastructure and regulatory fabric for advanced AI systems used by labs, governments and large organizations. It currently employs about 15 people, primarily in Israel with a small team in California, and reports relatively low infrastructure costs due to its mathematically driven work. The company raised $20 million in November 2025 to grow the team and advance its technology.

Participated · Series A · Jun 2026

Jedify’s platform connects to enterprises’ knowledge sources via APIs to build a multi-dimensional context graph that captures relationships across entities, data, people, permissions, workflows, and terminology. Sources include databases, data warehouses and lakes, SaaS apps, BI tools, unstructured documents, code bases, Slack channels, and meeting recordings. The company’s context graph is model-agnostic, updates in real time, and is designed to inherit and enforce permissions from identity systems, file systems, SaaS tools, and databases while offering observability and governance tools. Jedify is targeting mid-market and large enterprise customers with mature data stacks and multiple data stores, and has seen interest from sectors such as gaming, industrials, and consumer packaged goods. At the time of the report it had between 10 and 20 early customers, including The Weather Company. Financially, the company has raised a total of about $33 million following the $24 million Series A.

Participated · Series B · Jun 2026

Founded in 2024 by Shay Levi, Larissa Schneider, and Adi Azarya, Unframe provides a managed delivery model and an open platform called The Framery to implement enterprise AI solutions rapidly. Its approach pairs core platform components with hands-on delivery so solutions can run in a customer's cloud, on-premises, or as a managed SaaS offering without tying customers to a single large language model. Commercially, Unframe reached $100 million in total contract value within its first twelve months and reported 400% net revenue retention, with roughly half of customers converting to paid contracts under an outcome-based pricing model. The company employs about 120 people across Cupertino, Tel Aviv, and Berlin. Near-term plans announced alongside the Series B include expanding delivery capacity, investing further in The Framery, and adding senior leadership to support growth.

Participated · Series A · May 2026

Ocean builds an agentic email security platform that analyzes the context of incoming email to detect AI-enabled phishing, impersonation and fraud. The company says it built a small language model tailored to quickly analyze emails, infer sender intent and evaluate messages against an organization’s context. Ocean reports reviewing billions of emails each month for customers including Kayak, Kingston Technology and Headspace. Founder and CEO Shay Shwartz brings a background that spans early hacking, top-tier cybersecurity roles connected to Israeli defense and intelligence projects (including work tied to Iron Dome), and experience at Axis prior to its acquisition by HPE; Oran Moyal is the company’s co-founder and CTO. Ocean emerged from stealth concurrent with its $28 million fundraise and has attracted both venture capital and prominent angel investors.

Participated · Series A · Feb 2026

Matia delivers a single platform that consolidates data ingestion, observability, cataloging and reverse ETL, giving developers end-to-end visibility and control over production data pipelines. Built for the AI-native era, it replaces fragmented point solutions and supplies the context needed for trusted, scalable data systems. The company has grown more than 10× in the past year as customers such as Ramp, Drata, HoneyBook and Lemonade standardize on its platform. Users report up to a 78 % reduction in total cost of ownership by eliminating multiple standalone tools. Matia is now developing an AI data engineer that will autonomously create pipelines, detect anomalies and run impact analyses, further easing operational burdens. Including its Series A, the company has raised over $31 million to fuel continued product innovation and go-to-market expansion.