The Venture Codex

Led · Series A · Apr 2025

Hi Auto develops a SaaS conversational voice platform that automates drive-thru order-taking for quick-service restaurants. Its system delivers over 96% order accuracy and over 90% order completion rate, using advanced noise-cancellation and a specialized language model tuned to chaotic drive-thru environments. The product includes dynamic upselling that recommends add-ons based on store inventory, daypart, and weather, helping boost average ticket sizes. Customers include Bojangles, Checkers & Rally's, Lee's Famous Recipe Chicken, Burger King New Zealand, and Popeyes UK, and the company is running multiple paid pilots with top-tier QSR chains in the U.S. and abroad. Founded in 2019 by Roy Baharav, Eyal Shapira, and the late Zohar Zisapel, Hi Auto employs about 100 people worldwide. The company plans to use new funding to expand its footprint, refine its product, and scale deployments with leading QSR brands.

Participated · Series C · Apr 2024

Hailo, co-founded in 2017 by Orr Danon and Avi Baum, designs specialized processors to run AI workloads on edge devices. Its chips execute AI tasks with lower memory usage and power consumption than typical processors, targeting compact, offline and battery-powered devices such as cars, smart cameras and robotics. Hailo’s processors are used for object detection, semantic segmentation, image and video enhancement, and increasingly to run LLMs on edge devices including personal computers and infotainment electronic control units. The company says it has over 300 customers across automotive, security, retail, industrial automation, medical devices and defense, and employs around 250 people. It reports having $340 million in the bank; the recent capital is intended to enable Hailo to leverage opportunities in its pipeline and set the stage for long-term growth. Hailo and its leadership view growing demand for generative AI as further driving requests to process LLMs locally, supporting the company’s edge-focused expansion. Hailo designs AI chips and modules optimized for edge devices, targeting use cases such as smart cities, retail, industrial settings and next-generation automotive systems. Its Hailo 8 chip and accompanying modules are built to adapt to existing hardware and run custom neural networks with high efficiency and low energy use. The company supports common frameworks like TensorFlow and ONNX and is investing in software to broaden its offerings beyond hardware. Hailo has seen a surge in demand across multiple sectors, doubling the number of projects it is working on to about 100 in the last quarter. While some segments such as full autonomous vehicles have softened, demand overall has continued to rise and semi-autonomous and other deployments still translate into business. Hailo develops the Hailo-8 deep learning chip for edge AI, optimized for real-time image recognition and other inference tasks. The company’s architecture adapts resources to users’ custom neural networks, improving speed and energy efficiency and delivering about 26 tera operations per second. Hailo showed multiple demos at CES highlighting real-time image recognition performance. The new funding is intended to roll out the Hailo-8 and accelerate entry into new markets and industries. Targeted use cases include mobility, smart cities, industrial automation, and smart retail. With the Series B, Hailo’s total funding has reached $88 million. Hailo is developing a microprocessor, the Hailo-8, based on proprietary technology to deliver data center performance to edge devices for deep learning applications. The processor is high-performance, low-power and small-size, designed to enable embedded devices to process high-resolution video and other high-throughput streams in real time. Hailo positions the chip to serve a strategic focus on the automotive market while addressing surveillance, smart home, IoT, industrial, robotics, AR/VR and wearables. The company is opening registration for a Hailo-8 Fast Track program to let select customers evaluate initial samples and develop or prototype their own deep learning products. Led by CEO and co-founder Orr Danon, Hailo emphasizes enabling developers and customers across sectors to integrate its processor into devices. Hailo develops specialized deep learning processors for embedded devices. Its chips are aimed at running embedded AI applications such as drones, cars, smart home appliances and cameras. The company identifies the automotive industry as a key market and positions itself alongside Israeli startups like Mobileye. Hailo says it has redesigned processor architecture—memory, control and compute—to substantially boost deep learning performance. It will use the new funding to further develop its processors and expects samples to reach the market in the first half of 2019. Financially, Hailo announced a $12 million Series A round, bringing its total funding to $16 million.

Participated · Series A · Jan 2022

Addionics produces textured, three-dimensional copper and aluminum foil current collectors for lithium-ion batteries, using electro-deposition for copper and electroetching for aluminum. Its foils feature tiny holes and undulating peaks and valleys that increase contact between the foil and active material. The company says the design improves battery performance and efficiency and can potentially double battery lifespan, and that the collectors can work with a wide range of chemistries. Addionics plans to tailor collectors to different chemistries in the future to extract additional performance. The Israel- and U.K.-based startup recently raised a $39 million Series B to accelerate delivery of its current collectors and to explore new markets and geographies. Earlier this year it announced plans to build a $400 million factory in the U.S. and said it has letters of intent from U.S. automakers. Addionics develops patented Smart 3D Electrode architecture and a scalable electrode fabrication process that replaces traditional 2D layered electrodes, aiming to increase energy density, power, safety and lifetime without raising cost. Its drop-in solution is compatible with existing battery manufacturing lines and is paired with a proprietary AI algorithm to accelerate and optimize electrode design for varied applications. The company targets electric vehicles initially and is collaborating with automotive OEMs and suppliers in the U.S. and Europe to integrate with NMC, LFP, silicon, lithium polymer and solid-state chemistries. Addionics plans to commercialize by 2024 and will use funding to advance product development, expand the team, and increase activity in the U.S. and Germany. The company also highlights applications beyond EVs, including consumer electronics, stationary storage, aviation, defense and medical devices. Addionics has developed a scalable, patent‑protected “smart 3D structure” that redesigns battery architecture via 3D metal fabrication to reduce internal resistance and improve mechanical longevity and thermal stability. The company’s approach is chemistry‑agnostic, designed to enhance existing and future battery chemistries rather than replace them. Addionics says its technology can increase EV mileage, improve safety, and reduce cost and charging time, and could be applied to consumer electronics, medical devices, grid storage, drones, and more. Commercial traction is early: the company is working with an unnamed tier‑1 American automotive company on a proof‑of‑concept and testing Addionics cells in vehicles. Management aims to secure 3–4 major collaborations with world‑leading OEMs over the next year. Financially, the company has raised $6M in funding, which includes a $2.5M grant awarded through the European Union’s Horizon2020 program.

Led · Series C · Oct 2021

Tactile Mobility builds virtual sensors via an in-vehicle Tactile Processor (TP) installed in the chassis ECU and uploads sensor outputs to its Tactile Cloud to create tactility maps of vehicle and road "DNA." Its product suite includes tire grip estimation, tread-depth and tire-stiffness sensing, weight estimation, aquaplaning, vehicle-health and micro-collision sensors, produced using signal processing and machine learning. The company monetizes data through a revenue-share model with OEMs and by selling analytics and maps to OEMs, tire companies, insurers, transport authorities, municipalities and Tier 1s. Tactile has completed more than 30 proofs of concept and pilots with seven OEMs and reached production-level deployment with BMW; the TP is present in 2.5 million BMW vehicles annually. The startup has grown from about 25 employees to 40 and plans to hire up to 20 R&D staff this year. Recent funding will support development of additional virtual sensors, expanded product offerings and further buildout of its cloud platform. Tactile Mobility provides a software platform that collects first-order data from vehicles’ built-in, non-visual sensors (wheel speed, wheel angle, RPM, paddles position, gear position) and analyzes it to deliver real-time, actionable insights. Its sensing and data offerings describe and analyze the evolving state of vehicles, roads, and vehicle-road dynamics for customers across sectors. The company’s insights are used for road planning and management, tire condition tracking, insurance applications and more. Tactile has executed partnerships with 10 road authorities and municipalities globally (including the UK, Germany, Israel, Singapore and Detroit) and with six vehicle manufacturers, including BMW and Porsche. The company plans to use the new funding to support demand for its technology and data, expand go-to-market operations, and strengthen traction among vehicle manufacturers, insurers and tire manufacturers across the US, Europe and Asia. Co-founded in 2012 by Boaz Mizrachi, Yossi Shiri and Alex Ackerman, Tactile is based in Haifa, Israel. The company has raised over $20M in total funding following this investment. Tactile Mobility, founded in 2012 and based in Haifa, Israel, builds a tactile-sensing platform that derives non-visual road-condition insights from vehicle signals such as wheel speed, wheel angle, RPM, paddle and gear position. Its software feeds real-time tactile insights back into vehicles’ onboard systems and uploads anonymized data to the cloud to produce a crowdsourced, constantly updated map of road conditions. The company has launched a mapping service in Haifa with plans to roll out to several other cities and has already collected roughly 10 million kilometers of road data across four continents. Tactile has signed paid proof-of-concepts with five major OEMs, including Ford, and holds RFPs with major European automakers. The company recently appointed Amit Nisenbaum as CEO and reports total funding raised of $9 million.

Participated · Equity · Dec 2020

Innoviz Technologies Ltd. announced it expects to receive $200 million in funding through a private placement. The company entered into a subscription agreement for 20,000,000 common shares at $10 per share for gross proceeds of $200,000,000. The transaction is being led by Antara Capital LP and was raised at a post-money valuation of $1,375,000,000. The board of directors has approved the transaction. The closing is targeted for the first quarter of 2021 on the date of, and immediately following, the consummation of a merger and is subject to regulatory and stockholder approvals and other customary closing conditions. The company has entered into a 180-day lock-up agreement from issuance. Innoviz develops solid-state lidar sensors and bundled perception software aimed at autonomous vehicles and robotaxis. Its flagship product, InnovizOne, is an automotive-grade lidar system the company says can be produced and sold at roughly 90% lower cost than its first-generation system. Innoviz packages perception software with its sensors and partners with OEMs and Tier 1 suppliers such as Magna, HARMAN, HiRain Technologies and Aptiv. The company has secured commercial design wins, notably with BMW for series production starting in 2021. With the new funding, Innoviz plans to scale production, expand manufacturing capacity, and grow in key markets including the U.S., Europe, Japan and China. It also intends to invest in R&D to develop next-generation products and improved software performance. Innoviz Technologies, based in Kfar Saba, Israel and led by co-founder and CEO Omer Keilaf, develops solid-state LiDAR sensing solutions aimed at the mass commercialization of autonomous vehicles. The company leverages proprietary System, MEMS and Detector designs to deliver long-ranging, accurate sensing at cost and size targets for automotive adoption. Its product lineup includes InnovizPro, a development platform for automakers, Tier 1 suppliers and tech companies, and InnovizOne, an automotive-grade LiDAR device targeting levels 3–5 autonomy. InnovizPro was slated to be available in Q1 2018, while samples of InnovizOne were planned to begin shipping in 2019. The company said it will use the new funds to grow its team across R&D, operations, marketing and business development. At the time of the article the Series B had been extended and the company reported total funding of $82M. Innoviz makes solid-state LiDAR sensors designed for greater reliability (no moving parts) and improved sensing across challenging conditions such as bright sunlight. The company offers a development-focused product, InnovizPro, and plans to begin delivering InnovizPro to automakers starting in the first quarter of next year. Its automotive-grade InnovizOne sensor is slated to be available as a manufacturing sample sometime in 2019. Innoviz raised $65 million in a Series B from strategic partners and auto suppliers to help push toward mass production of its LiDAR modules. The funding will also support the company’s computer vision work and formation of new partnerships. Strategic investors Delphi Automotive and Magna International—both positioned to supply automakers with autonomous-driving components—are already working with Innoviz to integrate its technology into OEM systems. Innoviz Technologies develops compact solid-state Lidar sensors aimed at autonomous vehicles. The company says its prototype is working internally and it plans a public demo by the end of this year, with a mass-production-ready product targeted for mid-2018. Innoviz aims for an under-$100 price point at volume by reducing components and expects a package smaller than 5cm x 5cm x 5cm. The company declined to disclose technical details but said it took a different technical approach to the scanning element than competitors such as Quanergy and MIT. Beyond hardware, Innoviz is expanding its team to build complementary software for mapping and localization, object detection and tracking, and sensor fusion. Financially, Innoviz raised $9 million in a Series A round closed in February.