Participated · Equity · Nov 2020

KisanHub offers a ‘seed to sale’ connectivity platform that combines crop intelligence with supply-chain intelligence to ensure farm yields reach processors and retailers in good condition. The platform integrates data from crops, stores, load dispatches, satellites and field sensors to support growers, field staff, procurement managers and management teams in decision-making. Target customers are agricultural enterprises that supply retailers and processors and that work with networks of contract farmers or own farmland. Sustainability is a central focus for the company; global brewer ABInBev has implemented the platform to help meet its 2025 sustainability goals. The company plans to use new funding to grow its business in the UK and Europe and to strengthen links with local and national governments. KisanHub was founded in 2013 and has previously raised a £1.75M seed round in 2018 and just over £3M in a Series A last year. KisanHub builds an agricultural and supply-chain data platform that uses big data analytics, cloud computing and machine learning to process satellite imagery, weather stations, soil sensors and other sources. Its product offers yield predictions, pesticide application monitoring, integrated market data, compliance information and crop protection recommendations to help agronomists, suppliers, processors and retailers manage contracts and decision-making. Rather than going direct to farmers, KisanHub targets agriculture enterprises and integrates with customers' existing software and Excel systems, while enterprise partners roll the technology out to growers. The company sources data via partnerships — including Planet Labs for satellite imagery — and integrates public data rather than building its own sensors. Founded in 2013 as a Cambridge Judge Business School spin-out, KisanHub operates in the UK and has an office in Pune, India, and works with partners such as AB InBev on programs like Smart Barley. Management says the £3.4m Series A will be used to continue platform development and implement the solution across multiple geographies, focusing on consolidating positions in the UK and India and meeting demand from a major undisclosed global food and beverage partner. KisanHub provides a Crop Intelligence Platform that leverages big data, cloud computing and machine learning to bring data-led decision-making to both producers and suppliers. The company supplies data to upstream and downstream members of the food supply chain to prove food provenance and increase production efficiency from farmer to retailer. KisanHub currently serves a user base of over 3,000 enterprises and farmers. Founded by Dr Sachin Shende (CEO) and Giles Barker (COO), the company is based in Cambridge, UK. It intends to use the new funding to continue development of its technology and to expand its sales team and customer success functions. The articles do not disclose prior financing details beyond this round. KisanHub has built a cloud-based enterprise farming platform that blends diverse datasets—farm, crop, operations, weather, satellite, commodities, machinery and sensor data—to generate actionable, data-driven decision points for growers. The platform is intended to help forecast pest and disease risk, optimize irrigation timing and volumes, and schedule field operations based on predicted weather, with the aim of boosting yields while reducing inputs such as pesticides and water. Typical customers are enterprises that source produce from networks of farmers and supply processors or supermarkets; end users include individual farmers and enterprise staff. KisanHub reports a user base of over 1,000 farmers and multiple large enterprises. The company says it will use new funding for R&D, sales and customer support to expand its offerings and commercial footprint. KisanHub is partnering with NIAB to develop technical solutions for farmers and farming enterprises and to leverage NIAB’s crop research expertise.

Participated · Series B · Jun 2020

SQream develops a GPU-accelerated SQL analytics platform designed to process and query very large datasets for enterprise use. Its product targets verticals such as semiconductors, manufacturing, telecoms, financial services and healthcare, and its disclosed customers include Orange, Samsung, LG, Alibaba and PubMatic. The company claims significant performance and cost advantages, stating it can analyze up to 20x more data and up to 100x faster (and more recently claims up to 90% reductions in ingestion and preparation times, footprint, and up to 80% cost reductions). SQream acquired Panoply in 2021 to expand connectivity to hundreds more data sources. The team originated in 2010 and leaned on Nvidia GPUs early to enable parallel processing for BI, ML and AI workloads. Future plans noted by management include doubling down on North American growth and R&D to explore next-generation processors (optical, quantum and others). SQream develops and markets SQream DB, a data analytics acceleration platform designed to enable enterprises to analyze massive data stores. SQream DB is available both on premise and in the cloud and is used by global enterprises to scale the amount of data they analyze to hundreds of terabytes and more. The company is led by CEO and co-founder Ami Gal and is based in Tel Aviv, Israel. SQream raised $39.4M in a Series B+ funding round. The round was led by Mangrove Capital Partners and Schusterman Family Investments, with participation from existing investors including Hanaco Venture Capital, Sistema VC, World Trade Center Ventures, Blumberg Capital, Silvertech Ventures and Alibaba Group. The company intends to use the funds to recruit talent and to accelerate advancements in technology, cloud innovation, and customer delivery platforms; in conjunction with the financing Charlie Federman (Silvertech) and Roy Saar (Mangrove) joined SQream’s board. SQream develops SQream DB, an SQL analytical database that leverages thousands of parallel processing cores in NVIDIA GPUs to speed large-scale data analytics. The company says customers can analyze up to 20x more data, up to 100x faster, at as little as 10% of the cost. Unlike other GPU databases such as Kinetica and MapD that rely on in-memory storage and are limited to roughly 5 TB, SQream was built to scale to hundreds of terabytes. The Series B capital will be used to add new features to SQream DB and to grow sales, marketing and delivery teams while deepening focus on China and other regions. SQream has a collaboration with Alibaba Cloud that will give Alibaba Cloud users access to the GPU database starting in October, and new Asian customers include Thai operator AIS and India’s ACL Mobile. The company has raised a little over $40 million to date and was founded in 2010 in Tel Aviv.

Participated · Series B · Jun 2020

Connecterra’s core product is a data platform that powers two applications: Ida for Farmers (a farmer-facing sensor and insights product) and Enterprise (a farm advisor/consultant app). Ida for Farmers is sold in 18 countries and the Enterprise app is used with farmers and advisors globally. The company uses AI to generate heat, health and performance insights and to enable data-driven decision making across the dairy value chain. Connecterra was co-founded by CEO Yasir Khokhar and Saad Ansari in 2015 and is focused on advancing its platform capabilities. Following the recent investment, Datamars acquired the Ida sensor business and took a majority share in the company, while Connecterra remains independent to continue development of Enterprise. Management says the partnership will accelerate scale, bring higher-quality cross-value-chain data, and unlock new insights and innovations to support sustainability and productivity goals. The Ida team is joining Datamars to maintain and support existing farmer customers as the companies integrate technologies. Connecterra, founded in 2014 and headquartered in Amsterdam, develops Ida, a predictive intelligence platform that combines proprietary sensor hardware, animal data, third-party enterprise data, and machine-learning algorithms. Ida has evolved from sensor tech to a full-stack technology and AI platform that provides farmers and industry stakeholders with actionable insights to improve farm and value-chain efficiency. The company operates in 16 countries and aims to empower animal farmers of all sizes to increase productivity while reducing the environmental footprint of animal agriculture. With the new funding, Connecterra plans to accelerate the growth and deployment of Ida and democratize access to its technology to millions of farmers. Management cites COVID-19–driven digital transformation as increasing demand for sustainable and efficient farming practices. The raise also positions Connecterra as one of the largest Series B financings for a European livestock-tech company and among the largest Series B rounds for a Dutch agtech startup focused on farm animals. Connecterra builds Ida, an AI-powered dairy farmer assistant that processes wearable-sensor and farm data to detect health issues, reproductive timing, and feeding problems while continuously improving via automated learning. Ida detects mastitis and lameness at least 24 hours before they become critical, identifies cows on heat and optimal insemination timing, and flags digestive disorders such as ketosis. The company is testing features to predict calving and to identify cows most efficient for breeding. Connecterra integrates multiple data sources rather than centering on the sensor, and targets farmers with herds from about 50 to 10,000 cows. It has several thousands of subscribers and works with larger industry clients including Danone. Ida is available in Canada, the US and Western Europe, with interest from markets including Ecuador, South Africa, and Mongolia. Connecterra plans to use new funding to further develop its technology, expand into new markets, and grow its team by hiring field technicians and account managers in the US and Europe. Connecterra, founded in 2014 and led by CEO Yasir Khokhar, develops a dairy health service combining sensor technologies and machine learning. Its core product is a wearable device that monitors herds in real time and transmits data to a cloud platform for analysis and prediction of behavioral patterns. The platform's insights aim to help farmers improve milk production per animal and optimize breeding cycles. The company will use proceeds from its $1.8M seed round to further develop its machine learning platform, grow its team, and accelerate trials and market delivery. Connecterra is supported by Microsoft through the Bizspark Plus Program. The company is based in Amsterdam and targets the dairy industry with its sensor-plus-cloud service.

Participated · Series B · Mar 2020

Five (formerly FiveAI) developed sensor-equipped test vehicles and a suite of testing and measurement tools for autonomous driving. The company has pivoted from designing and operating its own fleet to a B2B model, licensing software to carmakers and the wider autonomous-service ecosystem. Its tools focus on assessing perception accuracy and diagnosing errors that propagate from perception into planning. Five has been a partner on the London government-backed StreetWise project and says insurers and others can use its testing output to determine risk and pricing. Co-founder and CEO Stan Boland remains at the helm, and Direct Line’s Gus Park is joining Five’s board. Five has raised $77 million to date and announced a $41 million Series B; the company said its valuation is up on its last round but did not disclose details.

Participated · Series A · Oct 2019

Sensat builds a visualization platform that collects and delivers infrastructure data, translating physical sites into digital twins to help owners and construction partners plan, coordinate, and track project performance. The software surfaces hidden risks and helps teams deliver large infrastructure programs on time and within budget. Customers named in the article include AECOM, Connect Plus, Heathrow, Kier, Morgan Sindall, Network Rail, and WSP. The company plans to use new funding to accelerate international expansion and product development, underpinning infrastructure automation. Sensat was founded by James Dean and Harry Atkinson; CEO James Dean said the firm will serve utility customers in the UK, the US, and beyond. The company reportedly aims to become Europe’s first-ever trillion-dollar company. SenSat builds AI-driven "digital twins" that create accurate, up-to-date, machine-readable representations of real-world locations. Its Mapp platform enables infrastructure companies to interact with worksites digitally and apply digital automation to improve decision-making. Mapp is used by more than 30 international infrastructure companies. In a project with Murphy Group for the U.K. National Grid and the Triton Knoll offshore wind farm, SenSat digitized a 52 km underground transmission line and says this reduced time on site by 200%. The company says its technology improves safety, cost-efficiency, waste generation, project collaboration and reduces carbon generated in projects. CEO James Dean describes the goal as building an "intelligent ecosystem" — the third platform — to translate the real world into a form understandable to AI, with plans to broaden application across offline industries. Financially, SenSat has just completed a $10 million Series A led by Tencent. SenSat builds high-resolution digital replicas of real-world locations by photographing environments (using autonomous drones) and infusing real-time spatial datasets from open and proprietary sources. Its platform delivers "simulated realities" that enable large-scale machine learning and data analysis to solve complex physical-domain problems. The company initially targets infrastructure construction to automate manual design tasks, reduce design-phase time and cost, and produce validated best-option designs that can save millions. Beyond construction, SenSat is researching applications for autonomous-vehicle simulation to train and test agents in realistic real-world conditions. Founded in 2017 and based in the U.K., the startup says its simulations include fine details such as street furniture, lane markings and signage to support reinforcement-learning and safety use cases. It will use newly raised capital to further develop its technology and expand its San Francisco office.