Creative Destruction Lab (CDL) is a no-fee/no-equity organization that delivers an objectives-based mentoring program for massively scalable, pre-seed stage, science- and technology-based companies. Its nine-month program allows founders to learn from experienced entrepreneurs, increasing their likelihood of success. Founded in 2012 by Professor Ajay Agrawal at the University of Toronto’s Rotman School of Management, the program has expanded to thirteen sites across seven countries: Seattle, Oxford, Paris, Atlanta, Estonia, Wisconsin, Vancouver, Calgary, Montreal, Berlin, Melbourne and Halifax.

Creative Destruction Lab (CDL)

SensiML

SensiML is a SaaS analytics toolkit company targeting IoT and wearable device developers, systems integrators, and OEMs.  SensiML’s suite of software and cloud service allows embedded sensing device developers to rapidly create accurate, customizable, learning sensor algorithms that run directly and autonomously on sensor devices and requires zero embedded coding or data science expertise to develop.

SensiML Corporation, a subsidiary of QuickLogic, provides AI software solutions for IoT Edge devices. The company's flagship product, the SensiML Analytics Toolkit, is an end-to-end development platform that enables the creation of ultra-low-power IoT endpoints that can transform raw sensor data into meaningful insights at the device level. SensiML's technology supports a wide range of hardware, including 8/16/32-bit MCUs, Arm Cortex-M class and higher microcontroller cores, Intel x86 processors, and AI/ML-optimized SoCs.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

SensiML is a subsidiary of QuickLogic, which offers AI software solutions for IoT applications.&nbsp;

Generating, collecting, and analyzing enterprise data will never be the same.

Edge Computing

SensiML Expands Platform Support to Include the RISC-V Architecture

Infineon Technologies

To offer developers a process to capture data from Infineon XENSIV sensors, train Machine Learning (ML) models, and deploy real-time inferencing models directly on ultra-low power PSoC 6 microcontrollers (MCUs).

Integrated solutions that handle the end-to-end processes of developing, training, deploying, and monitoring ML models.

To simplify the development of AI code for edge IoT applications, enabling efficient, low-power AI models on Microchip's microcontrollers.

Platforms and frameworks that help developers build and train ML models.

QuickLogic

SensiML continued to operate as a seperate division under QuickLogic following the acquisition, offering software tools for developing AI and machine learning capabilities for Internet of Things (IoT) edge devices.

SensiML Corporation, a subsidiary of QuickLogic, provides AI software solutions for IoT Edge devices. The company's flagship product, the SensiML Analytics Toolkit, is an end-to-end development platform that enables the creation of ultra-low-power IoT endpoints that can transform raw sensor data into meaningful insights at the device level. SensiML's technology supports a wide range of hardware, including 8/16/32-bit MCUs, Arm Cortex-M class and higher microcontroller cores, Intel x86 processors, and AI/ML-optimized SoCs.SensiML's AutoML solution simplifies the process of creating machine learning models for sensor data with minimal manual intervention. The company's tools are designed to generate compact, optimized sensor inference code for IoT device applications, with models as small as 5KB. SensiML's technology supports various applications, including acoustic event detection, gesture and human activity recognition, anomaly detection, keyword spotting, and vibration classification.In June 2024, SensiML launched Piccolo AI, an open-source AutoML solution for IoT Edge AI development, which aimed to democratize access to AI technology and enable developers to contribute to ongoing advances in Edge AI. The open-source project includes a suite of resources, including a central hub for project information, a community forum, and a GitHub repository with free access to the AutoML codebase.

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 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.

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

SensiML is a subsidiary of QuickLogic, which offers AI software solutions for IoT applications.&nbsp;The company's flagship product, the SensiML Analytics Toolkit, provides an end-to-end development platform for building intelligent IoT endpoints that transform raw sensor data into actionable insights directly at the device level. The toolkit covers the entire development process, including data collection, labeling, algorithm generation, firmware auto-generation, and testing. SensiML's software is compatible with various hardware, including Arm Cortex-M class microcontrollers, Intel x86 processors, and QuickLogic SoCs with FPGA optimizations.Piccolo AI is an open-source AutoML solution that SensiML offers for edge AI/ML development. It is a hardware-agnostic platform that supports various edge processors and silicon vendors, enabling developers to create ultra-compact edge ML code with sizes as small as 5KB. Piccolo AI offers a no-code GUI and a Python SDK interface, allowing users to switch between point-and-click and programmatic workflows.Additionally, SensiML offers Data Studio, a platform for collaborative sensor data management in AI/ML projects. This tool is designed to streamline data preparation tasks, making it easier for teams to manage and prepare sensor data for machine learning model development.Key customers and partnershipsSensiML caters to companies in various industries such as industrial, consumer, commercial, healthcare, agriculture, and environmental.

DC Blox offers edge colocation centers, including disaster recovery services, mainly targeting the underserved markets in the southeastern region of the US. Its clients range from enterprises, cloud providers, government entities, and educational institutions, among others. DC Blox connects users to any destination globally through its private network and ecosystem of global communication partners.DC BLOX’s data centers are located in Birmingham, AL; Huntsville, AL; Chattanooga, TN; Greenville, SC, and Myrtle Beach, SC, with others in development near Atlanta and Berkeley County, SC as of March 2024.In 2023, DC Blox embarked on an <a href="https://finance.yahoo.com/news/dc-blox-set-build-hyperscale-133500449.html">expansion strategy</a>, with the development of a hyperscale-ready data center campus in Rockdale County, Georgia, being one of the latest and most significant projects. This new campus was set to feature a sprawling 750,000 sq ft space with a total power capacity of 216MW, supplied by Georgia Power. The project was designed to include a dark fiber ring around the Atlanta metropolitan area, enhancing the connectivity for its tenants and bolstering the company's network infrastructure.Funding and financialsDC Blox raised USD 187 million in funding from Post Road Group and Bain Capital Credit, in March 2021. It aims to use the funds to refinance existing credit facilities, add liquidity to its balance sheet, and expand data center capacity in new and existing locations.

DC Blox

Edgeworx offers the Eclipse ioFog Engine, an application platform that turns hardware into an intelligent edge node. The company allows users to extend their cloud to the edge and run and monitor microservices from any infrastructure. It caters to both developers and operations users to uniformly manage hardware and software.In November 2023, Edgeworx, <a href="https://sp-edge.com/companies/728459">launched Edgeworx Cloud</a>, an enterprise-grade edge computing platform, on the Google Cloud Marketplace. The platform enables enterprises to deploy and manage containerized edge applications from any network without needing to operate their own Kubernetes clusters. It provides secure data management across edge devices, micro-services, hosts, and clients, as well as a hardware-agnostic agent for synchronizing deployments of heterogeneous fleets.Key customers and partnershipsEdgeworx's technology benefits from a range of partners including Docker, Kubernetes, Microsoft, and Red Hat, among others.

Edgeworx

Crosser offers a real-time analytics platform for enterprise Internet of Things (IoT), primarily for industrial IoT (IIoT).The Crosser Platform enables real-time processing of streaming or batch data, to enable industrial IoT, data transformation, analytics, automation, and integration, all to improve the utilization of industrial assets. The platform moves machine data into the cloud while also enabling edge analytics, hybrid integration, and factory floor integration.Key customers and partnershipsCrosser has a robust portfolio of partnerships with leading technology, AI, and ML providers. Some of its notable partners are AWS, Microsoft, SAP, Agora, Oracle, IFS, Siemens, ZEDEDA, and Intel.Funding and financialsIn March 2021, Crosser raised EUR 3 million (~USD 3.6 million) in Venture funding led by NTT DOCOMO Ventures and Montan-Ventures-Saar, with existing investors Industrifonden, Spintop Ventures, 42 Cap, Almi Invest, and Norrlandsfonden also participating.

Crosser

Zededa was founded in 2016 and came out of stealth in 2018 to offer an open edge ecosystem to provide visibility, control, and security when deploying apps remotely on the edge, regardless of the hardware used. The company commercially launched its remote management software in January 2021. The platform allows developers to avoid vendor lock-in and additionally offers support for industries facing more complex edge applications. Moreover, Zededa allows enterprises to mix old and new technology seamlessly, making it for industries like surveillance. The red company has an office in Pune, India, in addition to its headquarters in San Jose, California.In July 2023, the company released a suite of edge application tools including “Edge Access,” which provides access controls and audit tracing for edge deployments. Users can remotely access edge devices from any location at any time without requiring backend configuration or specialized skills.<a href="https://sp-edge.com/updates/24108">In November 2023,</a> the company announced a new service named ZEDEDA Edge Kubernetes Service, offering a fully managed Kubernetes service for distributed edge.Key customers and partnershipsThe company has a substantial customer base, with numerous Fortune 500 enterprises spanning various industries like manufacturing, renewable energy, telecommunications, and healthcare. Prominent clients include Rockwell Automation, Emerson, Agora, and VMware.Zededa collaborates with leading technology firms through its global ZEDEDA marketplace, granting partners direct entry to edge operations teams. This marketplace facilitates swift scalability for customers across thousands of edge devices with one-click deployments, eliminating the need for extensive professional services. Notable partners encompass Microsoft, Suse, Juniper Networks, AWS, Rafay Systems, Aviatrix, Fortinet, and more.Through Zededa's technology partnerships, customers can procure hardware devices and have them shipped directly to their intended destinations. This adaptable approach reduces solution expenses and empowers technology providers to offer optimal value to their clientele. Noteworthy partners in this initiative comprise Dell, Supermicro, HP Enterprise, Equinix, and others.During 2023, Zededa collaborated with Applied Digital in August, a company specializing in advanced digital infrastructure for High-Performance Computing, to use ZEDEDA's management and orchestration software. In May, it also partnered with Avassa, a container management platform tailored for edge environments, to facilitate comprehensive orchestration across the entire stack, ensuring security and visibility from hardware to edge applications.Zededa is also a part of multiple industry consortiums to use edge computing to address emerging issues faced by the energy industry. These collaborations include the OSDU Forum as well as LF Energy and Project Alvarium, which are part of the Linux Foundation (a non-profit group to standardize and support the adoption of Linux). In December 2022, the company extended its partnership with Emerson to integrate its edge application management and orchestration solution into Emerson’s DeltaV automation system. This would in turn enable Emerson’s customers to extend this automation system into the distributed edge.Funding and financialsIn <a href="https://sp-edge.com/updates/26448">February 2024</a>,it raised USD 72 million in a Series C funding round led by Smith Point Capital, with participation from Hillman Company, LDV Partners, Endeavor Catalyst Fund, Juniper Networks, and others. The funds were directed toward expanding sales and marketing endeavors and speeding up R&amp;D.In January 2023, the company announced that it had grown its annual revenue growth by 300%, and nodes under management by 250% over the previous year.

Zededa

SmartCone Technologies Canadian company specializes in developing Internet of Things (IoT) based safety and monitoring solutions.It mainly offers its services for securing dangerous worksites, controlling bicycle lane traffic, managing vehicle fleets, monitoring traffic incident scenes, crowd control, and site security surveillance, among others. Its devices range from wearables and torches, to constellation positioning systems.In July 2022 SmartCone Technologies announced HeatGuardian, a spin-off company dedicated to providing applications and micro-climate weather stations to calculate localized heat exposure to aid individuals and workers in staying safe during periods of hot weather. This initiative was undertaken in partnership with the Human and Environmental Physiology Research Unit at the University of Ottawa.Key customers and partnershipsThe company mainly caters to customers in the mining, logistics, and energy industries. Some notable customers are Nokia, IBM, DHL, and Exelon.In November 2021, the company partnered with the Centre for Integrated Transportation and Mobility (CITM) to build a database architecture and platform that would capture data from all Smart Mobility Networks, both 4G &amp; 5G elements, Intelligent IoT Nodes, C-V2X device, IoT devices, and other sensors installed on the Smart Mobility Networks.In January 2021, AutoGuardian by SmartCone became one of 37 firms in automotive company AISIN Group’s “open innovation initiatives.” This was in response to AutoGuardian’s successful proof of concept relating to vehicle-to-infrastructure (V2I) technology. AutoGuardian uses a SmartConeTM device, equipped with a camera, AI, radar, and onboard edge computing to offer non-line-of-sight alerts by using data such as vehicle speeds, vehicle and pedestrian count, and behavior estimations.Funding and financialsIn April 2019, Smartcone received CAD 187,500 in Debt Financing backed by FedDev Ontario.

SmartCone Technologies

Companies that provide software to enable users to run their applications at the edge.

Companies that produce hardware and infrastructure such as routers and servers that are not embedded on devices.

Companies that provide software that facilitates analytics, cyber security, and IoT at the edge.

Companies that produce embeddable hardware, including microchips, that allow devices to transmit and process data.

Companies that provide software used in data centers to carry out operations effectively.

Companies that offer datacenter infrastructure to facilitate edge computing, including micro data centers deployable to more strategic locations.

Some players in the embedded hardware segment offer microprocessors for running GenAI applications at the edge of enterprise networks

Most companies operating in this industry operate under a B2B SaaS model

Includes companies that support AI/ML workloads and offer IoT data management

All companies in this industry offer edge computing solutions

Offers solutions for managing IoT device data on the edge of users' networks

Includes micro processor manufacturers that particularly target AI workloads for the edge

Many service providers partner with telecom services to leverage 5G to reduce edge application latency

ANALYST_QUICK_TAKE

PROMINENT_CATEGORY

<div>

SensiML, an AI software solutions provider for IoT applications, has incorporated RISC-V processor support into its AI development tool suite. This development enables developers to utilize SensiML's open-source <a href="https://sp-edge.com/updates/31913"> Piccolo AI </a> AutoML tool to generate ML models for Edge devices using open-source hardware and software.

</div> Analyst QuickTake: 
 The integration of RISC-V support aligns with SensiML's strategy to provide transparent and accessible solutions for the IoT market. This integration enables developers to design and deploy Edge AI solutions while retaining control over their product architecture. RISC-V's open-source framework offers flexibility and cost savings compared to proprietary systems.

SensiML

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