Accelerators
By lowering barriers to entry in both knowledge acquisition and market participation, accelerators are catalyzing a new era of distributed innovation, where anyone with an idea can potentially contribute to solving global challenges.
Superconductors in the network of innovation
In the realm of accelerators, we're democratizing the tools of progress and dismantling barriers to innovation. From AI-driven data analysis to cutting-edge scientific research platforms, from revolutionary work technologies to transformative educational systems, we're equipping individuals and small teams with the power once only available to massive institutions.
These technologies are fundamentally rebuilding the infrastructure through which knowledge and ideas propagate, solutions are built and shared, and people engage in problem-solving at both local and global scales, ushering in an era of unprecedented individual and collaborative potential.
Sectors in Accelerators
Click on a sector to learn more:
Data & AI
Synthesizing cognitive architectures to boost cosmic intelligence.
An expedited exploration of what minds can do, unbound by the organic constraints that governed their initial emergence, automating and amplifying learning processes that have unfolded over eons.
Generative AI stands out as an area with immense potential. Far from being a tool merely for imitation, this technology is at the forefront of creative and analytical innovation. It enables creators to blend algorithmic complexity with artistic vision, resulting in unique music, literature, and works of art that may surpass conventional creative processes. In the business sector, its impact is equally profound, offering novel ways to approach marketing, product design and development, and customer engagement.
Turning to computer vision and voice recognition, which will imbue systems with human-like abilities, these rapidly evolving fields present a myriad of challenging problems. In computer vision, the focus is on developing systems that can not only see but understand and interact with their surroundings — a feat that requires a deep understanding of both the technology and the environment in which it operates. Voice recognition technology is advancing beyond mere speech transcription to nuanced understanding and response, creating opportunities in areas ranging from interactive customer service to integrated vehicle systems.
Machine learning platforms are offering an increasing number of features that make them more user-friendly, bridging the gap between high-level theoretical concepts and practical, real-world applications. No longer reserved for the tech elite, they offer opportunities for experimentation and innovation to a wide range of users, extending from natural language processing to predictive analytics and decision-making systems. This democratization is further bolstered by the emergence of no-code platforms, which make AI functionality accessible to non-technical users.
Lastly, synthetic data — data that is generated to have the same statistical properties as real-world data, which may be limited in volume or restricted in use — is addressing some of the most pressing challenges in the field, particularly around data scarcity and privacy issues. Its utility extends beyond the mere augmentation of training datasets; with tools such as de-identification, bias elimination, and balancing, the synthetic datasets being built are instrumental throughout many industries for model training and simulations. Synthetic data is indispensable in creating realistic scenarios for a range of applications, from automotive testing to physical system simulations that allow for the design of advanced aerospace components.
Conversational AI for healthcare that facilitates communication between healthcare professionals and patients, providing medical advice, appointment scheduling, and health-related information
AI video creation and animation tools capable of generating videos with synthetic human faces, mimicking speech and facial movements
No-code AI tools for artists that enable them to integrate AI into their workflows for tasks such as converting photos into videos with captions and subtitles
AI-powered code editors and assistants that provide integrated development environments (IDEs) and code editors with autocompletion, proactive debugging, code generation, unit test creation, documentation writing, and code conversion assistance
Query generation for data retrieval that generate SQL and NoSQL queries based on natural language input, simplifying data retrieval for non-technical users
Cloud-based natural language data query platforms that allow business users to ask data-related questions in plain language, with AI generating the necessary queries to collect the required data
Low-code development platforms driven by AI to help developers rapidly build applications with minimal manual coding
Privacy-preserving image data generators that are capable of detecting and masking identifiable features in image data, producing statistically matched by de-identified faces for privacy-sensitive applications
AI music generation platforms that allow users to create original, royalty-free music by customizing parameters such as length, tempo, composition, instrumentation, and genre for various applications
Automated patent application generation tools to simplify the patent application process by generating flowcharts, block diagrams, descriptions, and abstracts
Nanosatellite-based wildfire monitoring platforms that utilize nanosatellites, equipped with thermal-infrared data intelligence, to monitor wildfires, detect small fires, predict droughts, estimate biomass loss, and monitor energy infrastructure
Synthetic data generation for computer vision training which generates perfectly labeled digital images for training computer vision models with applications in ID verification, XR (extended reality), driver monitoring, pedestrian detection, virtual try-on, teleconferencing, and security
Visual data analysis platforms designed to analyze various types of visual data, including photos, videos, thermal, and infrared data, offering insights and intelligence with computer vision algorithms
Street-level image capture and analytics platforms on which users can capture and share street-level images which are processed using computer vision techniques to create immersive views or extract useful information
Digital food analysis and sorting platforms that employ computer vision and ML to assess the quality of food commodities and automate the sorting of fruits and vegetables based on visual characteristics
Agricultural management with computer vision that assists farmers in managing irrigation and monitoring crop health by analyzing visual data from agricultural fields
Identity verification and fraud detection solutions that utilize computer vision for identity verification, fraud detection, and automated digital identity authentication, comparing biometrics to identification documentation
Collision avoidance tools in space operations that use data from planes, satellites, and drones to enhance safety in space operations by employing computer vision for collision avoidance
Speech recognition and voice authentication solutions that capture and recognize customers’ intent from spoken words, and include text-to-speech capabilities for responding to user queries or commands, with applications in customer service and voice assistants
Voice AI stacks for wearables that offer a comprehensive set of voice-related functionalities, such as wake-word recognition, speech-to-text conversion, intelligent response selection, and text-to-speech capabilities, often used in in-ear voice assistants, smartwatches, and smartphones
Transcription and customer experience AI solutions that are trained on large customer experience datasets using natural language understanding (NLU), natural language processing (NLP), deep learning, and other AI techniques, and are utilized in various industries such as healthcare, finance, retail, and telecoms to understand, analyze, and respond to customer interactions as well as handle authentication tasks
NLP model training and generation platforms focused on training NLP models, including large language models (LLMs), with capabilities such as semantic search, question answering, summarization, document similarity, information extraction, and content generation
Deep learning and AI analytics platforms that are designed for deep learning and interpretable AI, catering to a wide range of ML tasks and providing tools for understanding model decisions
Model library and access platforms that offer access to pre-trained models for tasks such as image generation, custom persona creation, and shareable chatbots
End-to-end ML and data science platforms that allow users to build, train, and deploy ML models, offering infrastructure for running models in various applications
Cloud-native neural search solutions powered by AI and deep learning for neural search, enabling users to search for information across different data formats, supporting multimodal AI tasks such as text generation from images, prompt engineering, and video subtitling
AI-assisted ML Ops platforms that assist in ML operations by selecting the best algorithms based on data, training models, deploying models, and monitoring their performance
Custom deep learning models for business processes that offer models trained on various data types such as text, images, and documents to automate specific business processes
Collaborative data analysis and modeling platforms that support collaborative data analysis, modeling, data preparation, integration, analysis, visualization, and model deployment
AI platforms for predictive models that can handle various data types, such as location data, text, images, and documents, with options for both code-free and code-first approaches
Cloud-based ETL platforms that perform Extract, Transform, and Load (ETL) functions for processing, transforming, and exploring large datasets, as well as build, test, and deploy ML models, including ETL for structured and unstructured data
Automated ML platforms that automate tasks such as data labeling, feature engineering, model selection, and model tuning, providing visualizations and mathematical methods for explaining ML models
Generative AI solutions for privacy-sensitive industries that employ generative AI to create synthetic data replicating the statistical patterns and complexity of real data, primarily designed for privacy-sensitive industries such as healthcare, finance, and insurance
Synthetic data for computer vision training specifically catered to industries like automotive, security systems (object and motion detection), and smart offices
Production-like synthetic data solutions that mimic production data to create safe, de-identified data for testing, development, quality assurance, and various business applications, which can support scientific inquiries, process optimization, and decision-making
Real-time synthetic test data generation solutions that generate real-time synthetic test data specifically for unit testing purposes and can integrate with test data and test automation to accelerate continuous integration / continuous deployment (CI / CD) pipelines
Hyperspectral and physics-based synthetic data platforms that combine hyperspectral rendering, accurate sensor simulation, and cloud data production to generate synthetic data with physics-based quality, used for simulating various conditions, such as lighting, weather, and physical conditions for applications in the automotive and autonomous vehicle industry
Behavior augmentation with validation tools that augment existing datasets by extracting behavior patterns, completing missing data, balancing data, and eliminating biases, and providing validation tools to visualize similarities between the original and augmented datasets
Bayesian Statistics, Linear Algebra, Optimization Theory, Discrete Mathematics, Logic, Graph Theory, Combinatorics, Information Theory (entropy, data compression), Numerical Analysis, Differential Geometry, Functional Analysis, Dynamic Systems, Control Theory, Game Theory, Category Theory.
ML, Deep Learning, Computational Creativity, Cognitive Science, Image Processing, Pattern Recognition, Signal Processing, NLP, Acoustics, Linguistics, Data Science, Machine Learning, Computer Graphics, Computer Science, Software Engineering, Distributed Systems, Data Engineering, Transformer models, Variational Autoencoders (VAEs)., Neural network architectures, High-performance computing, GPUs for real-time processing, Cloud computing, Voice Biometrics, Microphone Array Technology, Edge Computing, Privacy-preserving techniques (like differential privacy), Data Augmentation methods, ML Frameworks (TensorFlow, PyTorch), Big Data Processing Tools (Hadoop, Spark), Automated ML tools, Deployment and Monitoring Technologies, Scalable Infrastructure Solutions (Kubernetes).
ML/AI Engineering; MLOps; AI Cybersecurity; Computer Vision Engineering; Natural Language Process (NLP) Engineering; Multimodal AI Engineering; Software Engineering; Data Engineering; Systems Engineering; DevOps Engineering; Data Science.
Scientific Research
Decentralizing discovery through collaborative brainpower and fluid resource allocation.
The constraints that historically stifled innovation are fading into obscurity, replaced by inventive funding solutions and open-source initiatives that are recharging the potential for exploratory research, with AI acting as a catalyst for rapid scientific progression.
New funding models in scientific research are challenging traditional grant and funding mechanisms. For-profit institutions are now actively engaging in basic science with the potential for commercialization, fostering a symbiotic relationship between research and entrepreneurship. Concurrently, academic-philanthropic hybrids are emerging, enabling researchers to pursue high-impact studies. Young researchers are also receiving financial support to embark on high-impact research immediately after obtaining their degrees, reducing the traditional grant-waiting period that characterizes academia.
Open source and open science initiatives are changing the way scientific knowledge is created and built upon. By advocating for the free exchange of data, methodologies, and findings, these movements are breaking down barriers to access and collaboration. This openness accelerates the pace of discovery and innovation, allowing researchers from diverse backgrounds and disciplines to contribute to and benefit from collective knowledge. Open science platforms are also facilitating peer review and publication processes, democratizing the dissemination of and access to scientific information.
Distributed and decentralized approaches leverage the power of distributed networks and communities to conduct research across geographical and institutional boundaries. By decentralizing the research process, these approaches harness the collective intelligence of a global community of researchers, citizen scientists, and enthusiasts.
AI tools are driving innovation across the research landscape. High-throughput lab automation with AI is accelerating drug discovery in cloud-based labs. AI-powered literature management systems are streamlining researchers’ workflows by assisting in literature search, data extraction, and even hypothesis generation. These AI-enhanced capabilities are further complemented by platforms for AI-driven research data management and analysis, offering researchers powerful resources for navigating the complexities of modern scientific inquiry.
For-profit basic science and research institutes in which researchers work on fundamental projects, such as longevity and evolutionary biology, with the aim of developing commercial applications. Some of these institutions also provide in-house research platforms and programs to incubate and support science startups, and focus on strategic and operational support for biotech startups. Research findings from these institutes are often made publicly available.
Focused research organizations (FROs) that focus on specific research problems or areas, addressing critical challenges in fields like brain-architecture mapping, open source tools for life sciences, longevity research, artificial general intelligence (AGI), metascience, climate tech, and the biology of aging. Key features of these institutes include a concentrated effort on targeted research areas, collaboration among experts in the field, and the development of open-source tools and resources.
Academic-philanthropic hybrids that support potentially high-impact research in which experts attempt to understand the root causes of complex diseases like neurodegeneration, cancer, and immune dysfunction, for example. Researchers in such settings tend to have more flexibility in their research direction, and more independence.
Funding for young researchers in which financial support and stipends are awarded to promising young researchers immediately, or soon, after they earn their degrees. These organizations attempt to accelerate their research careers and mitigate the need for them to wait until later in their careers to receive the large research grants that those in academia must typically wait for.
Crowdfunding platforms for scientific research that allow researchers to seek support directly from the public and interested communities, and allow individuals to contribute to research projects that align with their interests.
Open access journals with peer review that publish scientific research, making it freely available to the public while maintaining rigorous peer review processes to ensure the credibility and quality of the research
Micropublishing platforms for high-impact research that enable researchers to quickly publish narrowly-scoped scientific reports without paywalls or fees, focusing on sharing high-impact research rapidly
Open source platforms for research and data that aim to make research and data both accessible and understandable, on which researchers can publish, analyze, and visualize data
Global research data sharing and preservation platforms that provide open-source web applications which allow users, including researchers and data collectors from various disciplines, to share, preserve, cite, explore, and analyze research data globally
Data visualization platforms focused on the comprehensive visualization of public data from various government sources to help users understand critical issues and make more informed decisions
Open science advocacy organizations that work to increase the openness, integrity, and reproducibility of scientific research by democratizing access to research, involving all stakeholders, and promoting open science practices
Non-profit open access publishers that focus on making scientific research publications freely accessible to the public, prioritizing open access to scientific knowledge over traditional publishing models
Collaborative research data and materials exchanges that facilitate the sharing of research data, open peer reviews, and materials exchange across laboratories, aiming to reduce duplication and enhance collaboration
Guides for best practices in open research that provide open, free guides with information and resources for researchers to use at the initiation of their research projects to ensure reproducibility and quality in scientific research
Open data science competition and learning platforms that host data science competitions where participants can find, publish, explore, and build models on datasets as well as access learning resources for coding and best practices in data science
Open source tools for survey research that provide researchers with a toolkit to analyze survey data, such as advanced statistics and machine learning for data analysis
Distributed research groups with open source tools consisting of researchers who collaborate remotely and often build open source tools in the process of conducting research, leveraging digital technologies to facilitate collaboration, share research findings, and develop tools for the wider scientific community
Independent non-profits for mentorship and collaboration that make such opportunities accessible and free to all researchers by offering research training, free compute resources, conferences, and lecture series to support scientific advancement
Decentralized, community-owned research collectives that are dedicated to funding and advancing early-stage research and typically involve collective decision-making processes to allocate resources and support research projects
Online life sciences research collectives that provide and utilize open tools and infrastructure for research, helping scientists find and access funding opportunities, and connect with collaborators while emphasizing transparency and open science principles
Scientific research repositories that offer mobile and web app environments for efficient collaboration on scientific research in which researchers can share articles, discover papers, upvote articles, ask questions, and leave comments on research work
AI tools for organizing, sharing, and citing research papers by providing a centralized location for researchers to manage references
Research paper search engines that use research papers exclusively to produce answers to questions and facilitate information retrieval, prioritizing scholarly publications as a knowledge source
LLMs for paper summarization which can extract key points from scientific and research paper and help researchers quickly grasp the essential information from lengthy, complex documents
AI-powered paper rewriting tools that assist researchers in rewriting scientific papers in a technical and professional tone, improving the clarity and readability of research publications
NLP tools for citation analysis and metrics that analyze citations, assess the quality and impact of research papers, and provide visualizations and metrics related to citations to help researchers evaluate the scholarly influence of scientific papers
Cloud-based research and development platforms that automate various processes and manage workflows involved in scientific research, designed primarily for querying, browsing, managing, and sharing scientific data and documents in the cloud
AI-powered literature management systems that can automate various parts of researchers’ workflows, such as helping them to find relevant papers, extract key claims, summarize data, and brainstorm ideas
Research and analytics platforms with IP management that provide comprehensive solutions for scientific and academic research, including trademark protection and intellectual property (IP) management, on which researchers can conduct research, manage IP, and protect their innovations on a centralized platform
Science as a Service platforms that offer on-demand research infrastructure and services for lab-less biotech companies, on which users can design, build, and operate research setups that are faster, more reliable, and more repeatable, with reduced capital costs
Open Source Scientific Tools; Blockchain and DAOs; AI Tools; Cloud Computing; High-Performance Computing; Data Visualization and Analysis Tools; Collaboration Platforms; Reproducibility Tools; Automated Scientific Experimentation Tools.
Data Science; Data Analysis; Research & Development; Statistics.; Computational Materials Science; Biostatistics; Bioinformatics; Computational Neuroscience; Computational Biology; and Systems Biology.
Edtech
Personalizing cognitive development through adaptive learning.
Expanding pathways to cultivate a global community of awe-seekers, the complexities of science and the intricacies of technology are becoming more widely available to those in pursuit, offering immersive and personalized learning experiences.
In various STEM edtech applications, there’s an increasing emphasis on hands-on learning experiences, including a focus on collaborative programming, robotics, and emerging technologies such as AI, drones, and 3D printing. The integration of interactive visual courses and online platforms allows for these experiences to reach audiences from children to professionals looking to change fields.
Math-specific edtech is marked by the expansion of interactive math tools and simulations for understanding the mechanics of, and building intuition for, the behavior of mathematical objects and concepts. The gamification of learning advances alongside the integration of adaptive learning technologies that personalize instruction and support individualized learning paths.
Bootcamps and alternative certifications give continuing learners many solutions available to choose from when launching self-directed studies. This growth of career-focused apprenticeships and training programs often also matches students with potential employers, particularly in the fields of coding and data science.
In simulation and immersive learning, the incorporation of the emerging technologies associated with virtual reality can help train pilots, surgeons, first responders, and others to react to rare but critical situations. It can also provide immersive experiences without any associated risks, transport students to distant or historic sites for field trips, and facilitate remote learning.
Collaborative robotics and coding platforms that provide shared environments in which students can code virtual and physical robots and sensors, learn coding, and control real-world hardware
Subscription learning services that offer a wide range of STEM experiences, including digital content, augmented and virtual reality, online learning modules, and hands-on activities
Online coding instruction for children through which experts in AI, machine assembly, and various tech-related topics give lessons on coding fundamentals, logic, and algorithmic thinking
Project-based coding platforms that teach students to code by engaging them in practical projects
Interactive visual courses in STEM subjects that offer engaging courses in subjects such as mathematics, physics, and computer science using visualizations
Educational experiences that integrate emerging technologies such as robotics, drones, AI, and 3D printing, allowing students to gain hands-on experience with cutting-edge technology
Personalized adaptive learning tools that use AI to tailor STEM content to individual students’ needs and learning styles
Career- and industry-specific training platforms that provide specialized training and education to prepare students for careers in fields such as biotechnology, cybersecurity, or data science
Professional development platforms for teachers that help them enhance their teaching methods and stay updated on the latest educational technology and approaches
Lesson-building and customization tools for teachers to create and customize lessons to meet students’ specific needs, incorporating interactive elements, multimedia resources, and real-world examples to enhance engagement
Interactive platforms with real-time assessment that offer virtual mathematics learning tools, digital tasks, practice exercises, and assessments of student comprehension based on problem-solving strategies employed to identify areas in which students may need additional support
Visual instruction platforms for conceptual understanding that focus on building deep understanding of mathematical concepts through hands-on tools, games, and activities, emphasizing spatial-temporal reasoning ability and helping students develop a strong foundation by visualizing abstract concepts
Game-based, interactive math simulations that engage students in active learning and application of mathematical concepts, encouraging critical thinking and problem-solving skill development
Adaptive mathematical instruction platforms that uses intelligent technology to track student interactions and adjust the level of difficulty and other parameters dynamically, taking into account students’ problem-solving strategies and not simply their input answers to provide targeted support
Career-focused training programs that provide education in areas like coding, data science, and technology, allowing students to gain practical, hands-on experience while learning relevant skills to prepare them for specific job roles in the tech industry
Upskilling and reskilling platforms for adult learners with a variety of courses and certifications in diverse fields to enable career transitions or advancements
Online learning platforms with career coaching that offer courses in tech-related fields such as software engineering, data science, cybersecurity, UI/UX design, and tech sales, providing integrated career coaching and support with resume building, interview preparation, and job placement
Remote and in-person coding bootcamps that offer intensive training programs in various disciplines like web development, software engineering, UX design, data analytics, and quality analysis
VR education and training platforms that allow users to organize presentations, courses, and events remotely, offering immersive experiences that simulate physical presence
VR tours for classroom use that offer immersive tours of historical sites via virtual field trip experiences
Immersive experimentation platforms that provide students with virtual environments in which they can conduct physics and chemistry experiments, allowing them to gain practical lab experience safely and effectively
Soft-skills training platforms that allow users to learn communication skills and develop effective communication techniques
Medical simulation training platforms that allow experts to create customized training scenarios for healthcare professionals, ranging from basic checkups to advanced surgical procedures
VR training platforms for high-pressure professions such as astronauts, pilots, first responders, and nuclear power plant employees to ready them for complex and high-stress events that occur infrequently but must be handled expertly
Educational Psychology, Cognitive Science, Computer Science, Data Science, AI & ML, AR & VR, Cloud Computing, IoT.
Quality, Analysis, & Testing; Systems Engineering; Software Engineering; Cybersecurity Engineering; Data Science; Curriculum Developer; Instructional Designer; Content Specialist; User Experience (UX) Research.
Work Tech
Reducing the time from concept to enterprise.
Tools that help scientists navigate from ideation to operational success, equalizing the entrepreneurial landscape and empowering research-based companies to adapt and grow rapidly.
X as a Service (XaaS) companies usually offer cloud-based software and/or infrastructure services that can be accessed on-demand by customers, who pay for these services either on subscription or usage bases. XaaS companies provide and maintain the digital infrastructure, software, and security measures required to use their products.
In remote work technology, collaboration and communication platforms are increasing in importance as teams require reliable tools for video conferencing, screen sharing, file sharing, messaging, and project management. Many of these services are cloud-based, as they enable users to collaborate from anywhere and at any time. Productivity and workflow tools are also popular, helping employees manage tasks, schedules, workflows, and projects. Video and audio tools, including those enhanced with AR/VR capabilities, are growing in use to help teams communicate, meet, and collaborate in real-time. AI is also important in automating repetitive tasks and helping employees analyze data and gain insights.
Automation and AI are also playing an increasingly important role in solopreneur and startup tech, as they can provide efficiency, analysis, and insights that allow solopreneurs and founders to move faster in building their businesses. This is especially true for automating sales and marketing processes, allowing small companies to grow more quickly and gain more customer engagement. Additionally, solopreneurs and startup teams can benefit from prototyping tools for UX and design that enable them to create and test user interfaces and even entire products quickly and easily, without the need for advanced design skills.
Collaboration and communication tools that provide platforms for teams to work together in real-time, offering features such as document editing, messaging, collaborative whiteboards, video calls, and virtual brainstorming sessions
HR and employee management platforms that streamline human resource functions, including tracking hour worked, managing benefits, payroll processing, hiring and onboarding, and fostering company culture
Customer engagement and support solutions that enable businesses to interact with customers in real-time through various channels such as email and messaging, and utilize ML to automate responses and provide personalized assistance
Sales intelligence platforms that equip sales teams with tools for lead identification, qualification, and connection, as well as provided ML-enhanced email assistance
Project management tools that support project planning, tracking, and collaboration as well as features like task management, whiteboards, dashboards, chat, goals, and shared documents
Network security management platforms that help automate the management of IT infrastructure, such as firewall management, threat monitoring, and the safeguarding of critical networks
Data and analytics platforms that process, store, and analyze data at scale, as well as offering ML capabilities for building and deploying models
No-code development platforms that empower users to create custom applications, websites, and booking systems without coding
Software development and automation platforms that streamline software development processes by testing code, managing releases to production environments, tracking versions, and translating code discussions into documentation
Collaboration and workspace management platforms that allow users to centralize and consolidate cloud documents, links, notes, tasks, and workspaces
Email management and productivity tools that assist users via instant scheduling, reminders, and mail merge capabilities as well as offering intelligent calendar assistants to optimize scheduling and reduce distractions
Communication and video collaboration tools that provide virtual environments in which users can conduct workshops, meet and chat, edit documents and videos, brainstorm, and interact via a variety of formats such as avatars for video, audio, and screen sharing
Meeting management tools that utilize AI voice assistants to transcribe meetings, take notes, and summarize key meeting points
Business naming and branding platforms that host competitions or use AI to create business names, logos, and other branding assets for businesses
Market research platforms that assist startups in identifying customer needs and suggesting new products through data-driven insights and feedback
Design and prototyping tools that help designers create responsive website designs, and create wireframes and mockups for websites, apps, and software
Marketing and PR tools that generate press kits for startups, including media releases, logos, and visuals, manage social media campaigns by planning, scheduling, and syndicating social posts as well as measuring ROI, and conduct keyword research, backlink analysis, and rank tracking to optimize SEO
Marketing and communication automation platforms that manage email, SMS messaging, push notifications, and chatbots
Presentation generation tools that transform data into engaging visual content such as slide decks, storyboards, and infographics, and use AI to create compelling presentations
Startup support and compliance platforms that offer startups services such as incorporation assistance, business name reservation, tax and accounting assistance, website building, domain registration, business email generation, and compliance support
Computer Science, Cloud Computing, Data Science & Analytics, AI & ML, Cybersecurity, Networking and Communication, DevOps, IoT, Edge Computing.
Software Engineering; Systems Engineering; DevOps; Quality, Analysis, & Testing; Project Management; Business Analysis; UX Research; Product Management; and AI Engineering.
Additional Deep Tech Sectors
Explore other sectors in the Deep Tech Ecosystem
