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Artificial Intelligence and Machine Learning Services
Artificial Intelligence Solutions, Machine Learning Services, and algorithms, supported by AI Consulting for Business, Data Science for Research, and AI-driven Analytics that power AI data analytics and AI-powered applications.
Empower Your Business with AI and Machine Learning
Artificial Intelligence (AI) and its branches, such as machine learning services, neural networks, deep learning, computer vision, and natural language processing, are phenomenal vehicles for business change, from deploying chatbots to AI powered platforms to automate processes and ultimately make smarter decisions.
At Statswork, we have the data science professionals and data scientist consultants capable of providing the end-to-end Artificial Intelligence Solutions and machine learning services that enable organizations to tap into the power of modern technologies.
We also have an area of specialization, called Data Science for Research, where we provide advanced analytics and insight to support scientific and academic innovations.
We provide the expertise needed to help you obtain the best value from your AI models by leveraging technologies like Python, Java, R, PyTorch, Keras, Caffe, Theano, TensorFlow, Apache Spark, Tableau, Power BI, Azure Machine Learning, MySQL, and more.
We provide ai-driven advanced analytics, ai data analytics and ai powered applications to ensure complete coverage of all resources associated with AI to propel your business.
Statswork Artificial Intelligence delivers world-class, dependable, and scalable experience to customers all over the globe. Our consultants work alongside your internal teams and stakeholders, creating a long-term partnership that focuses on ensuring an alignment in your business strategy and strategies for AI Consulting for Business digital transformation.
At Statswork we work with organizations to reduce costs, increase efficiencies, and enhance customer service using advanced Artificial Intelligence Solutions and Machine Learning algorithm development.
Requirement Elicitation & Engagement
Requirement Elicitation & Engagement is all about understanding the business need, diving deep into analysis, working with stakeholders, and ultimately aligning all of the goals. We will gather, refine, and elicit requirements in order to define a clear picture of the objective of the project. This all serves as a solid foundation to create a successful solution for the people who will ultimately use it.
Data Dictionary & Mapping Service
We provides organizations with improved data quality and consistency with its efficient
data dictionary mapping services.
We reduce errors from the data transformation and integration process ensuring your data is clean, accurate and consistent across all systems.
We assist organizations with metadata registration, entity-relationship modelling, and business logic rules development, which all help organizations to more effectively drives automated decision making, support and improve data governance, and ultimately provide more trustworthy insights for forecasting and analysis.
Business Rule Development & Decision Services
We offer powerful documentation and business rule development services designed to be the foundation for automating business logic and delivering on AI and Machine Learning Solutions. Our team will build rules-based logic and algorithms that sanitize, verify and enrich your data – adding capability for Machine Learning Services when appropriate. With expertise in technologies like TensorFlow and DeepLearning4J, and programming languages such as R, Python, Java, SQL and Apache Spark, Statswork will provide intelligent scalable algorithms aligned with your strategic business objectives. Statswork provides companies in all sectors with on-demand AI-enabled decision services that improve collaboration between stakeholders and have real-time visibility supporting Business Intelligence with AI.
Semantic Data Annotation & Labelling Services
Whether you are training image, video, text or speech recognition models, find the right ML training data with Statswork. We are experts in semantic data annotation and data tagging methodologies that drive deep learning solutions, pattern recognition and computer vision. Our experts will collect and label your data based on your specifications while providing accessible, reliable, and robust data tailored to your project through a variety of platforms, backgrounds, and environments including specialized applications such as ai in healthcare analytics.
Data Validation & Relevance
Data Validation & Relevance makes sure your data is accurate, consistent, and relevant for AI and analytics. We validate the data integrity, clean out inconsistencies in the set, and validate the relevance to the project goals. This process results in confidence in your inputs for accurate and effective outputs.
Advanced Algorithm Development for Modelling & Evaluation
Experience the full potential of AI and machine learning with our complete support. Statswork designs, builds, and evaluates advanced machine learning algorithms in your data architecture, image/video analytics, information management and visualization. Our services require various AI techniques including, neural networks, deep learning, natural language processing (NLP), and computer vision.
Statswork manages a global, experienced group to manage a large network of data collectors that compile diverse, high-quality training data, across various demographics, age groups, educational level, and ethnic backgrounds. We provide audio datasets for speech recognition, video datasets, image datasets, and handwritten/digital text datasets in multiple languages. Simply request and we can prepare datasets for your specific AI project including Custom AI model development tailored to your needs.
Data Analysis for AI & ML
When it comes to AI and ML, data analysis covers the cleaning, gathering, and analysing of data to uncover patterns that will drive intelligence systems. We prepare high quality data sets to train high performance and accurate AI and machine learning models. We guarantee data for driven insight to ensure higher level decision-making.
Algorithms for Data Visualization
We develop advanced data visualization algorithms to convert complex data into simplified, interactive visualizations of the data. To better design visualization, our team uses two- and three-dimensional coordinates, trigonometry and proportion, and we develop intuitive representations of data such as bar charts, line charts, radar charts, infographics and pie charts, our expertise also includes predictive analytics solutions to help forecast trends and support data-driven decisions.
We have experience in a variety of sectors, including defence, cybersecurity, education, marketing, agriculture, energy, etc. Our team has strong programming experience in R, Python, Java, SQL, Scala, Apache Spark, Hive, and SAS, and we utilize this programming skills to customize the visualization tools to fit the needs of our clients.
Our Industries
At Statswork we work with organizations to reduce costs, increase efficiencies, and enhance customer service using advanced artificial intelligence and machine learning algorithm development.
At Statswork we work with organizations to reduce costs, increase efficiencies, and enhance customer service using advanced artificial intelligence solutions and machine learning algorithm development. Our team of experts builds intelligent, scalable models to serve industries including healthcare, agriculture, manufacturing, supply chain, retail, and pharmaceuticals. While machine learning (ML) can be powerful and cost-effective, it also presents difficulties – things like memory complexity, uncertainty, and mobility. That is where we have the expertise. By outsourcing your ML algorithm development to Statswork, we can help you identify, choose, and deploy the right algorithm for your unique business.
We focus on automated deep learning algorithms, which include CNNs, RNNs, deep residual networks, and reinforcement learning methods, for analysis of big data. These models are highly effective for applications of predictive analytics, object detection, speech recognition, medical diagnosis, and many types of autonomous systems.
We use sophisticated neural networks auto encoders, LSTMs, and Deep Belief Networks, and assess model efficacy using, sensitivity, specificity, and metric ROC evaluations to arrive at the optimal performance of the model. Our deep models are designed to be accurate, efficient, and robust for real world applications.
As industries adapt to IoT devices and wearable technology, data privacy and security have become mission critical. Sectors like healthcare must ensure that patient data is protected. At Statswork, we create encryption algorithms such as AES, DES, RSA, Blowfish, E-DES, ElGamal, among others to protect sensitive information.
We use sophisticated neural networks auto encoders, LSTMs, and Deep Belief Networks, and assess model efficacy using, sensitivity, specificity, and metric ROC evaluations to arrive at the optimal performance of the model. Our deep models are designed to be accurate, efficient, and robust for real world applications.
We develop AI algorithms targeting wireless communication system applications. Specifically, we are working with 5G, AR/VR and IoT platforms. Our innovations optimize radio signal processing, channel estimation, signal detection, and compression sensing.
Statswork collaborates with software engineers to build algorithms that apply deep learning to end-to-end communication, enhancing the performance and security of mobile data networks.
Statswork is committed to creating innovative multi-objective optimization (MOO) processes that can help weigh competing real business goals to solve complex real-world problems. Our data science team uses many well-established approaches, like genetic algorithms, differential evolution, Pareto optimization, particle swarm optimization, ant colony optimization, simulated annealing, shuffled frog leaping algorithm and the analytic network process. Optimization approaches help decision makers identify the right trade-offs in product design, operating efficiencies, or strategic options, so that they can make well-informed, data driven decisions regardless of their industry.
We implement either text mining or web mining techniques as a method of extracting meaningful inferences from high-dimensional, unstructured sources of data. Our capabilities comprise of:
- Text Mining: Utilize SVM, Naïve Bayes, Decision Trees, Neural Networks and Generalized Linear Models to extract data from text
- Web Mining: Content mining, structure mining and usage mining (the latter of which also considers distinct methodological approaches such as an image or multi-discipline context) using methods such as Latent Semantic Analysis and clustering to assist in pattern identification.
- Statswork builds customized algorithms with specific design and implementation requirements, providing insights across the range of industry.
Encryption and Decryption Algorithm for Healthcare Application as per the HIPAA Security Rule
Today, industry is embracing the growing use of IoT-based wearable technology, which poses serious privacy and security concerns about data transfer and transaction log. In health care, security and privacy threats can put patients’ lives at risk.
At Statswork, we employed hybrid advanced cryptographic primitives that include DES, TDES, AES, E-DES, BLOWFISH, Paillier, RSA, and ElGamal, for a client who adheres to the HIPAA Security Rule. Statistics of the existing hybrid algorithm as compared to standard algorithms indicated greater than 99% performance accuracy.
Advanced Algorithms and Protocols for Wireless Communication Technology
As mobile data continues to explode, driven in part by the Internet of Things (IoT), and wireless applications become ever-more ubiquitous — think 5G, augmented reality (AR), virtual reality (VR), etc., the demand for future wireless communication systems will continue to overwhelm the ever-growing expectations and requirements of users.
Artificial Intelligence (AI) is playing a key role in overcoming the complexities of radio frequency (RF). At Statswork, we are providing AI-driven, machine learning (ML), and deep learning (DL) derived solutions for identifying and classifying radio signals in a timely and effective manner.
Solve Real-Life Challenges: Decide the Best Choice
By employing multi-objective optimization, we help clients solve and optimize several conflicting objective functions at the same time. Depending on the problem, we use solutions based on algorithms like genetic algorithms and differential evolution to express the trade-offs between competing objectives.
Evaluation of algorithms
Our data science team conducted a comparison of a client’s new algorithm against the standard algorithms based on performance metrics including sensitivity, specificity, and a receiver operating characteristic (ROC) curve to evaluate performance.
Thanks to the precise medical image annotation provided by the team, our AI model achieved clinical-grade accuracy. This directly contributed to our publication in the Journal of Medical Imaging and Health Informatics.
— CTO, HealthTech AI Startup,
- USA
We were impressed by the team's expertise in clinical text annotation. Their work helped us build an NLP pipeline that led to our successful article in the International Journal of Medical Informatics.
Lead Researcher, Clinical Research Organization,
- UK
The annotated dataset they delivered met all journal standards, and their adherence to HIPAA compliance was commendable. Our study was published in the BMC Medical Informatics and Decision-Making journal.
Principal Investigator, Healthcare AI Lab,
- Canada
The Statswork team helped us annotate and label a massive dataset for drug discovery, contributing to our manuscript accepted in Frontiers in Pharmacology. Their scientific accuracy was outstanding
Senior Scientist, Pharma Research Unit,
- IndiaData Dictionary Mapping
The Next Era of Data Entry
Reduces Errors and Boosts Efficiency
Artificial Intelligence (AI) is the general concept of machines being able to carry out tasks in a way that we would consider “smart.” Machine Learning (ML) is a select subcomponent of AI, in which machines improve performance on the tasks that they do by learning, without explicitly programming the machine for the specific task.
AI and ML can automate many tedious tasks, generate insight from data with proper analysis, improve customer service with chatbots, improve decision-making and functional ability. These benefits can be realized in finance, healthcare, retail, manufacturing and every other sector if there is enough measurable ROI.
Fraud detection in banking, predictive maintenance in manufacturing, recommendation systems in e-commerce, disease diagnostics in healthcare, and personalized learning in EdTech are common applications. Fraud detection in banking, predictive maintenance in manufacturing, recommendation systems in e-commerce, disease diagnostics in healthcare, and personalized learning in EdTech are common applications.
Both AI and ML depend on high quality, properly labeled data. The type of data could be images, text, audio, video, transactional data, sensor data, etc. depending on the use case. Good data that is clean and well-annotated is needed so proper models can be trained accurately and responsibly.
The prices and timelines are estimates only and depend on the complexity of the task. AI is much easier to access and more affordable today for companies of any size and complexity, because of scalable cloud infrastructure, pre-trained models and off-the-shelf tools.
First, identify a concrete problem or opportunity. Next, consult with AI specialists to evaluate the readiness of your data, determine how success will be defined, and select a model or platform that’s relevant for you (for example, a custom solution developed for your business or an off-the-shelf service).
In supervised learning, we train models from labeled data, which is appropriate for classification with labeled instanced or regression problems, while in unsupervised learning, we are training with unlabeled data to discover patterns or groupings. Unsupervised learning is typically appropriate for clustering and anomaly detection, as well as exploratory analysis of additional data where no labels are known.
Reputable AI firms comply with rigid data privacy, encryption, and compliance protocols (i.e. GDPR, HIPAA). Always vet your AI vendor’s security policies to make sure your data is anonymized and handled in a responsible manner.
In fact, most AI/ML applications are built using APIs and a modular architecture that enables the application to be integrated into current software platforms like CRM systems, ERP systems, and even custom databases. This makes it possible for the application to operate with an existing software platform seamlessly.
To aid in accuracy, continuous model monitoring, performance tracking, and re-training with recent data, are critically important. Many organizations choose to use MLOps (Machine Learning Operations) procedures to automate those responsibilities and ensure that models continue to perform.
