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highly experienced developers will create a brand new ERP system from scratch or customize your current systems with custom integrations.
Considering the complexity and newness of the technology, integrating AI and machine learning solutions into a business’s current IT stack can seem like a daunting task. That’s where comes in. Our AI engineers provide machine learning development services applicable to several different verticals, including healthcare, marketing, and banking.
Our team of expert AI developers program enterprise systems with advanced machine learning solutions to produce actionable decision models and automate business processes. We convert raw data from legacy software systems and big data providers into clean datasets for executing (multi-label) classification, regression, clustering, density estimation, and dimensionality reduction analyses, and then deploy those models across relevant systems.
We leverage deep learning software to generate insights from big data sources like practice management and hospital information systems, EMRs, and Health Information Exchanges (HIE). In addition to using machine learning engines to improve RCM operations, we help create systems that develop and test new drugs, study genes, automate prescription details, optimize triage prioritizations.
Our data software scientists write machine learning algorithms to create deep learning engines and Artificial Neural Networks (or Machine Learning as a Service). We develop custom MLaaS applications, with back- and front-ends built with Python, Django, AI Markup Language (AIML), and other technologies commonly used with machine learning systems. We design supervised, semi-supervised, unsupervised, active, and reinforcement neural networks.
We integrate machine learning programs with CRM and marketing automation software systems in order to conduct precision marketing, drill down on market segmentation, optimize pricing scenarios and demand forecasting, generate propensity models, score leads, and improve content recommendations for individual customers and market segments. We can also develop virtual assistants and chatbots.
Using machine learning solutions to improve data integrity and cybersecurity protocols in desktop, mobile, and web apps is key component of our application development process. We integrate and deploy and machine learning engines to help systems better identify malware, flag unusual user behavior, develop personnel-based risk models, and scale up Zero Trust Security (ZTS) frameworks. We also leverage neural networks
Our Fintech machine learning solutions for banks and financial institutions include user- and situation-based analysis for fraud detection, improved risk management and credit-scoring, portfolio diversification, intelligent customer service prompts, automated underwriting, and streamlined workflows. Our machine learning stock market solutions include High-Frequency Trading (HFT) program development.
We value our partners and are keen to work together with you.