AI & Machine Learning Technologies.

The AI Revolution is at Hand. Ready to Innovate?

Automate business processes and operations, discover deep insights through big data analytics, and engage patients, customers or prospects more effectively through CapeStart’s balanced roster of AI and machine learning technologies.

Unlock Your Organization’s Potential with AI.

Our innovative, in-house team of data scientists, AI engineers and data analysts have years of experience applying AI and machine learning technologies to organizations just like yours across the healthcare, telecom, legal, retail and financial services industries. Scroll down to learn more about what we can do for your organization.

AI & Machine Learning Technologies.

CapeStart knows AI and machine learning. Want to learn more about the robust technologies we can apply to your organization? Have a look below.

Computer Vision.

Deep learning algorithms and state-of-the-art machine learning models help pathologists and radiologists catch potentially fatal conditions earlier, leading to better health outcomes. These models detect the slightest presence of a condition – even at early stages often missed by human doctors due to sensory limitations – leading to faster, more accurate diagnoses of patients with serious conditions. Facial image recognition, for example, can be used to identify rare genetic disorders while object detection algorithms can de-identify personally identifiable information (PII) in medical records, enabling them to be used for commercial and research purposes without risking non-compliance with regulatory requirements.


Offering and Expertise: Software Engineering, ProNotate for Labeling, Medical Image Annotation by Radiologists, Prebuilt Models, Datasets

Chatbots & Virtual Assistants.

Chatbots and virtual assistants help patients or clients find what they’re looking for from your organization faster, cheaper, and more effectively. Bots can also help healthcare professionals book appointments or update medical records, while assisting patients with prescription refills, bill payments, next step recommendations or scheduling assistance. CapeStart’s machine learning models and pre-annotated datasets feed the learning algorithms of virtual assistants and chatbots with accurate, relevant Q&A datasets.


Offering and Expertise: Intent Classification, Software Engineering, Annotation Platform & Services, Prebuilt Models, Datasets

Robotic Process Automation (RPA).

RPA, also known as software robotics, helps organizations automate mundane, repetitive, rule-based tasks to streamline business processes, lower costs, and increase task accuracy. Claims management, billing, patient onboarding, report management, data management, the transfer of paper records to digital, and prescription management are all manual, everyday tasks easily automated with the right experience and technology. RPA helps streamline these and other processes, improving results by reducing system errors.


Offering and Expertise: Human-in-the-Loop services, Software services to convert processes to bots, Multiple domain experts, Content moderation

Natural Language Processing (NLP).

NLP can be used to extract insights from unstructured medical, pharmaceutical, legal, or any other big text datasets with lightning speed and more accurate results than manual analysis. Healthcare organizations can use medical NLP to classify handwritten physicians’ notes, pathology reports, surgery notes, and drug reactions for improved pharmacovigilance, while organizations of all stripes can use it to analyze sentiment in customer or patient feedback.  Drug or medical device developers, as well, can use NLP frameworks like SpaCy to perform named-entity recognition (NER) on clinical trial data to extract relevant information.


Offering and Expertise: Expert labeling, ProNotate platform, Software services, Prebuilt Models, Datasets, on going Human-in-the-Loop services

Speech Recognition.

Identify incredibly nuanced data points from audiological data, such as mood changes or emotional states, using advanced speech recognition algorithms. Speech recognition can be used as a tool to streamline the use of electronic health records through automatic transcription, benefitting clinicians and patients and enabling NLP analysis, and as a platform for creating chatbots or other bots able to perform tasks based on voice commands.


Offering and Expertise: Application development, Speech user interface design, Prebuilt Models, Datasets

Machine Learning.

The applications for machine learning models throughout healthcare and other industries are everywhere: From clinical trial candidate selections, to resource allocation and appropriate staffing predictions based on multiple data sources, to assessing high-risk clients or patients, to predicting the demand of ICU beds or managing inventories. Cardiac doctors can use time series analysis on electrocardiogram (ECG) and phonocardiogram data to diagnose heart issues, pharma companies can use quantum machine learning algorithms to more efficiently develop life-saving drugs, and geneticists can use AI algorithms to sequence DNA and predict the impact of possible genetic variations. Deep learning and artificial neural networks, meanwhile, allow machine learning systems to learn and adapt on their own, reducing the need for time-consuming and ongoing ML model training.


Offering and Expertise: Software Engineering, ProNotate for Labeling, Labeling Services,  Prebuilt Models, Datasets, Audit and testing services

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