verificient-technologies

Autonomous mobility service enabling driverless operation on urban roads

AI data platform for annotating text, audio, images, video, and 3D data, plus model evaluation

An open-source hardware platform offering sensors, communication modules, and edge computing devices for prototyping.

A computer vision development platform for managing datasets, training models, and deploying inference services.

Browser extension that automatically captures screen activity and logs to generate defect reports

A developer productivity platform supporting structured code reviews and incremental change management

Testportal is a versatile online skills and knowledge assessment platform that helps organizations efficiently create, manage, and analyze various types of exams, quizzes, and assessments. The platform offers a user-friendly question editing interface, supporting AI-powered intelligent test assembly, multiple question types, and extensive customization options. With advanced proctoring technologies—including AI-driven monitoring and secure timing—the platform ensures fairness and security during exams. Integrated with Microsoft Teams, it enhances collaboration and accessibility. Testportal delivers detailed data analytics and reporting, empowering data-driven decision-making in education, recruitment, and corporate training scenarios.

ExamOnline is a powerful online examination system designed to deliver high-stakes summative assessments for education and professional certification. It supports a wide range of question types, including multiple-choice, essay, and hand-drawn sketches, enabling complex exam formats. The platform features advanced remote proctoring capabilities, customizable exam configurations, and seamless LMS integration, all hosted on a scalable cloud infrastructure capable of supporting anywhere from hundreds to hundreds of thousands of concurrent examinees.

Sherlock AI is a comprehensive interview proctoring solution designed to uphold integrity in remote hiring processes. The platform seamlessly integrates with popular video conferencing tools such as Zoom, Microsoft Teams, and Google Meet to monitor candidate behavior during interviews. Leveraging advanced behavioral analysis, eye-tracking, keystroke dynamics, and pattern recognition, Sherlock detects various forms of cheating, including the use of external assistance, screen sharing, and unauthorized tools. The system provides real-time alerts and generates detailed integrity reports with timestamps and confidence scores, enabling recruiters to make informed decisions while maintaining minimal disruption to the candidate experience.

Evidently AI is a comprehensive solution designed to help teams build, evaluate, and maintain highly reliable AI products, covering both traditional machine learning models and large language model (LLM) applications. It includes an open-source Python library with 100+ built-in evaluation metrics, as well as a cloud platform that supports AI testing, monitoring, synthetic data generation, and collaborative workflows. Evidently AI enables users to detect data and prediction drift, perform regression and adversarial testing, and manage datasets and evaluations through an intuitive interface, ensuring AI quality throughout the entire product lifecycle.

Confident AI is a powerful evaluation platform built on the open-source DeepEval framework, designed to help teams systematically test and optimize large language model (LLM) applications. The platform supports a complete evaluation workflow—from dataset creation and custom metrics to continuous monitoring in production—enabling enterprises to compare different LLMs, detect regressions, and improve performance using industry-leading, scenario-based metrics and safeguards. Confident AI fosters collaboration between technical and non-technical team members, seamlessly integrates with CI/CD pipelines, and offers enterprise-grade capabilities including on-premises deployment, SSO, and HIPAA compliance.

Ragas is a powerful and flexible open-source library designed for evaluating LLMs and RAG pipelines. It offers a comprehensive suite of automated evaluation metrics covering dimensions such as factual accuracy, coherence, and relevance, while also supporting synthetic test data generation and online monitoring. Ragas enables benchmarking aligned with industry standards and allows for customizable evaluation workflows to meet diverse needs in research and production environments. Its strong integration capabilities help developers and researchers optimize and ensure the reliability of AI applications.