QVscribe
QRA’s tools streamline engineering artifact generation, evaluation, and prediction, refocusing engineers from tedious work to critical path development.
Our solutions automate the creation of risk-free project artifacts for high-stakes engineering.
Engineers often spend excessive time on the mundane task of refining requirements, with quality metrics varying across industries. QVscribe, QRA's flagship product, streamlines this by automatically consolidating these metrics and applying them to your documentation, identifying risks, errors, and ambiguities. This efficiency allows engineers to focus on more complex challenges.
To further simplify requirement authoring, QRA introduced a pioneering five-point scoring system that instills confidence in engineers. A perfect score confirms accurate structure and phrasing, while lower scores prompt corrective guidance. This feature not only refines current requirements but also reduces common errors and enhances authoring skills over time.
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Quaeris
Based on your interests, history, and role, you will receive personalized and recommended results. QuaerisAI provides near-real-time data access for all data. QuaerisAI enhances your data and document workload with AI.
To increase knowledge sharing and track performance, teams can share insights and pinboards. Our advanced AI engine transforms your inquiry to a database-ready language within micro-seconds. Data is nothing without context, just like life. Our cognitive AI engine interprets search terms, interests, roles, and past history to provide ranks results that allow further exploration. You can easily add filters to search results to dig into the details and explore relevant questions.
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Amazon Comprehend Medical
Amazon Comprehend Medical is a natural language processing (NLP) service that complies with HIPAA regulations and utilizes machine learning to pull health information from medical texts without requiring users to have prior machine learning skills. A significant portion of health data exists in unstructured formats, including doctors' notes, clinical trial documents, and patient records. The traditional method of manually extracting this data is labor-intensive, and attempts to automate the process through rule-based systems often miss crucial contextual information, leading to incomplete data extraction. Consequently, this unreliability renders the data ineffective for large-scale analytics, which are essential for progressing the healthcare and life sciences sectors, ultimately hindering potential improvements in patient care and operational efficiencies. By leveraging this advanced service, healthcare providers can unlock valuable insights and enhance decision-making processes.
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Lettria
Lettria presents a robust AI solution called GraphRAG, aimed at improving the precision and dependability of generative AI applications. By integrating the advantages of knowledge graphs with vector-based AI models, Lettria enables organizations to derive accurate answers from intricate and unstructured data sources. This platform aids in streamlining various processes such as document parsing, data model enhancement, and text classification, making it particularly beneficial for sectors including healthcare, finance, and legal. Furthermore, Lettria’s AI offerings effectively mitigate the occurrences of hallucinations in AI responses, fostering transparency and confidence in the results produced by AI systems. The innovative design of GraphRAG also allows businesses to leverage their data more effectively, paving the way for informed decision-making and strategic insights.
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