Search results for PreProduct

Aetion® Substantiate is an advanced analytics application designed to transform real-world data into decision-grade evidence, meeting regulatory standards with precision and transparency. It enables researchers to implement high-impact studies that generate reliable evidence to inform regulatory, payer, and clinical decisions regarding the safety, effectiveness, and value of medical treatments. Key Features and Functionality: - No-Code Dynamic Workflows: Guides users step-by-step through study implementation, eliminating the need for manual coding. - Implementation Guardrails: Automatically adjusts workflow settings based on study type, with analytic options pre-populated with best practices. - Plain Text Audit Trails: Provides downloadable audit logs, including relevant methodologies, ensuring transparency and reproducibility. - Reusable Study Components: Allows saving and reusing measures and patient cohort definitions across studies and teams, enhancing efficiency. - Custom Analyses: Offers access to Analytic Cohort Files in secure coding environments like RStudio, combining programming flexibility with auditability. Primary Value and Problem Solved: Substantiate addresses the complexity of real-world evidence generation by providing structured, bias-aware workflows for cohort building, study execution, and transparent reporting. It ensures robust, reproducible, and transparent evidence, enabling researchers to efficiently implement studies from concept through regulatory submission. By offering a scientifically validated application, Substantiate empowers safety teams, real-world evidence teams, and health economics and outcomes research teams to generate interpretable evidence, maximize efficiency, and clearly communicate the comparative value of treatments in key populations.

Fluidize is an AI-driven platform designed to revolutionize scientific computing by automating simulations and experiments. It accelerates research and development (R&D) processes for scientists and engineers by streamlining the setup, execution, validation, and scaling of computational tasks. By integrating seamlessly with existing simulation stacks or operating as a comprehensive end-to-end solution, Fluidize enhances efficiency and collaboration in scientific workflows. Key Features and Functionality: - Integration with Existing Tools: Fluidize can wrap over your current simulation stack, allowing for smooth incorporation of open-source or licensed software without disrupting established workflows. - Automated Scaling: The platform auto-scales computational pipelines using cloud computing resources, ensuring that simulations run efficiently regardless of their complexity or size. - Dependency and Version Management: Fluidize automatically handles dependencies and versioning, reducing the risk of errors and ensuring reproducibility across experiments. - Collaborative Dashboards: It offers shared dashboards that enable real-time collaboration among team members, facilitating instant communication and knowledge sharing. Primary Value and Problem Solved: Fluidize addresses the common challenges in scientific R&D, such as time-consuming setup procedures, complex dependency management, and scalability issues. By automating these aspects, the platform allows scientists and engineers to focus more on innovation and discovery rather than on the intricacies of computational processes. This leads to faster development cycles, improved reproducibility of experiments, and enhanced collaboration among research teams, ultimately accelerating scientific breakthroughs.

WYKYK AI Deep Scan is an AI-driven penetration testing platform that combines automated exploitation with validation by certified ethical hackers. Instead of a one-off annual pentest, AI Deep Scan continuously tests an organisation's external attack surface (web applications, APIs, domains, subdomains and cloud endpoints), attempts real exploitation of discovered weaknesses, and delivers reproducible, evidence-backed findings with severity, business impact and remediation steps. Key capabilities: - AI-driven reconnaissance and attack simulation across 2,250+ checks, including OWASP Top 10, misconfigurations, exposed services, credential leaks, brand protecion and business-logic flaws - Human validation: a network of 40+ ethical hackers & developers confirms exploitability, eliminating false positives - Reproducible proof-of-concept exploits for every confirmed finding - Executive summaries and technical reports generated per scan, mapped to NIS2, DORA and ISO 27001 requirements - Continuous or on-demand scheduling, with re-testing after remediation - PenPortal dashboard with a 100-point security score, trend tracking, findings hub and team collaboration AI Deep Scan is built for IT managers, CISOs and security teams at mid-sized organisations and enterprises that need to prove continuous security testing to auditors, customers and regulators, without the cost and lead time of traditional manual pentests. Data is hosted in region (EU, UAE) on isolated infrastructure. WYKYK is headquartered in the Netherlands with offices in India and Dubai.

HRDQ is a publisher of training resources for developing great people skills. The company offers a wide range of research-based products that include paper and online assessments, experiential games, simulations, and reproducible training programs.

Get all the info you need to understand what the user is experiencing, right from your helpdesk software. Bugpilot automates the collection of screenshots, steps to reproduce, user info, browser logs, and more.

Carcha Seal is a self-hostable license server and SDK set for vendors who sell installed desktop software. Instead of a proprietary binary that phones home, the app ships only a public key and verifies a short-lived, Ed25519-signed JWS lease on the device — online or offline, with a grace period. Licenses follow per-product policies: node-locked or floating/concurrent seats, perpetual or subscription, trials, and feature-based entitlements. Air-gapped machines activate and renew by exchanging a request file and a license file. Run the whole server yourself — your signing key, your database, no runtime call home — or use the hosted service with a 14-day trial. SDKs cover Electron/Node.js, .NET and C++.

OpenCFU is a free software that should facilitate (and render more reproducible) the enumeration of colony forming unit (CFU). You can simply run the program on your computer and input pictures of plated bacterial colonies (or other cells).

CAAPS allows you to automate the mundane tasks associated with accounts payable processing. Reducing the workload for everyone in your business. CAAPS gives you complete visibility and consistent, reproduceable quality every time you process an invoice.

Di-Freeze is a Laboratory stock management software that fully reproduces your storage locations, it keeps each inventory record up to date, previews the usage history & tracks the amount of storage space available for your clinical trials.

PromptML (Prompt Markup Language) is a domain-specific language designed to structure AI prompts as code, enabling prompt engineers to define prompts in a deterministic and explicit manner. By breaking down prompts into distinct sections—such as context, objective, instructions, and metadata—PromptML enhances clarity and standardization in prompt engineering. This structured approach facilitates better collaboration, version control, and reproducibility, addressing the inherent ambiguity of natural language prompts. Key Features and Functionality: - Structured Prompt Definition: Utilizes annotations like `@context`, `@objective`, and `@instructions` to clearly delineate different components of a prompt. - Domain-Specific Language (DSL): Tailored specifically for prompt engineering, offering a syntax influenced by XML and Ruby, making it intuitive for users familiar with these languages. - Explicit Metadata Inclusion: Allows embedding of metadata within prompts, such as constraints on length, tone, and difficulty, to guide AI behavior more precisely. - Version Control Compatibility: The code-like structure of PromptML prompts facilitates integration with version control systems, enhancing collaboration and tracking of changes. - Parser Integration: Provides a Python-based parser (`promptml.parser.PromptParser`) to convert PromptML code into structured data, enabling seamless integration into AI workflows. Primary Value and Problem Solved: PromptML addresses the challenges of ambiguity and inconsistency in AI prompt design by offering a standardized, code-based approach. By explicitly defining each component of a prompt, it ensures clarity and reproducibility, leading to more reliable AI outputs. This structured methodology not only enhances collaboration among prompt engineers but also streamlines the prompt development process, making it more efficient and less error-prone.

Foundry is a comprehensive training and evaluation platform designed for web-native AI agents. As AI progresses from static models to dynamic agents capable of real-world interactions, Foundry provides the necessary infrastructure to ensure these agents operate reliably within the complex and ever-changing web environment. By offering high-fidelity simulations of real websites and workflows, Foundry enables rigorous, reproducible testing of agents on end-to-end tasks under realistic conditions. Key Features and Functionality: - Deterministic Environments: Foundry offers frozen content with website versioning, allowing for consistent evaluation runs. This ensures that performance differences are due to agent behavior rather than changes in web content. - State-Based Evaluation: The platform provides structured state JSON and manages state on the backend, enabling users to define custom evaluation and reward functions based on specific criteria. - Informed Data Collection: In instances of agent failure, Foundry collects demonstration data for behavioral cloning or similar simulation examples for on-policy reinforcement learning, facilitating continuous improvement. Primary Value and Problem Solved: Foundry addresses the challenges faced by AI agents operating in web environments, such as silent failures caused by unforeseen layout shifts, DOM mutations, and race conditions. By providing a controlled and reproducible testing environment, Foundry allows researchers and developers to build reliable agents through iterative improvement. This is particularly significant given that over 60% of global knowledge work is mediated through browsers. Agents that can effectively navigate and automate web-based tasks unlock substantial economic opportunities across support, sales, and internal operations.

Automates time consuming and repetitive tasks during image analysis set-up. Increases reproducibility and detects complex phenotypes by eliminating the biased selection of handcrafted features. Saves time by quickly being re-applied in different experimental settings. Seamlessly integrates with Genedata Screener for image data analysis.

Nexus aide les équipes de recrutement à examiner de grands volumes de candidatures sans perdre la capacité d'expliquer leurs choix. Vous décrivez le poste ou collez une offre d’emploi existante, et Nexus rédige la publication avec vous. Les candidats postulent via un lien public, sans compte à créer. Nexus lit chaque CV (PDF, Word ou texte) et le structure : compétences, expérience, formation, disponibilité. Vous choisissez les candidats à noter et voyez le coût avant que quoi que ce soit ne soit publié. Chaque candidat reçoit un score de correspondance composé de cinq critères avec des pondérations fixes : compétences (30 %), adéquation sémantique (25 %), expérience (20 %), localisation (15 %) et un examen de cohérence par un modèle linguistique (10 %). Quatre des cinq sont calculés en code et sont entièrement reproductibles. Chaque score est décomposé à l'écran, chaque compétence requise étant marquée comme confirmée par le CV ou encore à vérifier. Nexus ne prend pas de décisions d'embauche. Trois étapes nécessitent toujours une personne : approuver le besoin d’embauche, approuver l’offre d’emploi et approuver les refus. Les e-mails de rejet sont rédigés pour qu'un recruteur les approuve ; Nexus ne les envoie jamais lui-même. L’équité est testée et non supposée. Les noms, photos et coordonnées sont exclus de chaque évaluation. Les CV appariés qui ne diffèrent que par le sexe, l'origine suggérée par le nom, l'âge, le lieu de résidence ou la langue du CV sont notés par rapport au même emploi, avec une limite de 3 points sur 100. Lors de notre dernière série d'appels de modèles réels (octobre 2026), l'écart le plus important était de 1 point pour les attributs personnels et de 2 points pour le langage du CV. Ces tests utilisent des profils synthétiques ; il ne s’agit pas d’un audit indépendant et les rapports complets sont disponibles sur demande. Chaque action est enregistrée : qui a ouvert quelle application, quand, ce qui a été décidé et quel modèle a produit chaque étape automatisée. Le journal peut être exporté. Les données des candidats peuvent être effacées sur demande et vous définissez la durée de conservation des candidatures. Les données d’application sont stockées dans l’Union européenne et les fichiers CV sont cryptés. L'interface est disponible en anglais et en français. Les pilotes travaillent pendant 8 à 12 semaines sur un ou deux postes ouverts, sur une instance dédiée à votre organisation.

eLearning Impulse uses an intelligent capturing technique for single screenshots that can then be edited as slides. Mouse movements are automatically reproduced. Projects can be exported into various formats for Internet, Intranet or published on CDs. The created files are extremely small - only ~0.1 MB per minute of playback.

Sophelio, formerly known as SapientAI, is an AI and machine learning company based in Austin, Texas, specializing in developing scalable, production-ready data systems for complex scientific and industrial domains. The company focuses on creating signal-first, provenance-driven systems that ensure reproducibility, interpretability, and operational trust in environments where these factors are critical. Key Features and Functionality: - Data Fusion Labeler (dFL): Sophelio's flagship platform, dFL, is designed for harmonizing, labeling, and exporting complex multimodal time-series data with full provenance. It offers visual DSP pipelines, Python-powered autolabeling, and schema-compliant exports, enabling users to transform raw signals into machine learning-ready assets efficiently. - Advanced Time Series Solutions: The company provides tools that allow users to uncover key drivers behind their data, visualize complex patterns, and confidently predict future outcomes. These solutions empower organizations to anticipate challenges and optimize operations for maximum efficiency. - AI and Machine Learning Integration: Sophelio seamlessly integrates AI solutions into existing systems through front-end GUIs, custom APIs, or backend libraries, delivering rapid results while saving time and effort. Primary Value and Solutions: Sophelio addresses the challenges of managing and analyzing complex, high-stakes sensor data by providing tools that ensure rigorous, reproducible, and trustworthy data workflows. Their solutions enable organizations to transform large, heterogeneous datasets into actionable intelligence, bridging the gap between raw data and deployable machine learning systems in real-world environments. By focusing on signal-first analytics and data harmonization, Sophelio empowers industries such as advanced manufacturing, robotics, energy, and scientific research to make data-driven decisions with confidence.

Uni Trainer is a local-first platform for fine-tuning, validating, and deploying LLMs without sending data to third-party servers. Teams can prepare and version datasets, run LoRA or CPT training, test outputs against golden sets, apply deployment gates, and keep a full reproducible audit trail - all from a single workflow.

Mindpeak Prostate H&E is an advanced software module designed for the automated analysis of digital histopathology images of prostate needle biopsies. It identifies areas suspicious for cancer and grades malignancies using the Gleason scoring system. This tool enhances the efficiency and accuracy of prostate cancer detection and grading, providing pathologists with reliable and reproducible results.

inForm Tissue Finder adds exceptional functionality to inForm Cell Analysis to automate the detection and segmentation of specific tissues through powerful patented pattern recognition algorithms. Automation provides consistent reproducible results and enables comparative studies of multiple markers and specimens, supporting researchers to make faster discoveries of the indicators of disease.

The Bioconductor mission is to promote the statistical analysis and comprehension of current and emerging high-throughput biological assays. Bioconductor is based on packages written primarily in the R programming language. Bioconductor is committed to open source, collaborative, distributed software development and literate, reproducible research. Enabling user and developer communities is an essential part of our mission. Scientific and Technical Advisory Boards provide project oversight.

LogicStar AI is a pioneering company dedicated to transforming software development and maintenance through advanced artificial intelligence. Their flagship product is an autonomous AI agent designed to seamlessly integrate into existing engineering workflows, autonomously reproducing and resolving software bugs with precision. This innovation allows developers to focus on creativity and innovation, while the AI handles the complexities of application maintenance.