Atinary SDLabs Platform Description
Atinary's Self-Driving Labs (SDLabs) platform offers a no-code solution for AI and machine learning, aimed at transforming research and development workflows by allowing conventional laboratories to move from hands-on experiments to fully autonomous experimentation. This platform enhances the design and refinement of experiments through a comprehensive closed-loop system that incorporates AI-generated hypotheses, forecasts, and decisions. Among its notable features are multi-objective optimization, efficient database management, streamlined workflow orchestration, and real-time data analysis. Users have the capability to set experimental parameters with specific constraints, enabling machine learning algorithms to determine the next steps in the process, conduct experiments either manually or with robotic aid, analyze outcomes, and update models with the latest data, thus expediting the pursuit of improved, cost-effective, and environmentally friendly products. Additionally, Atinary offers proprietary algorithms, including Emmental for tackling non-linear constrained optimization, SeMOpt for implementing transfer learning in Bayesian optimization, and Falcon, which collectively enhance the platform's functionality and effectiveness. By leveraging these advanced tools, researchers can achieve greater efficiency and innovation in their experimental processes.
Atinary SDLabs Platform Alternatives
Pipefy
Pipefy is a low-code Business Orchestration and Automation Technologies (BOAT) platform designed to act as a modern middleware layer for the enterprise stack.
Rather than replacing existing Systems of Record (SORs) like SAP, Oracle, or Salesforce, Pipefy wraps them in an agile orchestration layer. This architecture allows technical teams to modernize legacy operations and extend the life of core systems without the risks associated with "rip and replace" projects. Pipefy provides the infrastructure to sanitize data inputs, manage complex business logic, and orchestrate API calls between fragmented endpoints.
Technical & Architectural Highlights:
• Adaptive Governance Framework: Pipefy solves the "Shadow IT" problem by establishing IT-sanctioned "Safe Zones." Business users can build workflows within these guardrails, while IT retains control over critical data, integrations, and permissions via a centralized console.
• Agentic AI Engine (BYOLLM): The platform features a governable AI Agent Studio. Unlike "black box" solutions, Pipefy supports a Bring Your Own LLM approach, allowing enterprises to integrate preferred models (Azure OpenAI, AWS Bedrock) securely to automate document analysis (OCR) and decision-making.
• Robust Connectivity: Built with an API-first philosophy, Pipefy offers a GraphQL API, Webhooks, and enterprise-grade iPaaS capabilities to ensure seamless data interoperability across the stack.
• Security & Compliance: Engineered for regulated industries, the platform is ISO 27001, ISO 27701, and SOC2 Type II certified, supporting compliance with GDPR and SOX standards.
Pipefy empowers IT leaders to eliminate technical debt and clear development backlogs by safely delegating low-complexity builds to business units.
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SciSure
SciSure is reshaping the future of laboratories worldwide with forward-thinking digital solutions. Our Digital Lab Platform (DLP) unites key tools such as Electronic Lab Notebook (ELN), Laboratory Information Management Systems (LIMS), and advanced technologies like AI and machine learning. Built for seamless compatibility with your lab's hardware and software, the platform enhances flexibility, security, and efficiency. By consolidating and optimizing your research and development workflows within a secure and compliant environment, we help researchers dedicate more time to innovation. Our expert team is committed to supporting you at every stage of your digital lab transformation.
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ScienceDesk
ScienceDesk's data automation simplifies the integration of artificial intelligence within the field of materials science. This tool serves as a practical solution for teams to consistently implement and utilize the latest AI algorithms in their daily workflows. It features customizable attributes, universal identifiers, QR codes, and a robust search engine that connects sample data with experimental results. As a groundbreaking platform, ScienceDesk facilitates collaboration among scientists and engineers, allowing them to engage with and glean insights from their experimental findings. However, the full potential of this resource remains untapped due to the diverse data formats and a reliance on specialists to manually retrieve targeted information. The ScienceDesk research data management system addresses this challenge by merging documentation with data analysis within a thoughtfully designed data structure. Our algorithms empower researchers and scientists, granting them comprehensive command over their data. They can not only exchange datasets but also share their analytical expertise, fostering a more collaborative research environment. Overall, ScienceDesk enhances data accessibility and encourages innovative approaches in scientific investigation.
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Materials Zone
Transforming materials data into superior products at an accelerated pace enhances research and development, streamlines scaling processes, and optimizes quality control and supply chain decisions. This approach enables the discovery of innovative materials while utilizing machine learning guidance to predict outcomes, leading to swifter and more effective results. As you progress towards production, you can construct a model that tests the boundaries of your products, facilitating the design of cost-effective and resilient production lines. Furthermore, these models can forecast potential failures by analyzing the supplied materials informatics alongside production line parameters. The Materials Zone platform compiles data from various independent sources, including materials suppliers and manufacturing facilities, ensuring secure communication between them. By leveraging machine learning algorithms on your experimental data, you can identify new materials with tailored properties, create ‘recipes’ for their synthesis, develop tools for automatic analysis of unique measurements, and gain valuable insights. This holistic approach not only enhances the efficiency of R&D but also fosters collaboration across the materials ecosystem, ultimately driving innovation forward.
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Company Details
Company:
Atinary
Year Founded:
2019
Headquarters:
Switzerland
Website:
atinary.com/solutions/
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