Google Scholar Integrations

Our mission is to organize the world's information so that everyone can access and use it. Every time you search, there are thousands, sometimes millions, of webpages with helpful information. How Google figures out which results to show starts long before you even type, and is guided by a commitment to you to provide the best information. Even before you search, Google organizes information about webpages in our Search index. The index is like a library, except it contains more info than in all the world’s libraries put together. In a fraction of a second, Google’s Search algorithms sort through hundreds of billions of webpages in our Search index to find the most relevant, useful results for what you’re looking for. To help you find what you’re looking for quickly, Google provides results in many useful formats. Whether presented as a map with directions, images, videos or stories, we’re constantly evolving with new ways to present information.

Clay is the AI-driven data marketplace and orchestration layer that powers modern go-to-market teams. Clay enables teams to find and qualify prospects with AI agents and intent signals, enrich their CRM with best-in-class accuracy and fill rates from 150+ data providers and AI, and orchestrate GTM workflows such as ABM, outbound, and pre-call meeting notes. Over 5,000+ companies, like OpenAI, Canva, Anthropic, and Rippling, use it to power everything from recurring CRM enrichment to targeted outreach.

Eigent is an open-source desktop automation platform designed to act as a powerful AI workforce for modern productivity. It transforms context into action by coordinating multiple intelligent agents to automate complex tasks directly on the desktop. Built with multi-agent collaboration and parallel execution, Eigent handles long-horizon workflows faster and more efficiently than single-agent systems. The platform is fully customizable, allowing users to create their own worker nodes and plug in tools through modular MCPs. Privacy and security are central to Eigent’s design, with support for local deployment that keeps sensitive data fully under user control. Eigent supports a wide range of real-world use cases, from file organization and report generation to ERP automation and market research. As an open-source solution, it offers transparency, flexibility, and enterprise-grade performance without vendor lock-in.

Rayyan is an AI-powered research collaboration platform designed to streamline the process of conducting systematic reviews and literature reviews. Utilizing artificial intelligence, machine learning, and natural language processing, Rayyan assists research teams in reducing the time required to complete their reviews by understanding language, learning from decisions, and providing intelligent support throughout the review process. Researchers can efficiently manage their reviews using Rayyan's AI-powered workbench and time-saving features, enabling them to extract and synthesize relevant information effectively. It offers a mobile app, allowing users to collaborate on reviews from anywhere, even offline, turning unproductive moments into productive research time. Rayyan supports the import of references from various sources, and provides advanced features such as duplicate detection, relevance ranking, PICO highlighting, etc.

Resea AI is a full-featured academic research assistant that autonomously plans, conducts, and writes in-depth academic tasks from literature review to report drafting. It connects seamlessly with major scholarly databases such as Google Scholar, PubMed, and arXiv to source trusted research, then employs its proprietary “Think and Research” engine to determine research direction, core concepts, and writing angles through multi-stage inquiry. Feeding into its AI writing editor, Resea AI is capable of generating documents of unlimited length (even up to 50,000 words), and offers interactive editing for fast refinements. It ensures academic rigor through support for dozens of citation formats with accurate source indexing. It evaluates performance with benchmarks like xBench‑DeepSearch that measure deep research capabilities. Additional use cases include systematic literature reviews, academic outlines, content synthesis, reviewer-perspective feedback, and more.

Upon starting a new essay it sets up the title section/page, margins, font, line spacing, alignment, page headers/footers, etc. It formats your references, in-text citations, footnotes/endnotes, figures, tables, table of contents and more. Add in-text citations and footnotes/endnotes with ease. Simply click the insert citation button and select the reference you wish to cite. An in-text citation/footnote/endnote is automatically created for you. Add references quickly and easily using Google Scholar, Essayist’s built-in search, by pasting a URL or manual entry forms. Once added, references are automatically formatted and added to your essay’s references/works cited list.

Patents from around the world, translated. Plus technical papers and books, are organized and labeled automatically. Search for prior art, all in one place. Understand results, with images, PDFs, and citations. Security technology and the Privacy Policy protect your data. Search and read the full text of patents from around the world. Google Patents includes over 120 million patent publications from 100+ patent offices around the world, as well as many more technical documents and books indexed in Google Scholar and Google Books, and documents from the archive. New ideas are often published either as patent applications or in academic journals. If you are searching for prior art to a patent application, it is critical in many fields to also search for non-patent literature to get a complete view of the state of the art. Patents with only non-English text have been machine-translated to English and indexed, so you can search patent publications using only English keywords.

Hyperagent is a cloud-based AI agent platform designed to move beyond traditional chat interfaces by enabling autonomous, task-driven agents that can perform real work across an organization. Rather than acting as a simple chatbot, it provides “powerful cloud agents with a full computing environment” that can browse the web, analyze data, generate content, build applications, and interact with existing tools and services in real time. These agents are capable of executing complex, multi-step workflows such as sourcing candidates, compiling executive reports, or planning marketing campaigns, all while integrating with platforms like Slack, Gmail, and CRM systems to gather and act on data. A core feature of Hyperagent is its ability to learn and improve over time by storing “skills and memories,” allowing it to adapt to company-specific processes, internal data structures, and brand guidelines without requiring explicit retraining.

Next-generation AI chatbot building platform, quickly create bots without coding and publish them on various platforms. Workflow is a useful tool for planning and implementing complex functional logic, often used for multi-step tasks like travel planning and report analysis. For tasks with complex functionality and high stability requirements, implementation with a workflow is ideal. Workflow provides a wide range of flexible, combinable nodes, and even supports custom code, to handle complex and controllable AI task flow needs. When the targeted AI task scenes involve many steps, and there are strict requirements on output accuracy and format, it is suitable to use a workflow.