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All data is not created equal. As the amount of data increases exponentially, knowledge workers find themselves overwhelmed with data, struggling to find the useful nuggets they need.

RAG creates boundaries so that the AI cannot wander off into chaos or start exploring some other reality at your expense. Rather than wandering the universe of all possible answers, RAG limits the AI to reality: no imaginary court cases in your list of precedents, no imaginary customers in the report to senior management, etc.  

Search, or the fine art of finding what we’re looking for, is only partially solved.

We are excited to announce the release of SWIRL 3.8, packed with new features, user-requested improvements, and performance upgrades to enhance your AI and search experience.

AI agents are tools that use AI to respond to their environment and take actions based on what they “perceive.” AI agents present a powerful method for businesses to automate strategy, harnessing AI to identify patterns and respond to changing market conditions more rapidly and more accurately.

Unlock the power of AI in research with SWIRL’s innovative infrastructure. Learn how to accelerate your research process, improve data management, and enhance search capabilities while maintaining data security. Discover how AI can become your personal research assistant, ending the data scavenger hunt and boosting productivity.

Discover how AI infrastructure software enhances research efficiency, allowing more time for creative work. Learn about key features like universal connectivity, AI flexibility, and advanced metasearch capabilities that transform AI into a powerful assistant for academics and researchers.

Discover how AI Infrastructure Software transforms a Mixture of Experts into a personal AI Advisory Board. Learn to harness multiple AI models for personalized advice, enhanced decision-making, and efficient information processing. Explore the power of AI-driven expertise without the chaos of managing multiple language models.

Discover how to effectively increase productivity with AI using strategies like the Centaur and Cyborg approaches, and learn why AI Infrastructure Software is crucial for overcoming common AI challenges in business operations.

Discover how AI infrastructure software can revolutionize data-driven product development. Learn about universal connectivity, AI flexibility, and powerful search capabilities that enable businesses to efficiently turn data into valuable products. Explore SWIRL’s innovative approach to AI integration and its benefits for decision-making, efficiency, and time-to-market.

Discover the key differences between unified search, metasearch, and federated search engines. Learn how each search technology works, their benefits, and when to use them for optimal information retrieval

Discover 5 ethical ways to leverage AI in academic work from a former psychology professor. Learn how AI can enhance research, writing, and citation processes without compromising academic integrity. Perfect for students and researchers looking to boost productivity and quality in their academic pursuits.

Discover how AI infrastructure software revolutionizes course catalog searches, simplifying class registration and enhancing student-advisor interactions. Learn how advanced search capabilities and AI-powered insights can streamline the course selection process and improve academic planning.

Discover how unified search solutions revolutionize enterprise knowledge management, boosting productivity and streamlining information access. Learn key benefits, overcome implementation challenges, and unlock your organization’s full potential with advanced search technologies.

AI is transforming library research by automating resource discovery, enhancing semantic search, and providing personalized recommendations. Through natural language processing and machine learning, AI tools can quickly analyze vast databases, extract key insights, and connect related concepts across disciplines. Discover how these intelligent systems are revolutionizing academic research, making it faster, more comprehensive, and tailored to individual needs.

AI models need enormous amounts of data to learn and generate accurate outputs. This data hunger comes with significant privacy and security risks that companies must address proactively. To safeguard personal information within training data, companies must implement robust protection measures such as data anonymization, de-identification techniques, and more advanced approaches like differential privacy.

Data silos hinder AI adoption in retail, with 70% of organizations missing opportunities due to integration challenges. Bringing AI to the data, rather than data to AI, offers a secure solution. AI infrastructure software like SWIRL AI Connect enables universal connectivity, AI flexibility, and powerful unified search to maximize AI’s potential in retail.

SWIRL changes information retrieval by integrating advanced search capabilities with generative AI. Unlike traditional approaches that require costly data duplication, SWIRL allows users to access information across multiple platforms without moving data. This innovative solution enhances productivity, reduces AI hallucinations, and offers a cost-effective way for businesses to leverage AI technology while maintaining data security and efficiency.

AI is changing how businesses work, helping them predict trends, automate tasks, and boost productivity. From small startups to big companies, AI is creating new opportunities and reshaping the future of work.

AI infrastructure software is vital for long-term, scalable AI projects, providing control over generative AI, machine learning, and deep learning models. SWIRL AI Connect offers a comprehensive solution for AI infrastructure, combining ease of access to data with security, scalability, and the ability to monitor and maintain AI systems. SWIRL AI Co-Pilot further enhances this by providing intelligent assistance to business users, enabling seamless interaction with data and incorporating metasearch and RAG.

Discover how Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) are transforming business research by providing real-time insights and automating workflows. And help break data siloes.

Integrating Generative AI into enterprises presents transformative opportunities and significant challenges. While it promises enhanced productivity and accelerated decision-making, enterprises must address data integration, security, and scalability issues. By investing in robust training, governance frameworks, and scalable architecture, businesses can successfully harness GAI’s potential to drive innovation and growth.

Discover how generative AI can transform your business with SWIRL AI Connect. Learn to harness AI securely and responsibly, enhancing productivity and decision-making without extensive data migration. Embrace AI advancements with minimal IT involvement and maximize your enterprise’s potential.

Finding data can feel like an episode of the X-Files. The truth is out there, but no matter how much you search it’s always just out of reach.  

SWIRL transforms enterprise AI adoption with its AI Co-Pilot and AI Connect, offering secure, user-friendly solutions that integrate seamlessly with existing systems. By eliminating data duplication risks and simplifying AI interactions, SWIRL empowers businesses to harness AI’s full potential while maintaining data security and regulatory compliance.

What Does SWIRL Do? This post dives in with the philosophy behind SWIRL. What we hear from others very often is and what we offer.

AI surely is shaking things up in the business tech world. It’s changing how companies use their digital tools and could transform the way we work. Will AI mean the end of applications as we know them?

In the rapidly evolving landscape of modern business, artificial intelligence (AI) is both a beacon of progress and a source of apprehension. As AI technologies continue to advance, they promise unprecedented efficiency and innovation. Read the post to know more …

SWIRL Co-Pilot transforms how big businesses use Retrieval-Augmented Generation (RAG). It addresses major enterprise challenges like scattered data, strict security needs, and complex information structures. Acting as a smart assistant, SWIRL Co-Pilot securely searches all company data, understands company-specific language, and provides quick, relevant answers. It saves time, reduces errors, keeps data safe, and integrates with existing systems. With SWIRL Co-Pilot, companies can unlock the full potential of their data while maintaining security and efficiency.

Introducing SWIRL AI Co-Pilot: Your new smart assistant that understands your data and saves you time, revolutionizing enterprise AI adoption. Experience our lightning-fast, real-time system that keeps your data secure and easily accessible – no slow databases or data copying required.

In today’s fast-paced business environment, SWIRL AI Connect revolutionizes decision-making with real-time data insights. By eliminating the need for complex data movement, it provides accurate, agile, and proactive problem-solving capabilities. Discover how SWIRL AI Connect enhances decision-making with its intelligent, context-aware assistant.

As enterprises grapple with the complexities of scaling AI initiatives, SWIRL AI Connect emerges as a transformative solution. By addressing the core challenges of data fragmentation, inconsistent model performance, and lack of collaboration, the platform paves the way for a new era of AI-driven innovation.

Generative AI (GAI) has moved from hype to skepticism as organizations struggle to find practical applications and face challenges with data integration and security. Understanding GAI as a productivity tool rather than a predictive one is crucial for success. SWIRL AI Co-Pilot addresses these issues by providing seamless data integration, robust security, and contextual awareness, turning GAI into an intelligent assistant that enhances productivity and decision-making.

Understanding the latest advancements in search engine technology, metaranking, and reranking are redefining how search results are delivered. These sophisticated algorithms enhance the relevance and personalization of search outcomes by refining initial results and aggregating multiple ranking signals. Explore how these techniques, employed by major platforms like Google and Amazon, are shaping the future of search and ensuring users receive the most pertinent information in an ever-expanding digital landscape.

Metasearch engines streamline online searches by querying multiple search engines simultaneously and aggregating the results. This comprehensive approach saves time, enhances privacy, and offers more diverse results than traditional search engines. As digital information continues to expand, metasearch engines become increasingly essential for efficient and thorough searches.

The best thing about a Generative AI is that it will answer your questions. The worst thing about Generative AI is that it will answer your questions. Ai models create an illusion of context, but they don’t really understand context. Because of that lack of understanding, an AI will leak data in response to a carefully formulated query.

AI is particularly good at reducing the time spent finding and understanding data. Assuming, of course, that what the AI returns can be trusted – This article sheds light into how AI can improve motivation.

This post delves into why SWIRL Co-Pilot is the right product, arriving at the right time and perfectly positioned in the right place for transformative enterprise growth.

SWIRL Co-Pilot offers a groundbreaking solution for large, regulated enterprises to overcome generative AI security and compliance hurdles. By keeping data in its original system and simplifying access control, SWIRL enables organizations to harness AI’s power while maintaining data security and regulatory compliance.

Uncover the critical security challenges enterprises face when adopting generative AI, from data privacy to model safety. Explore real-world case studies and learn effective risk mitigation strategies. Gain actionable insights for balancing AI innovation with robust security in your organization.

In this post I want to share my thoughts on the MIT Imagination in Action conference. This was an invaluable opportunity that I highly recommend every founder take advantage of. 

Post-merger data integration is crucial for financial institutions. SWIRL AI Connect streamlines this by using AI to efficiently search, analyze, and retrieve data without extensive ETL processes, enhancing data accessibility and security during banking mergers and acquisitions.

AI is revolutionizing financial services, but there are genuine risks to data security and decision accuracy. To maximize effectiveness, AI systems need access to sensitive data. Read to learn about maximizing benefits of AI.

Financial institutions are increasingly using AI to manage risk by identifying patterns and trends early. However, effective AI deployment requires large amounts of current data and seamless integration into existing systems to avoid issues such as data breaches and synchronization challenges. Addressing these hurdles is crucial for maximizing AI’s benefits in risk management.

Banks can benefit from artificial intelligence (AI), provided they can keep their data secure and trust what the AI tells them. AI has the potential to revolutionize the banking industry by streamlining processes, improving customer experience, and providing valuable insights.

The Google Gemini RAG incident highlights the urgent need for enterprise AI safety and trust. By prioritizing responsible AI development and governance, businesses can mitigate risks and harness AI’s full potential.

Cognitive overload occurs when the brain is overwhelmed by excess information or demands, making it difficult to process and remember new information. This state can lead to feelings of stress, decreased productivity, and impaired decision-making

Companies should be wary of relying on single, centralized data repositories like vector databases for RAG, as this introduces significant risks and challenges that must be carefully considered and addressed. In this post we share light onto those risks of over relying on vector databases and more.

AI infrastructure software is essential for deploying on-premises AI solutions. And in this post, we discuss the possibilities of SWIRL AI Connect and how it can enable you to

While foundational in many data management strategies, the ETL process involves transferring large amounts of data into a centralized store. This operation is both resource-intensive and costly, as it requires substantial computational and storage capabilities. And in this article we discuss the case against ETL systems, in AI Architectures.

The adoption of AI in the enterprise is not without its challenges. As organizations rush to integrate AI into their operations, they often overlook critical aspects that can lead to significant risks, and this is why we have to focus on a set of principles that will dictate the next generation of AI apps in the enterprise.

SWIRL AI Connect allows for instant deployment of AI Models. In this post, Sid tries out Llama 3 with SWIRL.

A Reader Large Language Model (LLM) is an AI designed to understand and analyze text. Unlike LLMs that generate text, Reader LLMs focus on reading and making sense of existing language.

AI Infrastructure Software is an umbrella term for a software infrastructure that seamlessly integrates AI capabilities while prioritizing security, safety, and access control. It operates as a middle layer between data, AI infrastructure, and large language models (LLMs), ensuring that end-users can harness the power of AI without compromising data security or compliance.

SWIRL is moving towards bringing AI to the data instead of data to the AI. Breaking conventional barriers and utilizing Reader LLMs and eliminating the need for extensive data movement, SWIRL enables enterprises to generate valuable AI insights without complex IT projects.

Discover how SWIRL AI Connect can help your business stay ahead of the curve in the ever-evolving world of artificial intelligence. With cutting-edge capabilities and a focus on data-driven decision-making, this advanced infrastructure is the key to unlocking new levels of efficiency, innovation, and customer satisfaction.

Improve your organization’s knowledge flow with these 5 essential knowledge management strategies. Optimize information access and foster a knowledge-sharing culture

Discover how to implement generative AI for increased efficiency and innovation, while ensuring security. Learn about use cases, best practices, and how Swirl can help.

In this post, Simson explains what a vector database is and why Dr. Low’s article on Vector Database says you don’t need one and provides context to Dr. Low’s answer.

Dive into the fascinating world of Large Language Models (LLMs) and uncover the science behind these powerful AI systems that can generate human-like text and even create images. Explore their evolution, inner workings, and the potential they hold for the future.

Cosine similarity is a metric that measures how similar two entities (vectors) are irrespective of their size. Commonly used in high-dimensional positive spaces, it can be helpful in various applications, including data analysis, information retrieval, and understanding the relationship between documents in text processing.

Generative AI promises to revolutionize enterprise search, empowering organizations to extract critical insights, foster innovation, and optimize decision-making.

Critical information resides in far-flung corners: structured databases, departmental silos, and scattered unstructured files. While this data holds immense potential, discovering the right insights often requires a tedious process of piecing together fragments from various sources.

The concepts of Generative AI, Machine Learning, and Deep Learning are fueling an explosion of exciting possibilities, yet some need for clarification about how they relate and differ may persist. Let’s break down these powerful branches of AI to get a clearer picture.

Knowledge management (KM) is the process of creating, sharing, using, and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieving organizational objectives using the best knowledge.

Semantic similarity measures how similar two pieces of text are in meaning rather than just the words used. It is a branch of artificial intelligence and natural language processing that deals with understanding the meaning of words and phrases.

A data silo refers to a repository of data controlled by a particular department, team, or system within an organization.

The sheer volume of online data necessitates precision in search results. Search relevancy is the essential tool that filters through the informational deluge, presenting users with the most accurate and applicable content.

A search index is a data structure that improves the speed of data retrieval operations on a database by providing quick lookups to the data records.

A vector database stores numerical representations of texts, images, and videos.

Cloud computing has undeniably transformed the way organizations approach IT infrastructure. Among the prevalent cloud models, private clouds (internal or corporate clouds) are rapidly gaining traction due to their emphasis on security, control, and customization. This article delves into the fundamentals of private cloud computing, its architectural components, advantages, drawbacks, various types, use cases, and comparisons with other deployment models.

Enterprise search involves creating a massive, unified index of your organization’s data. This index is a comprehensive library catalog, encompassing everything from documents on file servers to email archives and customer records. When a user queries, the enterprise search engine consults this index for results.

Machine learning (ML), a transformative branch of artificial intelligence, has transitioned from theoretical realms to real-world impact across industries. Instead of rigid rules, machines learn from examples and data to find patterns on their own.

A search engine is a complex software system meticulously designed to discover, interpret, and organize internet content.

Enterprise search is a technology that helps employees find information across their organization’s data silos. It can search various sources, including file shares, databases, email, and collaboration platforms. However, traditional enterprise search solutions often need to be revised, delivering irrelevant results or requiring users to know exactly what they want.

Hosted enterprise search is a cloud-based solution where the search infrastructure is managed and maintained by a third-party provider. This approach reduces the need for in-house IT resources while offering scalability and ongoing updates.

Discover how Retrieval Augmented Generation (RAG) enhances language models. Find out its real-world applications and how Swirl tackles RAG with metasearch for unparalleled flexibility.

Demystifying enterprise search and federated search – understand the differences, benefits, and use cases with an eye on how Swirl Search empowers both strategies.

Imagine all your business data – every file, email, and database entry – trapped in separate rooms. Searching means running from room to room. Frustrating, right? Federated enterprise search builds a hallway connecting everything; one search box to find it all.

Federated search is a technique used to simultaneously search multiple data sources, data warehouses, etc. A federated search engine is a powerful tool that lets you search across multiple databases, websites, chats, internal articles, or information systems all at once, using just one query.

Unified search is an advanced strategy consolidating data from diverse sources (databases, documents, web pages) into a single, easily accessible interface. Users execute a single query, spanning various repositories, streamlining the search process and maximizing efficiency.

A metasearch engine is an information retrieval solution that connects to multiple search engines to fetch results for the same query and then produce a blended result set. Metasearch engines take a query from a user and immediately distribute the query across search engines for results. After gathering the data, the metasearch engine ranks and displays the results. Best in class metasearch or federated solutions will normalize relevancy from the disparate sources.

Swirl releases version 3.2.0. With this, we continue our march towards a secure, tight, air-gapped enterprise-grade unified search and data access platform, which operates within your enterprise firewall, and with your private large language model.
Swirl is available in Azure with a 30 30-day free Trial.

This article showcases the Swirl Reference Architecture for Real-Time, AI-Powered Enterprise Search.

We have the new AutomaticPayloadMapperResultProcessor which automatically organizes the data from search providers into the Swirl system, so you don’t have to map out the results manually. With this, your search queries would be easier behind the scenes, and you’ll be more productive at work.

Bringing AI enabled search to the enterprise. We know that AI is important for our organizations, but the real problem is how we can empower our organizations with AI. Swirl provides a solution for that.

Adam sets up to write about his journey with Swirl, and how he’s planning to shape the future of Enterprise search with Swirl. And a moment to reflect on Swirl’s journey over the past nine months and celebrate the launch of Swirl on Azure Marketplace for private cloud deployment.

AI-powered enterprise search for secure private cloud retrieval augmented generation. Swirl AI-powered federated metasearch enables enterprise users to rapidly locate, retrieve, and act on enterprise data, applications, and insights through an intuitive search interface.

Chris Biow joins in as Head of Federal Sales at Swirl. Biow will expand Swirl’s presence and impact in the federal market, where AI demand is growing rapidly.

Swirl Breaks Cookie Cutter Enterprise Search Approaches with its unified searching capabilities along with artificial intelligence integration.

Swirl nails the enterprise search and provides the best search results from a wide array of data sources.

Swirl 3.1.0, the latest update to the open-source search enterprise search platform, brings several exciting features, seach providers, etc.

This blog talks about how Swirl uses Swirl at work, which is incredibly compelling.

Why large language matters and the context between word also matters when it comes to search, ranking and relevancy.

The traditional approach is the lift and shift of data from one container to another. It is a big problem in many cases, and Swirl serves as the best solution to this problem.

Searching through your entire enterprise? Swirl Search offers viable solutions for this. It is the AI Driven Enterprise Search Solution. Perform federated search through all of your enterprise with easy.

Swirl is thrilled to announce the addition of five distinguished professionals to its Board of Advisors.

Swirl 3.0 introduces new features like Retrieval Augmented Generation, LLM Swapping & more. Read this blog to know more.

US Government Agencies can evaluate and deploy Swirl today without cost by utilizing Swirl’s Open Source offerings. Please checkout the blog for more information.