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AI Infrastructure Enhances the Power of Generative AI, Machine Learning, and Deep Learning 

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.

Overcoming the Challenges and Understanding the Benefits of Using AI Infrastructure Software to Accelerate Gen AI Adoption in the Enterprise

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.

Generative AI: The Double-Edged Sword of Innovation

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.

The Truth is Out There 

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.  

Secure AI Conversations: Transforming Enterprise Data Interaction

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.

Optimizing Retrieval-Augmented Generation (RAG) for Enterprise Applications

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.

Team SWIRL Update: Exciting Milestones and Cool New Features!

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.

Transform Your Business with Real-Time Data Insights: SWIRL AI Connect

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.

Navigating AI Disillusionment — Generative AI is a Productivity Tool

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 Meta-ranking and Re-Ranking

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.

Understanding Metasearch: A Comprehensive Guide

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.

AI See, AI Say—Stop Your AI From Leaking Data

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.

Overcoming Generative AI Security and Compliance Hurdles with SWIRL

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.

Harnessing AI for Effective Risk Management—Why Financial Institutions Need a Robust AI Infrastructure

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.

Rethinking Data Integration for AI: The Case Against ETL in AI Architectures

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.

What is AI Infrastructure Software?

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.

What are Large Language Models (LLMs)?

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.

What is Knowledge Management?

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.

What is a Data Silo?

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

What is Search Relevancy?

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.

What is a search index?

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.

Private Cloud Computing: Architecture, Benefits, Challenges, and Best Practices

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.

AI Powered Enterprise Search

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.

What is Enterprise Search?

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.

What Is Federated Search?

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.

What is Unified Search?

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.

What Is A Metasearch Engine?

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’s First 9 Months: A Journey Through the AI Universe

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.

Matter LLMs, Why? 

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

Swirl Security Overview Pt. 2

This blog covers the second part of Swirl Security Overview (User Data, Metadata, and Credentials). This is a three-part series that guides you about Swirl’s security.

Swirl Security Overview

This series of blogs will give you a security overview of Swirl. How Swirl works behind the scenes, and how to securely deploy Swirl in Azure.

Swirl 2.6 Released

This release adds SearchProviders for ServiceNow, Hacker News and Google News. We’ve also validated Swirl on the latest stable Python version (3.11.5) and updated our Dockerfile image to the latest stable Debian release (Bookworm).

Embedding Swirl in your application

Software companies can reduce churn and increase engagement by adding generative AI. However, challenges such as lack of data, security concerns, and integration with existing processes can make it difficult. When successfully embedded, AI can create differentiation and unlock various use cases.  Swirl, an open-source tool released on GitHub under Apache 2.0, allows for quick […]

Easily Swirl generative insights from your data and ChatGPT 

Swirl is delighted to announce our end-to-end enterprise support for using enterprise content, such as Microsoft 365 and ChatGPT, to get current generative insights from your own data, quickly and safely. Swirl Retrieval Augmented Generation (RAG) combines metasearch, relevance ranking, authentication, prompt creation and ChatGPT response, with citations. Per OpenAI’s privacy policy the prompt is not used for training unless you opt-in. Deploy in minutes via Azure.

Giving you time in a Swirl

It is understood that “Any company that creates more than $10 billion in shareholder value does one of two things: extend time (more time, saving time) or enhance time.” Time is priceless.   Swirl recently released version 2.5 featuring a performance benchmark showing a median search time of ~3 seconds across 12 sources. In layman’s terms, […]

Swirl 2.5 Released

Team Swirl is thrilled to announce the General Availability of Swirl 2.5! The theme for this release is performance. Configured with 12 SearchProviders, Swirl 2.5 supports up to 15 queries/second on a Standard F16s v2 server (16 vcpus, 32 GiB memory) with a median response time of 3 seconds.   Swirl 2.5 also includes SearchProviders for […]

Swirl 2.1 Released!

Team Swirl is delighted to announce General Availability of Swirl Metasearch 2.1!  This version features the new Galaxy Search Interface with Dark Mode: It also includes numerous refinements such as: Version 2.1 also comes with SearchProviders for GitHub Code, Commits, Pull Requests, and Issues. Please visit our Release 2.1 page in the public repo for full details! Search Developers, […]

Video – Swirl SearchProviders Deep Dive

One of the most important elements of Swirl Metasearch is the SearchProvider. In this video, Erik Spears and Sid Probstein from Swirl take a good look at SearchProviders. Some of the details covered in the video include: SearchProviders also contain: Although SearchProviders are stored in the Swirl configuration database, they can be viewed and edited […]

Why Metasearch Matters to Today’s Enterprise

Curious about Metasearch and why your company should be using it to solve cross silo search problems? In this video Sid Probstein, creator of Swirl Metasearch, explains why it represents a game changer for the enterprise! 

Introducing: Swirl Metasearch 2.0

We are delighted to announce the general availability of Swirl Metasearch 2.0!

This major leap forward in functionality makes it easier than ever to solve cross-silo Enterprise Search problems quickly and securely — without extracting or moving any data.

Why I Created Swirl Metasearch

I’ve been fortunate to work in search a few times now. And I believe it continues to be the most human way of interacting with data. But search changes constantly; Brin and Page were chasing the Star Trek computer; they ended up with an ad engine. Search is tricky, and not just because of the […]

How can we help you?

Contact Swirl to learn more