Search by Algolia
How does a vector database work? A quick tutorial
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What’s a vector database? And how different is it than a regular-old traditional relational database? If you’re ...

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Removing outliers for A/B search tests
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Algolia's search propels 1,000s of retailers to Black Friday success
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What’s the average ecommerce conversion rate and how does yours compare?
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What are AI chatbots, how do they work, and how have they impacted ecommerce?
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What are AI chatbots, how do they work, and how have they impacted ecommerce?

“Hello, how can I help you today?”  This has to be the most tired, but nevertheless tried-and-true ...

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Algolia named a leader in IDC MarketScape
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Algolia named a leader in IDC MarketScape

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Large language models (LLMs) vs generative AI: what’s the difference?
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Large language models (LLMs) vs generative AI: what’s the difference?

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What is generative AI and how does it work?
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What is generative AI and how does it work?

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What does it take to build and train a large language model? An introduction

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Top examples of some of the best large language models out there
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Top examples of some of the best large language models out there

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What are large language models?
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What are large language models?

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Mobile search done right: Common pitfalls and best practices
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We are proud to announce that Algolia was named a leader in the IDC Marketscape in the Worldwide General-Purpose Knowledge Discovery Software 2023 Vendor Assessment. This IDC Marketscape report also ranks Algolia the highest in capabilities powered by the Algolia NeuralSearch™ platform, a next-generation API that combines vector and keyword search with powerful, end-to-end AI processing of every query. What sets Algolia’s capabilities apart isn’t just the technology, it’s the total offering brought to market by an amazing team dedicated to relevance in the digital experience.

The ROI of relevance in search and discovery

The new rules of relevance in search and discovery require unheard-of precision and contextual understanding compared to yesterday’s solutions. We’ve all tasted and tested the impact of generative AI in our daily lives and we’ve seen its limitations. Algolia brings this capability to your organization with unmatched speed and accuracy, and lightens the load on your internal teams. Our approach delivers measurable results for different digital use cases, whether you are looking to implement a next-generation search and personalization experience for e-commerce, or bringing enterprise knowledge into focus for quick and concise internal decisioning. Forrester Research recently completed a TEI evaluation of our technology showing payback within 6 months and a 382% ROI over 3 years.

Responsive search at the speed of thought

Customers expect search results to be instant and relevant. Your technology needs to keep pace without burying your team in maintenance exercises without measurable outcomes. Algolia’s NeuralSearch solution does exactly that. Our engineers have combined vector search and keyword search into a single API for simplicity, scale, speed, and contextual relevance. This combination increases the precision and recall of search results but also understands the nuanced relationships between words and concepts. Using our proprietary Neural Hashing technology, a method that compresses lengthy search vectors into smaller expressions, Algolia has reduced the scalability challenges and high costs typically associated with vector searches, while preserving the integrity of the vector data.

Vector databases are in high demand due to their compatibility with complex AI/ML applications like ChatGPT, but Algolia has leapfrogged the competition with our latest Inference API. This means you won’t need specialized vector databases, which are often expensive and hard to work with, because Algolia enables the transformation of any existing data into a vector database. Your organization can now use cutting-edge AI search technology with the speed and scalability of familiar relational and NoSQL databases.

Revolutionary approach: From RAGs to rich experiences

Algolia’s NeuralSearch is designed to improve the findability of information, items, and products, and to drive strong results by providing a highly-relevant and personalized user experience. We use machine learning and deep learning to fine-tune search relevancy, auto-tag content, and enhance document understanding. This means less time is required by operators to improve results, because the results improve automatically with increased usage. Why would any business not jump on this opportunity? Because they don’t trust the future of their business to the “black box” of artificial intelligence when confronted with mass reports of AI hallucinations.

Algolia’s approach to this challenge is to harness the power of LLMs by grounding it in the context of the original query through a process called retrieval-augmented generation (RAG). This approach allows the LLM to generate responses that are both contextually relevant and highly accurate. Algolia’s solution, particularly with its NeuralSearch product, leverages RAG by combining its robust vector search capabilities with the generative properties of LLMs. Here’s how RAG fits into Algolia’s solution:

  • Understanding user intent: When a search query is entered, Algolia’s AI evaluates the intent behind the query using LLMs, which can understand and interpret natural language with a high degree of nuance. These signals can also be captured to the segment or individual user providing future personalization opportunities.
  • Retrieving contextually relevant data: The system uses vector search to retrieve information that is contextually relevant to the query. This step involves scanning through vast amounts of data to find vectors — numeric representations of data — that closely match the query vector in terms of semantic meaning.
  • Generating accurate responses: Once relevant data is retrieved, Algolia employs the LLMs to generate coherent and contextually appropriate responses or content suggestions. This step ensures that the search results are not just based on keyword matches but are enriched with understanding from the retrieved content.
  • Reducing inaccuracies: To reduce the generation of plausible but false or unverified information, Algolia’s use of RAG mitigates this risk by guardrailing the LLM’s generative capabilities in verified information retrieved by the vector search.
  • Scaling and economizing: Algolia’s unique neural hashing technique economizes the RAG process by reducing the vector space required for the search, making the retrieval component of RAG both faster and more cost-effective. This is highly beneficial when dealing with large-scale implementations that require real-time processing.

Reliable and flexible: non-negotiable expectations for search

Because your competition is just a click away and developments in search and discovery are now occurring at a frenzied pace, reliability is a major factor in every technical partnership. The importance of uptime and reliability in the user experience cannot be understated. Algolia provides high availability with 99.999% worldwide uptime and a 100% service-level agreement (SLA) for developers, ensuring consistent and reliable service delivery. In addition to uptime, the flexibility to partner with quickly-evolving LLMs should not be overlooked. Algolia’s architecture is LLM-agnostic so you can take advantage of your current integrations or efficiently pivot to an emerging solution.

Resource-rich support: empowering developers with robust tools

Developers play a critical role in integrating and advancing search technology, especially to handle your unique and evolving use-cases. Algolia’s suite of tools and integrations is built for developer efficiency. We’ve changed the “black box” of AI to a transparent one by providing the access and support your developers need to derive insights and to get the job done. Algolia is touched by 5 million developers a month and the feedback we’ve received from developers and engineers has only reinforced our decision to keep their needs at the forefront of our offerings. We encourage you to learn more about the breadth of our offerings at the Algolia Developer Hub.

Reach with real relevance: scaling search globally across industries

The challenge of scaling relevant search solutions to meet global demands is no small challenge. From strategies including multi-site ecommerce to multi-language enterprise search, Algolia’s performance across diverse industries and large-scale operations will help you succeed. Algolia drives relevance for 17,000+ customers across 150 countries applying end-to-end AI to 1.75 Trillion queries per year (and growing). Our industry-agnostic search solutions are one of the reasons Algolia was selected (for the second consecutive year) as one of the world’s best cloud companies, ranking in the Top 50 of the 2023 Forbes Cloud 100.

Refined and ready for the future: ecommerce and beyond

Algolia’s specialized features for ecommerce support the unique demands of online retail search and discovery. From auto-tagging massive catalogs of products with machine learning to real time personalization in-session, NeuralSearch brings the power of modern search into the hands of your merchandisers. Gone are the days requiring large armies of merchandisers to administer product attributes, boost and bury products by keyword query, and entering a confusing swathe of synonyms and stemming rules. Now your merchandisers can spend time doing what they do best – telling product stories that resonate with the consumers, building converting collections on the fly, refining product recommendations, and driving real relevance with one-to-one personalized experiences.

Check out the IDC Marketplace report to learn why we were recognized as a leader. Algolia is uniquely positioned to deliver ultimate relevance, across any industry, bringing the power of ecommerce refinements to every vertical including enterprise, departmental, and site search use cases. Our API approach empowers businesses to impact applications in any channel, at scale, and without redundant development holding your teams back from their very best. Business users and consumers alike can interact across any digital touchpoint including the web, mobile, connected devices, and whatever the future brings. We’ve even enabled voice search to bypass the speed constraints of the keyboard, empowering mobile search, and bringing realtime accessibility to all.

Harness the future of search now. Get in touch with our team for a custom demo, or signup to try Algolia for yourself.

About the author
John Stewart

VP Corporate Marketing

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