How to use AI to build your business

The world of technology is constantly evolving with generative Artificial Intelligence (AI) currently leading the charge. We’re suddenly surrounded by incredible tools that instantly produce text, images, voice, video, code, and more, with human-like capacity. Entrepreneurs can take advantage of AI solutions to build their businesses more rapidly than ever. 

The excitement over the new generative AI tools is partly due to their accessibility. For example, ChatGPT has become a household name overnight and is already the go-to tool for writing, brainstorming, and research. Now that AI is powered through natural language, people can finally imagine what’s possible and see how far the technology – and their ideas – can go. 

This topic was originally presented at Algolia DevCon 2023. 

Building a business with AI: step-by-step

Are you an entrepreneur that needs help hatching the next great idea? Well, now you can use generative AI tools along with Algolia NeuralSearch to bring your idea to life. Here’s a step-by-step example:

  • Start with using ChatGPT to conduct a business brainstorming session that covers products, markets, budgets, and regions. Repeat and refine that process until you seize upon an area you’re really excited about. Then ask ChatGPT to share its top five business ideas. You can even ask ChatGPT to come up with the ideal business name.
  • Next, create an AI stack of tools and services that will constitute your online business. To offer products, manage purchase transactions, and engage with shoppers, set up a Shopify e-commerce store, integrate it with Stripe for payments, and Twilio for customer service.
  • Use the AI tool to scrape the web for products and associated metadata that fit your target niche. Set up an affiliate marketing account inside the Amazon Associates Program, link it to your product data, and start earning commissions. Or connect your Shopify store directly to vendors on that platform or through a dropshipping app. 
  • Head back to ChatGPT or use CanvaAI to generate SEO-friendly product descriptions that will entice your ideal shoppers. Use Adobe Firefly to adorn your site with one-of-a-kind AI-generated images. Combine these tools to run eye-catching ads on Google, WhatsApp, and other social sites to get your brand in front of people.

understand ai search banner

By this point, generative AI has miraculously helped you realize your vision and set up a fully loaded e-commerce store that’s ready to earn revenue. And you haven’t even left your desk! 

Only one thing’s missing from your entrepreneurial launchpad – the connective tissue at the heart of online activity and through which people navigate their experiences: search and discovery. This is something we are deeply passionate about at Algolia, where we serve 1 out of every 6 searches on the planet.

From matching to understanding

AI search works differently than traditional keyword search. With older search technology, people had to lower their expressive capacity so computers could understand them. They typed keywords into search bars in hopes of returning one-to-one catalog matches.

With AI search, we can write search queries as we’d naturally say them. AI-powered algorithms know what you mean when you type “something to hold my hot coffee” or “keep my coffee hot.” The better the language understanding model, the better the conversions. This shift — from matching to understanding how customers express themselves without the need for exact keywords — is happening fast, and savvy business minds are taking note. 

The basics of vector search

So how does AI understand the relationship between words? It uses a language model to plot word tokens as vectors in multi-dimensional space according to how similar or dissimilar those tokens are along a spectrum of attributes. Using cosines as the measure of similarity, vectors plotted closer to one another share more similarities. Those further apart have more dissimilar attributes.

semantic vectors
Image via Medium showing vector space dimensions. Similarity is often measured using Euclidean distance or cosine similarity.

The accuracy of vector search relies on the language model used. The underlying technique works incredibly well, but training large language models makes vector search impractical for most businesses due to time requirements and processing costs.

Plus, as large language models improve, users will tend to input longer queries into a search box. These are even tougher to parse, requiring even more computational resources, and often return less precise results.

To see a quick visual explanation of this, check out our video here

Algolia NeuralSearch

At Algolia, our recently launched NeuralSearch democratizes vector search technology, making natural language understanding accessible to all. It’s built on the same underlying principles as other generative AI tools, but we deploy the latest innovations a little differently to do more for site search and discovery. 

Our machine learning model creates neural hashes of vector representations; it hashes, or compresses, vectors to a fraction of their normal size. These binary formats are easier to compute and store, achieving 99% accuracy at 10% of the cost. We’ve also retained the best of keyword matching, which is still a reliable and formidable technique in search and discovery. 

NeuralSearch makes vector search scalable and practical and combines it with keyword search, bringing the best of both worlds together. Accurate and relevant search results continue to be delivered at the same blazing fast retrieval speed Algolia is known for.

With matching and understanding powering every single query, Algolia NeuralSearch offers entrepreneurs a powerful new solution for helping their customers to discover the right products and pages using the latest in AI technology. 

Start Your Engines with NeuralSearch 

When customers search for things using natural language queries, NeuralSearch grasps their intent. There’s no need to craft elaborate indexes, word lists, or exceptions. AI-powered search understands what customers want, helping entrepreneurs get to market faster.  With query search in 50+ languages, NeuralSearch lets you instantly scale your store internationally with no extra effort and at zero extra cost.

To ensure top performance, customers will want to  enable NeuralSearch click analytics. Clickstream data fuels the platform’s machine learning capability, making it smarter over time.

The NeuralSearch engine gathers new actionable intelligence with every customer interaction and automatically optimizes results. If some products aren’t clicked, those are pushed down. Highly clicked and converted products rise to the top, adding to search relevance. You can also override the automation of NeuralSearch to take advantage of seasonal and other trends. Use manual controls to toggle settings and push hot items to the top of your page. Algolia also provides a free Merchandising Studio to make it easier for you to curate results and adjust the search algorithm to drive higher conversions and more revenue. 

Now it’s your turn. Translate your idea with AI tools and services and the power of Algolia NeuralSearch. To learn the basics and start building, request a demo.

About the authorAbhijit Mehta

Abhijit Mehta

Director of Product Management

Recommended Articles

Powered by Algolia AI Recommendations

What is AI-powered site search?

What is AI-powered site search?

John Stewart

John Stewart

VP, Corporate Communications and Brand
A simple guide to AI search

A simple guide to AI search

Jon Silvers

Jon Silvers

Director, Digital Marketing
How and why events drive search ROI

How and why events drive search ROI

Jaden Baptista

Jaden Baptista

Technical Writer
Ben Franz

Ben Franz

Sales Engineering and Product Leader at Algolia