Preamble

AI is no longer an experiment - it has become a practical tool that is already reshaping how online businesses operate. And unlike the dramatic headlines about "job replacement," the real story is much simpler and far more valuable: AI gives businesses something they could never access before - a tireless, accurate, and highly attentive sales assistant.

If you work in e-commerce, you already know how much the buying experience depends on a good salesperson. A great salesperson does something remarkable: they listen, notice details, offer alternatives, and explain why a particular product is right for the customer. With them, the buyer feels confident, the store earns revenue, and the salesperson earns their commission.

Reproducing this experience online has always been nearly impossible. No human can monitor thousands of visitors at once, understand their intentions, or adapt recommendations in real time.

• It understands user intent, not just keywords
• Suggests relevant products without bias
• Explains its recommendations clearly
• Works 24/7 without taking a commission from each sale

While e-commerce is a very clear and relatable example, the same principle applies to any digital experience where users need better navigation through your content, whether it's articles, news, documentation, legal materials, educational portals, or internal knowledge bases.

Despite our strong background in e-commerce, our extensive experience across multiple IT domains means there are virtually no limitations to how AI can be implemented to improve user experience.

If you're reading this page, you're already considering how AI can improve your business. This is exactly where we help. We transform AI into a predictable, controllable tool that works in the interests of your customers and your revenue.

Our AI Journey

Our experience with AI didn't begin with the recent wave of generative models. Long before AI became mainstream, we were already building systems that analyzed user behavior, predicted intentions, and adapted content dynamically.

One of our early projects, back in 2012, was a behavioral prediction engine for a large online portal. The system analyzed user actions, built patterns, and used optimal-path algorithms to identify the most likely user persona. Based on this prediction, it dynamically adjusted the interface and content. The more data the system collected, the more accurate its predictions became.

Our Portfolio of AI Solutions

Over the years, we delivered multiple AI-related solutions across different industries:

• Emotional speech analysis - detecting tone and sentiment in voice recordings
• Medical analytics - processing and interpreting clinical data
• Educational data processing - performance evaluation and personalized content routing
• Content rewriting and semantic transformation
• Image recognition and classification pipelines
• And many other solutions that we unfortunately cannot showcase publicly

The Turning Point: ChatGPT Era

The challenge with traditional AI systems was always the same: they required powerful servers, expensive GPU infrastructure, and complex architecture to handle multiple concurrent requests.

This changed dramatically on November 30th, 2022, when ChatGPT was released. We had tested GPT-3 in 2021 - it was promising, but not suitable for production-grade conversational logic. GPT-3.5, however, crossed a critical threshold: for the first time, a model was both affordable and high-quality enough to build real AI assistants.

After validating the new technology, we invested heavily into research and started offering AI-driven solutions to our clients. Every solution we build becomes more polished with each implementation, and we are steadily moving toward converting some of them into full SaaS platforms.

The Simplest AI Search

Our entry-level AI search is the fastest way to bring natural language understanding to your website. Despite its simplicity, it already outperforms traditional search engines, including solutions like ElasticSearch, when it comes to interpreting real user intent.

This search can be trained on any catalog in just a few hours. For example, we adapted this version to the product catalog of our client Rainier Arms in the firearms industry.

Why AI Search Performs Better Than Standard Search Engines

Most users cannot formulate their queries precisely. If a user names a product incorrectly or uses casual language, semantic search often fails.

AI also explains why each result is relevant. Unlike Google-style keyword matching, AI provides clear reasoning such as:

• "Ideal for duck hunting due to its accuracy and versatility"
• "Provides reliable performance for waterfowl hunting"

This explanation layer can be fully customized to match your industry and tone of voice.

Built-in Resistance to Search-Based Attacks

Traditional search fields are a common attack vector for script injection and spam queries. AI-based search allows us to identify suspicious behavior, block harmful patterns, and, if necessary, automatically suspend problematic sessions.

Cost Considerations

This version uses OpenAI Vector Storage, which makes it extremely fast to implement but slightly more expensive to operate. On average, a query costs around $0.003 - perfectly fine for low or moderate traffic, but not ideal for high-volume websites.

• The fastest way to test AI on your site
• The ideal option for MVPs or proof-of-concept
• A great starting point before moving to the Cost-Effective Hybrid Search

Cost-Effective AI Search

This version delivers the same high-quality natural-language understanding as our simplified AI search but operates 10× - 15× cheaper per request. It is designed for websites with growing traffic or long-term scalability requirements.

The only additional step is a short data-preparation phase: we take 2-4 days to analyze your catalog, optimize descriptions, and structure the information so that the AI model can interpret it with maximum accuracy.

How Data Preparation Boosts Search Quality

In the Rainier Arms example, we expanded product descriptions using AI and added structured attributes based on real user search behavior.

Before implementing the search engine, we pre-generated and embedded the following types of information into each product:

• Best use-cases (hunting, self-defense, sport shooting, home protection)
• Ideal customer profiles (beginners, women, hunters, professionals)
• Non-suitable scenarios, helping the AI avoid recommending products in the wrong context

These enriched descriptions dramatically improve the accuracy of AI-driven search results, because the model works with structured, meaningful attributes instead of raw text.

When You Already Have Good SEO Descriptions

If your catalog already contains strong SEO-optimized descriptions, we don't need to rewrite them. However, to unlock the full potential of the search engine, we still recommend analyzing:

• Common search patterns
• Frequent user questions
• Use cases your descriptions may not currently reflect

This allows us to generate professional, AI-ready descriptions that cover all relevant scenarios and elevate your natural-language search to the next level.

AI Search With Follow-Up Questions

This version builds on the foundation of our simplified AI search but adds an essential layer of intelligence: the ability to ask clarifying questions when the user's request is too broad or ambiguous.

The implementation time is almost identical to the basic AI search, but the user experience becomes significantly more refined. Instead of returning a long list of loosely relevant items, the system narrows down intent through short, conversational prompts.

Key Advantages

Who Should Choose This Version?

This option is ideal for businesses that:

• Have a large or complex catalog
• Often receive broad or vague customer questions
• Want a "conversation-like" search experience without implementing a full AI chat
• Value deeper insights into their customers' intent

Smart Product & Content Suggestions

Most recommendation engines on the market work in a very narrow "Amazon-style" manner: "Users who bought THIS also looked at THAT." Useful, but superficial.

It's like walking into a shoe store and having a salesperson wordlessly place several boxes in front of you. No context. No explanation. No understanding of your needs. Just boxes.

A Great Salesperson Works Completely Differently

• If you have foot-support issues, they point you to a pair that helps with that
• If you prefer a sport style, they find something that matches your taste
• If you care about waterproof materials, they highlight exactly why a certain pair is the right fit

They don't simply recommend - they explain, guide, and personalize. This is exactly what traditional recommendation tools fail to do. And this is exactly what our system fixes.

Why This Tool Is Different

Our engine doesn't just output a list of "related products." It recognizes user preferences and generates contextual explanations tailored to each individual. It mimics how a skilled salesperson communicates, but does it instantly and consistently for every visitor.

How It Works Under the Hood

• We process your visitor data (from on-site analytics or imports like Google Analytics)
• We pre-generate user preference profiles and AI-enhanced product descriptions
• The system monitors user behavior quietly in the background
• With a single lightweight AI call, it retrieves the matching pre-generated content

When the visitor clicks a recommended product, the page displays a version of the description that reflects their personal preferences. For end users, the experience simply feels like "being understood instantly."

Promoting Priority Products - Transparently

If you have items you want to promote first (seasonal, overstock, or high-margin products), you can mark them as priority. The system will recommend them whenever appropriate and explain why, keeping recommendations honest and trustworthy.

A Pathway to a Full Conversational Assistant

Since the logic already understands user preferences, it can be seamlessly extended into a conversational AI that answers product questions and provides comparisons, aligned with your tone and business rules.

Advanced Chat With Hybrid Search Integration

Most AI assistants on the market are powerful, but expensive. Typical SaaS AI chat platforms charge $0.50-$1.50 per conversation, which makes large-scale usage expensive very quickly. This isn't because vendors are greedy; it's because maintaining high-quality conversational context requires keeping the entire dialogue history in memory, which is costly.

We solved this problem differently.

Why Our Assistant Costs 1-2 Cents Per Session

We developed a smart memory-compression algorithm that allows the AI to operate only on the essential information from the conversation. Non-critical details are compressed or discarded, and only the relevant context remains available to the model.

Whenever possible, the assistant uses a rich cut-off knowledge base (a trimmed version of your content). If the knowledge base isn't enough, it seamlessly switches to your local database with prepared product or content data.

Pricing Does Not Depend on Catalog Size

Most conversational solutions charge based on catalog size. Our assistant doesn't. Whether your catalog contains 100 items or 100,000, the search cost remains ~$0.001 per search (as validated in our live demo).

How It Works in Practice

It behaves like a knowledgeable salesperson who understands preferences, context, and constraints.

Business-Driven Behavior

Just like our Smart Suggestions Tool, the assistant can promote the products you want to highlight - naturally and transparently, without manipulating the user. Its tone of voice can be adjusted to match your brand standards, from strictly professional to conversational.

Not Limited to E-Commerce

Although this demo uses e-commerce data, the assistant can operate on any structured or semi-structured content:

• Legal knowledge bases
• FAQs
• Documentation portals
• Educational materials
• Corporate knowledge systems
• Or any text/content you provide

What Makes Us Different From Other AI Developers

Most AI solutions today come as SaaS products: monthly subscriptions, fixed feature sets, limited customization, and costs that scale as your usage grows. This model makes sense for SaaS providers - they invest heavily into their platforms, so you pay for access, not ownership.

Our approach is different.

Our goal is not to lock clients into subscriptions, but to help them adopt AI in a way that fits their product, their data, and their long-term strategy.

Our Philosophy

Instead of selling a one-size-fits-all SaaS platform, we invest in building a portfolio of AI modules and solutions. Some of them may become SaaS in the future, but right now our priority is simple:

When You Work With Us

• You don't pay for what already exists
• You pay only for customization, data preparation, and new development specifically tailored to your needs
• Once delivered, you can use the solution lifetime, even if one day it becomes a SaaS product

Real-world use cases are what make our tools better. Every implementation helps us refine, improve, and evolve the technology. And that cycle of improvement directly benefits the next client - including you.

In that case, we act purely as developers and integrators: you own the idea, the rights, and the product - not us.