Specialized AI: How vertical AI makes a difference

If it feels like AI is everywhere these days, it’s true. The global AI market is growing by 19% yearly, and 65% of organizations now regularly use generative AI. Why does AI adoption grow like a snowball? 79% of small and medium enterprise owners want to understand how AI can transform their business challenges. It's not about having AI — it's about having the right AI. And here, we meet a “but.”

The truth is, business leaders need an AI that doesn't just compute but truly understands the nuances of their industry. In this article, we’ll pull the curtain on the much-talked-about vertical AI and show you what it does for specific industries. Let’s explore how specialized AI vertical applications create value, solve problems, and give you a competitive edge.

What is vertical AI?

In its very name, vertical means going deep into the layers of specific sectors in a precise way, learning, and constantly improving in the process based on your input and feedback.

Vertical AI focuses on industry-specific challenges and delivers tailored context-aware solutions. These solutions combine advanced language models with specialized domain knowledge to understand context, make complex decisions, and autonomously execute entire workflows. AI agents function as intelligent systems capable of adapting to new situations, managing nuanced tasks, and improving over time based on past experiences.

Here are the main aspects of vertical AI models:

• Targeted problem-solving within the industry context
• Deep integration of domain-specific knowledge
• Customized data processing tailored to unique operational requirements
• Training on industry-specific datasets to understand nuanced domain terminology
• Ability to navigate complex industry regulations

In short — it’s an AI that doesn't just understand technology but speaks the native language of healthcare, finance, or logistics (or any other industry it’s tailored to). Vertical AI models are like expert consultants, bringing deep domain knowledge that generic AI simply cannot match. For instance, a vertical LLM in healthcare might process medical records differently than a similar model in financial services, reflecting the unique language, regulations, and data structures of each domain.

What is horizontal AI?

Similarly, horizontal stands for a more universal solution with a model applied to various industries. These AI systems are designed to perform common computational tasks (like natural language processing, predictive analytics, and computer vision) that can be adapted to various contexts. 

Characteristics of horizontal AI:

• Flexibility across different technological domains
• Capability to handle standard computational problems
• Adaptability to multiple business unit requirements

Horizontal AI covers the general needs of business units and teams across various industries. For example, a sales team in the finance and travel industry might use the same model with the basic functionality and capabilities to automate or optimize some routine tasks. 

Horizontal vs vertical AI: What’s the difference?

The distinction between vertical vs. horizontal integration of AI lies in the focus of application: depth versus breadth. Vertical applications are like precision instruments, carefully calibrated to solve specific industry challenges, while horizontal AI operates more like a universal remote – functional across many scenarios but lacking specialized depth. 

Vertical AI emphasizes:

• Deep domain expertise, using AI to solve highly specific problems in industries like healthcare, finance, or manufacturing.
• Vertical infrastructure, including vertical models or vertical LLMs designed for precise data interpretation.
• Precision-focused verticalized software and vertical apps that streamline operations for a defined niche.

This vertical strategy allows creating specialized vertical platforms and seamless integration with market software. Horizontal AI, on the other hand, is designed for broad applicability across industries. 

Horizontal AI stands upon:

• Generalized computational capabilities that can adapt to diverse applications.
• Easier cross-industry implementation, making it versatile for businesses needing adaptable technology.
• Horizontal models that prioritize scalability and wide-reaching impact over deep customization.

While vertical versus horizontal integration defines contrasting strategies, they often complement each other. Businesses might deploy vertical AI solutions within specific areas while leveraging horizontal AI for foundational processes.

However, with the ability to cover many needs of modern businesses, these types of AI aren’t all you can find in the market.

Other specialized AI

The landscape of AI verticals extends beyond simple vertical and horizontal classifications, encompassing a range of sophisticated technological approaches. The first and most well-known one is generative AI. Most LLMs you use regularly (like ChatGPT 4o, Google Gemini, Perplexity, or Claude Anthropic) are generative. These AI models represent:

• Advanced content creation capabilities
• Ability to generate novel computational outputs
• Sophisticated learning from existing data structures

Specialized models like multimodal AI and edge AI show the evolving complexity of each technology vertical:

• Edge AI brings processing power to the source — devices equipped with IoT sensors — allowing industries like manufacturing, logistics, and autonomous vehicles to make lightning-fast, on-site decisions without relying on cloud connectivity.
• Multimodal AI handles multiple types of data at once — like text, images, and speech — making it useful for complex AI vertical solutions such as personalized healthcare or smart assistants.

Creating such sophisticated models needs a great deal of tech prowess. Machine learning specialists and Python engineers are the main leads in building and refining these AI systems, ensuring that the underlying code is adaptable and reliable. These advancements show us very closely how AI solutions constantly evolve to solve specific problems in smarter, more efficient ways, and connect the previously scattered parts and processes. 

Now that we know the types of AI present in the arena these days, let’s figure out what advantages you get from adopting vertical AI.  

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The benefits of vertical AI

As we already discussed, vertical AI is all about specialization, precision, and depth, while horizontal AI is about adaptability, scalability, and breadth. Now, what exactly makes businesses fall in love with vertical AI solutions? Let's break down their major benefits.

Enhanced precision and efficiency

Vertical AI is about creating hyper-focused tools that understand the intricate nuances of specific industries. A McKinsey study revealed a striking example: in customer service, generative AI increased issue resolution by 14% per hour and reduced agent handling time by 9%. Even more impressive, it cut agent attrition and manager intervention requests by 25%.

The secret? These AI models are trained on industry-specific data, allowing them to provide insights that generic solutions simply can't match. For instance, in healthcare, AI like PathAI can analyze medical records with depth and precision that would take human experts countless hours.

Unlocking previously impossible capabilities

Vertical AI is opening doors to capabilities that were once thought impossible. Take JusticeText, an AI that can automatically review hundreds of hours of video footage – a task that would be prohibitively time-consuming for human lawyers. Or Axion Ray, which helps manufacturers analyze massive volumes of product data across IoT, telematics, and production systems! 

With a cookie-cutter approach, it would take more time to fine-tune the model to your case, but with the precise adjustment to your domain and case, the possibilities are much wider.

Solving real-world challenges

The most exciting aspect of vertical AI is its power to address specific industry challenges with tailored solutions. In healthcare, AI vertical solutions improve workflows by helping doctors reduce paperwork, enabling more time for patient care. For instance, verticalized software integrates automated tasks like medical record management and diagnostic support.

In legal services, vertical AI applications automate time-consuming processes such as contract review, document drafting, and case analysis. In construction, AI vertical platforms are improving safety protocols and estimating predictive maintenance. So the implication here is clear — what solves problems is worth the cost. 

Cost-effective innovation

Contrary to what many think, vertical AI isn’t just reserved for the big tech players — it’s for businesses of all sizes. In fact, experts believe that vertical AI's market value could easily surpass that of traditional vertical SaaS by at least 10 times. How? Let’s talk dollars and cents. 

By automating repetitive tasks, vertical AI slashes payroll expenses. Vertical AI capabilities replace entire teams with smart, efficient AI agents. These agents don’t just take over tasks — they handle entire workflows, end-to-end, with consistency and precision. The result? Reduced human labor costs and a leaner, more cost-effective operation. It’s not just about saving money; it’s about achieving higher efficiency without compromising quality.

Competitive advantage

As AI becomes more prevalent, businesses that don't adopt vertical AI risk falling behind. Many industries now see companies actively seeking AI-enabled tools out of fear of being overtaken by more technologically advanced competitors.

The high level of specialization in vertical AI solutions also makes them much harder for competitors to replicate, offering early adopters a unique and lasting edge. By leveraging the best LLM APIs, these solutions can be fine-tuned to meet the specific needs of an industry, making them even more valuable and difficult to duplicate.

• Industry-specific data training 

It should be taking comprehensive datasets sourced directly from your industry. Integration of both structured and unstructured industry-specific information is crucial here, as well as continuous learning capabilities that refine uSo, Vertical AI isn't just a technological trend – it's about creating solutions so precisely tailored to an industry's needs that they become indispensable.

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Practical steps to implementing vertical AI

When considering vertical applications, start by conducting a deep dive into your industry landscape. This means understanding the unique pain points, workflows, and data ecosystems that define your sector. Unlike horizontal AI approaches that offer broad, generalized solutions, vertical AI focuses on creating highly specialized tools that speak directly to industry-specific needs.

Key steps for vertical AI implementation include:

1. Conduct a comprehensive internal audit of your current processes, identifying areas where specialized AI could provide maximum impact.
2. Map out the specific challenges unique to your industry that generic AI solutions fail to address.
3. Develop a clear framework for how vertical AI models can integrate seamlessly with existing infrastructure.
4. Create cross-functional teams that blend technical expertise with deep industry knowledge.
5. Establish clear metrics for measuring the effectiveness of your vertical AI implementation.
6. Start with small, focused pilot projects that demonstrate clear value.
7. Invest in continuous training and change management and build internal capabilities alongside external partnerships.
8. Develop robust data governance frameworks and create feedback loops for constant refinement.
9. To ensure complete safety and easy data migration, opt for cloud-hosted development or ready solutions with good security protocols.

The strategy moves from initial assessment and planning through implementation, optimization, and continuous improvement. The goal is to transform your technological approach from generic to genuinely customized. But how do you choose the solution to cover your business needs fully?

Choosing the best-fit vertical AI solutions

Selecting the right vertical AI solution is like finding a technological partner that speaks your language. The most powerful vertical applications go far beyond generic tools, offering a deep, nuanced understanding of your specific business ecosystem.

Here are the critical features to look for in a top-tier vertical AI platform:

• Nuanced domain terminology comprehension

Nuanced domain terminology comprehension involves creating solutions that understand intricate professional language specific to your sector. This requires advanced natural language processing capable of recognizing subtle industry jargon, contextual variations, and specialized communication patterns that generic AI might miss.

• Regulatory compliance and navigation

Regulatory compliance and navigation means building tools designed to understand and navigate complex, sector-specific regulations. This includes automated compliance checking, real-time regulation monitoring, and adaptive systems that can interpret and respond to evolving legal frameworks within your industry.

• Native professional interface design

Native professional interface design focuses on creating interfaces that feel intuitive and natural to industry professionals. This involves developing user experiences that seamlessly integrate with existing workflows, minimize learning curves, and provide role-specific interactions that feel like an extension of current work processes.

• Deep contextual understanding

Deep contextual understanding ensures processing that goes beyond surface-level data analysis. This means developing AI capabilities that can extract meaningful insights, understand complex relationships, and provide predictive intelligence that captures the nuanced ecosystem of your specific industry.

• Budget considerations for vertical AI solutions

Budget allocation for vertical AI implementation depends on organizational size and complexity. Key cost components include initial implementation, annual licensing, customization, and ongoing support and training. Plan for a phased approach, starting with pilot projects and scaling incrementally to manage financial risks and demonstrate value.However, the cost of trial and error is high, as you see from the varied budget spending we described. And what if the solution you pay for doesn’t justify itself?

The alternative to off-the-shelf solutions is a tailor-made system to cover your business and domain needs as best. The problem is, only best-in-class AI and ML engineers can develop and train a model on the necessary use cases and datasets, fine-tune it, and adjust the interface to your team’s requirements. But we happen to have them in our team!

Our AI implementation expertise

Our expertise in AI development sets us apart, offering your businesses a custom approach to transforming your technological capabilities. What makes our team your reliable choice is our deep understanding of specific industry challenges and creating tailored AI solutions that address real-world problems.

Take the retail industry, for instance. COAX doesn't just offer a one-size-fits-all approach; we dive deep into the unique complexities of retail operations, developing AI-powered tools that improve everything from inventory management to customer experience. But our company's impact doesn't stop there. Our solutions for the travel industry show an ability to understand customer needs. From intelligent booking systems to personalized travel recommendations, we develop and adjust AI solutions that make travel smoother and safer.

So, if you’re looking to optimize your operations or enhance your touchpoints with customers, COAX has the expertise, vision, and tech prowess to help you skyrocket.

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AI vertical applications vs. other business improvement tools

In this comprehensive overview, we'll explore both general business applications of AI and industry-specific tools that redefine productivity and efficiency.

Deep Vertical AI

Since vertical AI is all about tailored, very domain and use-case-focused solutions, let’s start with not an off-the-shelf tool, but with Deep Vertical AI, a company dedicated to creating custom AI solutions for enterprise clients. Their expertise spans many capabilities, including large language models (LLMs), retrieval-augmented generation (RAG), AI agents and multi-model systems, and domain-specific AI applications. 

By focusing on these vertical AI specialties, Deep Vertical AI is empowering companies to tackle their unique challenges with precision and efficiency. And their solutions are use case focused too — they offer you analysis AI agents as well as portfolio-monitoring AI agents to streamline decision-making and optimize investment strategies.

SymphonyAI

SymphonyAI offers a suite of AI-powered SaaS applications designed to address core challenges across various industries. These vertical AI solutions leverage predictive and generative AI to provide real-time insights, precise analysis, and optimized operations, enabling businesses to make more informed decisions.

SymphonyAI offers vertical AI solutions tailored to industries like retail and CPG (demand forecasting, customer insights, supply chain optimization), financial services (fraud detection, AML compliance, investigation hubs), trading and investing (portfolio analysis, credit modeling), industrial (intelligent manufacturing, predictive asset intelligence), media (analytics, predictive insights), and enterprise IT (service management, asset management, automation).

A precisely estimated demand also means less waste, and this is a great example of how your business can use vertical AI for sustainability optimization. With this vastness of offerings, SymphonyAI's verticalized AI tools are tailored to the specific needs of each industry, delivering tangible results.

Automat

When talking about vertical market software, we couldn’t miss Automat. It’s a business automation assistant that enables companies to build custom workflows and accelerate their operations. This vertical AI tool can be applied across a wide range of industries, including insurance, e-commerce, healthcare, private equity, legal, and construction. 

Automat's capabilities extend to automating tasks such as claims processing, order refunds, billing, and contract management, streamlining processes, and enhancing efficiency for organizations operating in these diverse vertical markets.

OpenAI's Operator

On the horizon, OpenAI is poised to unveil its new AI agent tool, "Operator," which could revolutionize how we interact with technology. OpenAI's Operator will launch in January 2025, and is designed to function as a vertical AI agent that can directly engage with your computer, performing tasks on your behalf. Unlike traditional AI models that wait for specific commands, Operator takes the initiative, perceiving its digital environment and making decisions independently.

Whether automating routine tasks, optimizing web browsing, or managing complex workflows, Operator represents a significant leap forward in verticalized AI technology, blurring the line between AI and everyday digital interactions. But to see the power of vertical AI, it’s always better to see focused, domain-specific solutions.

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List of AI models for industry-specific application

Let's see how these specialized AI solutions empower businesses to reach new heights of efficiency and success.

Vertical AI in science and research

In scientific research and development, the ability to navigate the ever-growing volume of data and literature is often a matter of life and death (literally). Here, vertical AI solutions like Causaly, the first production-grade generative AI platform specifically designed for the life sciences industry, become a go-to way out of numerous problems. Causaly empowers biomedical research teams to boost their productivity by up to 90%. What are the typical challenges tackled?

Poor target selection is a leading cause of clinical trial failures, with approximately 50% of trials falling short due to a lack of efficacy. Causaly helps manage the data overload, reduce bias, and separate signal from noise. This allows them to drive more effective target selection and focus their discovery programs.

Another challenge is uncovering the complex interactions between genetic, environmental, and lifestyle factors that contribute to diseases. Here, Vertical AI solutions, like the Molecule Programming Foundational Model developed by 310.ai, are developed to transform how researchers study and utilize biology. By compressing 4 billion years of nature's evolution into a powerful AI model, 310.ai's vertical AI platform enables researchers to build a more comprehensive understanding of disease biology.

AI vertical applications for law and insurance

While the life sciences industry has embraced the power of vertical AI solutions, the legal and insurance sectors are also witnessing a profound transformation. For instance, Harvey’s Professional Class AI platform allows lawyers to delegate intricate tasks to their domain-specific AI assistant, streamlining workflows and enhancing productivity. The platform's research capabilities enable legal professionals to quickly find answers to complex questions, with relevant citations, across areas like legal, regulatory, and tax. 

Similarly, in the insurance industry, vertical AI solutions like Sixfold are revolutionizing the underwriting process. Sixfold is a risk assessment AI platform built exclusively for insurance underwriters, boosting their efficiency, accuracy, and transparency.

Sixfold's vertical AI solution ingests an insurer's underwriting guidelines and uses them to identify positive, negative, and disqualifying risk factors. It then collects data from various sources, including the underwriting submission and supporting documents, to generate tailored recommendations and risk analysis. This allows underwriters to make more informed decisions and triage submissions that best align with the insurer's risk appetite.

Now let’s move to the most treasured industries of our company, where the large language model use cases are our target interest, expertise, and focus of attention (and a great pleasure discovering and applying the horizontal versus vertical integration of AI and ML). Let’s start with e-commerce.

E-commerce vertical LLM solutions

Vertical integration of AI into eCommerce is turning the traditional way of leading a business on its head. From intelligent site searches that understand exactly what you're looking for (even when you can't quite describe it) to AI-powered product recommendations that feel almost mind-reading, these technologies just rock.

If you need a merchandising copilot, that’s OmniThink.AI. It uses AI-driven solutions for predictive product design, intelligent merchandising, marketing optimization, and omnichannel intelligence. Merchandising teams gain data-backed insights for inventory and placement, product design teams can anticipate market demands with trend forecasting, and marketing teams can craft highly targeted, personalized campaigns for significant revenue growth, enhanced margin optimization, and faster, more responsive product development cycles.

Another efficient intelligence engine is Lily AI. Sometimes, your users struggle to find something online because they can't quite describe it — well, Lily AI solves that problem. This is where AI vertical image recognition and natural language processing mix nicely. Its capabilities deliver contextual suggestions, understand intent, and incorporate trends, driving up to 35% of purchases, a 10% conversion lift, and 15% higher click-through rates. For product content generation, Lily AI automates brand-aligned descriptions, cutting costs and time while ensuring SEO optimization and brand consistency. 

Last but not least, Aforza Vertical AI. Aforza represents a holistic AI solution specifically designed for consumer product companies, crashing complex business challenges:

• 1-click predicted order with demand forecasting for inventory planning, automated order generation, real-time integration with inventory systems, and a mobile-friendly platform. 
• Cross-sell and upsell recommendations with an AI-driven engine, dynamic product suggestions, performance tracking, and optimization tools.
• Perfect store visit summary featuring AI-powered account interaction analysis, personalized visit insights, real-time recommendations, and CRM integration.
• Promotion design recommendations using data-driven strategies, historical performance analysis, and dynamic simulation capabilities for campaign refinement.
• Image recognition and store scene understanding with advanced visual analysis, automated compliance reporting, out-of-stock detection, and workflow integration for corrective actions.

These three AI solutions represent the very definition of “new and efficient” in eCommerce technology, each with its unique capabilities that transform how you understand, engage, and serve your customers online to drive revenues and loyalty.

Travel vertical application boost

From AI-powered trip planning to hyper-personalized booking experiences, vertical AI technologies are breaking down traditional barriers and creating seamless travel solutions.

Avitor.ai is making waves already, delivering autonomous AI agents that are changing the game for brokers and online travel agents. With a Knowledge Hub powered by 2 million flight records and over 25,000 sales queries, Avitor.ai isn't just another chatbot — it's an expert advisor that understands the nuanced world of private jet travel. 

Its innovative features like AI Quote Reader and Automated Empty Leg Updates mean brokers can now access high-quality quotes and real-time flight information with unprecedented speed and accuracy.

Another game changer in travel AI is Mindtrip, a San Francisco-based startup with a new approach to trip planning. It’s an an AI assistant that doesn't just book your travel, but understands your travel style, suggests personalized experiences, and even helps you collaborate with friends and family on trip planning! All with the ability to generate detailed itineraries, provide visual recommendations, and create collaborative travel experiences.

From private jet charters to global adventure planning, these AI technologies are creating a more connected, intelligent, and personalized travel ecosystem.

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Specialized AI for business success

Unlike horizontal AI, which is a jack-of-all-trades, vertical AI is a master of one — diving deep into the unique challenges of your sector. From automating complex tasks to providing industry-specific insights, vertical AI isn't just a tech trend — it's a strategic tool that helps businesses work smarter, faster, and more efficiently.

Some numbers are very impressive: In customer service, generative AI has already increased issue resolution by 14% per hour and cut agent attrition by 25%. And we're just getting started! Companies like SymphonyAI and Automat are creating AI solutions that can automate everything in your workflows, and in e-commerce and travel, vertical AI solutions cut costs, predict demand, plan customer trips, and help you make better decisions.

The best part? This isn't just for tech giants anymore. Even smaller businesses can now access sophisticated AI tools that were previously out of reach. Whether it's retail, travel, legal services, or healthcare, there's a vertical AI solution that can help you work smarter, not harder.

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FAQ

What is vertical software?

Vertical software is a specialized type of technology designed to address the unique challenges and requirements of a specific industry, such as healthcare, finance, or retail. Unlike general-purpose solutions, it provides deep, tailored functionality for a particular sector.

What is the difference between vertical vs horizontal AI?

Vertical AI focuses on solving specific industry challenges with deep domain expertise, while horizontal AI provides broad, adaptable solutions across multiple industries.

How do I know if my business needs vertical AI?

If you have industry-specific challenges that generic tools can't solve, struggle with complex workflows, or need deep insights into your sector, vertical AI could be a game-changer for your business.

Who can benefit from vertical AI?

Businesses of all sizes can benefit, from small startups to large enterprises. It's particularly valuable for industries with complex, specialized workflows like healthcare, legal services, insurance, and e-commerce.

Are vertical AI solutions expensive?

While initial costs can be higher, vertical AI often provides significant long-term value by increasing efficiency, reducing errors, and offering insights that generic solutions can't match.