Strategic AI Integration: From Concept to Real-World Impact

Artificial Intelligence (AI) is reshaping industries and redefining how companies operate, compete, and grow. But successful AI implementation isn’t about following trends or experimenting with technology for its own sake. It requires thoughtful planning, clear business objectives, and a firm commitment to delivering measurable value. At Coherent Solutions, we guide our clients through this journey—helping them move from interest to impact with real, tangible outcomes.

AI Is Not a One-Size-Fits-All Solution

AI, particularly Large Language Models (LLMs), offers powerful capabilities, but they are not the answer to every business problem. As Lina Šiumetė, General Manager of Coherent Solutions Lithuania, notes:

“Modern large language models are powerful tools that can greatly enhance productivity and automate complex processes. However, businesses should approach AI implementation strategically, ensuring the technology genuinely solves specific operational challenges rather than complicating or obscuring them.”

This philosophy is central to how we work with clients. We start every engagement by defining the actual business challenge at hand. AI can only be effective when its application is aligned with clear strategic needs—whether that’s streamlining processes, improving decision-making, or enhancing customer experiences.

Practical Applications Across Industries

Coherent Solutions has implemented AI-driven solutions across diverse sectors, always rooted in solving real-world business challenges.

In construction tech, we supported an innovative roofing software company that provides contractors with digital tools to estimate roof dimensions using aerial imagery. Our team built an AI-powered service that extracts a detailed blueprint of a roof’s surface—including facets and total area—and developed an API to deliver this functionality via a scalable AWS platform. This enabled the client to modernize a traditionally manual process, helping them improve accuracy and efficiency for roofing contractors nationwide.

In retail, we developed an Optical Character Recognition (OCR) solution for a leading eyewear chain. The AI system automated the transcription of prescription data—used in more than 200 stores—reducing human error and significantly accelerating service time.

For another eyewear client, we enhanced their Virtual Try-On (VTO) experience by enabling an AI-powered feature that removes real glasses from a customer’s face during live video. This allowed users to virtually try on frames without needing to take off their current ones—dramatically improving engagement and conversion rates.

These examples illustrate how AI, when implemented with a strategic lens, creates operational efficiencies, cost savings, and better customer experiences—without overcomplicating the core business model.

Our Guiding Principles for AI Integration

To ensure our solutions deliver lasting value, we follow several key principles:

- First, every AI project begins with clearly defined business objectives. A vague goal leads to vague outcomes. By targeting specific needs—like speeding up a workflow, reducing error rates, or gaining real-time insights—we ensure that AI investments are directly tied to business outcomes.

- Second, we prioritize data quality. AI systems are only as good as the data they learn from. That’s why we help clients establish strong data governance frameworks to maintain clean, accurate, and relevant datasets.

- Third, we take a human-centric approach. AI should enhance—not replace—human expertise. By maintaining a “human-in-the-loop” model, we ensure that ethical considerations, domain expertise, and human judgment guide all decision-making processes.

Finally, we encourage organizations to start small—pilot, learn, and scale. A controlled rollout allows time to test assumptions, fine-tune performance, and build internal trust before scaling the solution across teams or markets. Continuous monitoring and recalibration ensure AI systems stay aligned with evolving goals and maintain long-term effectiveness.

Responsible and Informed AI Adoption

Strategic success is only one part of the equation. Responsible AI practices are equally important. At Coherent Solutions, we help clients understand the risks involved in AI deployment—from data security and intellectual property exposure to bias in training data. As Lina Šiumetė emphasizes:

“AI models, particularly LLMs, present challenges such as potential exposure of sensitive data, intellectual property risks, and unintended biases inherent in training data. Effective risk mitigation strategies, combined with human oversight, are essential to responsible AI usage.”

Technology selection is another critical aspect. Whether our clients are considering proprietary tools like OpenAI’s GPT-4 or Anthropic’s Claude, or open-source models such as Meta’s LLaMA, we provide expert consultation based on their data governance needs, security concerns, regulatory requirements, and long-term objectives. Our goal is not to implement whatever the client asks for, but to guide them toward the best, most secure, and scalable solution.

The Goal: Strategic Impact, Not Technological FOMO

Adopting AI because it’s fashionable can do more harm than good. The real objective is to implement technology that aligns with strategic goals and delivers tangible results. At Coherent Solutions, we believe in making technology work for the business—not the other way around.

Through our client-focused, responsible, and pragmatic approach, we help organizations harness the full potential of AI. The result? Sustainable growth, enhanced efficiency, and a competitive advantage that lasts.