Building Smarter Solutions: Manoj Sharma on Synarion IT’s Journey and the Role of AI in Tech

How has your agency started using AI in development projects? Can you share an example?

Artificial intelligence is no longer just a buzzword at Synarion IT Solutions - it has become an active part of how the team builds and delivers projects. Manoj Sharma explains, “At Synarion IT Solutions, we’ve integrated AI into our development projects to enhance efficiency, accuracy, and user experience.”

One example he points to is a recent mobile app project where AI was used to personalize user experiences. “We used AI-powered recommendation algorithms to personalize content for users, improving engagement and retention,” says Sharma. Beyond front-end features, the team is also leveraging AI behind the scenes for development itself. Tools like automated code testing, bug detection, and predictive analytics are enabling faster delivery cycles and more reliable outcomes.

By blending AI into both the product and the process, Synarion IT has been able to offer clients solutions that are not only functional but also adaptive and forward-looking.

Where Has AI Made the Biggest Impact in Your Development Process?

At Synarion IT Solutions, AI isn’t just a tool for one function - it’s reshaping the entire development lifecycle. Manoj Sharma, CEO of Synarion (synarionit.com), highlights the areas where the impact has been most visible.

“AI assists in generating boilerplate code and automating repetitive tasks, which significantly reduces development time,” he explains. Testing and quality assurance have also seen a major leap forward, with AI-powered tools detecting bugs, optimizing test coverage, and predicting potential issues faster than manual testing.

The company is also leveraging AI for data analysis and insights, enabling smarter app features such as recommendations and predictive analytics. On the user side, AI-driven analytics help refine UI/UX, making applications more engaging and personalized.

Even project management has benefited. “AI predicts timelines and resource needs more accurately, improving delivery efficiency,” Sharma adds.

By integrating AI into coding, QA, data handling, and planning, Synarion has positioned itself to deliver solutions that are not only faster but also smarter and better aligned with client expectations.

The Challenges of Bringing AI Into Real Projects

For Synarion IT Solutions, bringing AI into live projects has been as much about overcoming obstacles as it has been about unlocking opportunities. Quality and accuracy often sit at the top of the list, as Manoj Sharma explains:

“Making sure AI models stay reliable and consistent isn’t always easy, especially when datasets are limited or biased.”

Ethical concerns also remain a constant. Ensuring fairness and preventing bias in AI-driven decisions requires continuous oversight. Security is another pressing factor, with Sharma noting that AI systems “need strong protection to prevent data breaches or misuse.”

Compliance adds further complexity, particularly when working across regions with strict data privacy laws such as GDPR. And even when those hurdles are addressed, the technical side presents its own challenges - integrating AI seamlessly into existing workflows without disruption is no small task.

Advice for Businesses Considering AI

When asked what guidance he would give to companies exploring AI, Manoj Sharma emphasizes the importance of focus and practicality. Businesses, he says, should avoid chasing AI for its hype and instead “start with areas where AI clearly adds value - whether that’s improving efficiency, enhancing user experience, or generating insights.”

He suggests starting with a small pilot project, measuring the outcomes, and then scaling up further. This approach, Sharma explains, not only reduces risk but also ensures ROI while giving teams the time to adapt to AI responsibly.

AI Trends Shaping the Next 3–5 Years

Looking ahead, Manoj Sharma sees AI becoming deeply embedded across the software development lifecycle. He believes that tools for AI-assisted code generation and auto-completion will soon become mainstream, reducing development time and making coding more accessible.

Testing and quality assurance are also set for transformation. “AI-powered testing and predictive maintenance will dominate,” Sharma notes, pointing to the way automation can boost reliability and reduce human error.

Beyond the technical core, he highlights intelligent automation across workflows, from deployment to monitoring, as well as AI-driven personalization, which will give end users hyper-tailored experiences.

Sharma also draws attention to edge AI, where models run directly on devices for faster, real-time performance in areas like IoT, AR, and VR. Finally, he stresses the importance of explainable and ethical AI, especially as new regulations emerge. “Transparency and compliance will no longer be optional,” he says.

Preparing Teams for the AI Shift

At Synarion IT Solutions, preparing the workforce for an AI-driven future is just as important as adopting the technology itself. Manoj Sharma explains that the company has made training a top priority, equipping developers with skills in machine learning, model integration, and data handling.

Teams are also being introduced to generative AI tools for coding, testing, and deployment, which Sharma says “boost productivity while freeing developers to focus on higher-value work.” Beyond the technical, the company is building data literacy and analytics skills, ensuring every team member can interpret and act on insights effectively.

Equally critical are ethics and compliance. Sharma emphasizes responsible AI usage, pointing out that data privacy and fairness in decision-making can’t be overlooked. To round it out, Synarion encourages cross-skilling, enabling developers to master multiple tech stacks and integration methods so they remain versatile as the industry evolves.

The Evolving Role of Human Developers

Even in an AI-first world, Manoj Sharma believes developers will remain at the center of innovation. While AI can generate code or automate repetitive tasks, it’s human developers who will define the vision, logic, and creative problem-solving that drive truly valuable solutions. “AI can assist, but the innovation still comes from people,” he notes. The future of development, then, is less about raw coding effort and more about guiding technology toward purposeful outcomes.

Changing Client Expectations in the Age of AI

The rise of AI has also shifted what businesses expect from IT service providers. Clients are no longer satisfied with just functional software - they want smarter, faster, and more adaptive solutions. As Sharma puts it, “AI-powered features like predictive analytics, personalization, and automation are no longer optional - they’re becoming standard.”

AI-driven tools have also shortened delivery cycles, making faster timelines a baseline expectation. At the same time, businesses are demanding data-driven insights that go beyond dashboards, using AI to guide strategic decisions. Finally, the focus on enhanced user experiences - apps that adapt to user behavior in real time - has become a priority across industries.