Megan Harper
Developing GenAI applications is often a complex and fragmented process. Aman Sharma and his co-founder saw this firsthand and built Lamatic to simplify AI adoption, enabling developers to build, deploy, and optimize AI applications with ease.
1. What inspired the creation of Lamatic, and how has its vision evolved since its inception?
Aman Sharma: Me and Chuck ( my cofounder ) were initially building Dinnerfy (an app that creates meal plans, recipes, and grocery lists). While building, we soon realized the complexity of building GenAI Apps with too many disparate tools and methodologies. We thought of a platform that simplifies GenAI adoption, removes inefficiencies, and enables organizations of all sizes to harness cutting-edge AI without requiring a steep development curve. We started by addressing the growing pains of early adopters in the GenAI field. The goal has since evolved to include technologies such as edge deployments and integrated telemetry that not only streamline operations but also enable accessibility and creativity.
2. What challenges in the development and deployment of GenAI is Lamatic looking to solve?
Aman Sharma: We observed that many developers were spending excessive time on foundational setup and infrastructure instead of building appealing applications. To tackle these challenges, we developed Lamatic, a straightforward platform that manages complex technical aspects, enabling developers to concentrate on what truly matters: Building innovative AI solutions.
3.Lamatic offers a fully managed PaaS with low-code capabilities. How does this help with GenAI application development?
Aman Sharma: Our low-code platform dramatically reduces development time. We developed an easy Visual Studio that allows you to drag and drop AI components like Lego blocks, use pre-built templates for typical AI use cases, and Collaborate smoothly across teams.
4. The platform integrates VectorDB powered by Weaviate. How does this feature enhance context retrieval and performance?
Aman Sharma: We provided built-in Weaviate VectorDB for fast, accurate search and context retrieval. This allows our users to create more agile AI systems, especially for tasks like answering questions and searching documents without managing their own VectorDB infrastructure. Semantic search capabilities ensure that the AI comprehends the context better and delivers more pertinent results.
5. How does your edge deployment’s ultra-low latency enhance high-performance GenAI workflows?
Aman Sharma: Edge deployment reduces latency by shortening the distance between the Client Request and the AI servers. Our edge deployment offers considerable advantages, including quicker response times for AI applications, improved scalability when necessary, and cost efficiency through intelligent resource management.
6.Lamatic provides tools for monitoring and optimization. How do features like logs, traces, and actionable reports help users maintain reliability?
Aman Sharma: Monitoring solutions provide real-time visibility into developers’ apps. They can quickly identify issues, track performance, and make data-driven adjustments broken down by workflows and individual nodes. I’ve witnessed firsthand how this enables teams to develop more dependable AI apps.
7. The GenAI space is rapidly evolving. How does Lamatic stay ahead of industry trends to remain competitive?
Aman Sharma: We combine strong technical research with user-focused development. As CTO, I spend a substantial amount of time researching emerging AI technologies and developing them into practical applications. We use an agile development cycle with weekly releases, and our open product roadmap and active community contact ensure that we’re making exactly what our customers want. This method of integrating technology innovation and direct customer feedback has been important to our ability to stay on the bleeding edge of GenAI development.
8.Lamatic has a flexible price plan, running from free trials to tailored company solutions. How does this fit the different needs of its users?
Aman Sharma: We believe in making AI accessible to everyone. That is why our pricing is straightforward and flexible, starting with a free developer-focused plan and ending with Enterprise-Focused solutions. This strategy has truly made AI innovation accessible to anybody with an idea.
9. What do you find most rewarding and challenging about leading Lamatic’s journey?
Aman Sharma: The most exciting component is seeing how people utilize Lamatic to innovate and solve real-world challenges, such as automatic internal procedures and developing new AI-powered products. The challenges include keeping ahead in a competitive market and ensuring that the platform expands effortlessly to meet various user expectations. Every day, we wake up with the most important question: how can we remain relevant to our customers? The approach is to reduce the most powerful AI capabilities to elegant simplicity.
10. Could you provide me an example of a client using Lamatic to produce breakthrough results?
Aman Sharma: One of my favorite clients is 84000: Translating Buddha’s Words. This non-profit approached us because it wanted to use artificial intelligence to transform its translation process. We not only accomplished but exceeded their objectives by developing new ways to engage with their target audience across many touchpoints, such as natural search, chatbots, AI summaries, and more.
11. What does success mean to you, and what are your aspirations for Lamatic in the next five years?
Aman Sharma: For us, success includes democratizing AI by making it available to individuals and organizations who want to fully grasp GenAI’s promise without becoming mired down in technological complexities. Looking ahead five years, we intend to expand the Lamatic ecosystem, build a strong developer community, and establish ourselves as the world’s leading platform for GenAI innovation.
12. What does a normal day look like for your team at Lamatic?
Aman Sharma: A typical day at Lamatic is dynamic and goal-oriented. It starts with team stand-ups, where we go over priorities and agree on customer-focused projects. Throughout the day, we combine brainstorming meetings, technical sprints, and in-depth user feedback analysis. Our ownership-driven culture implies that each team member is fully responsible for their domains, from inspiration to deployment. We maintain continuing connections with our customers through numerous feedback sessions, community forums, and direct channels. This strong cooperation helps us to quickly iterate on features and ensure that our solution satisfies user requests. Our culture is also very transparent and ownership-driven, giving every team member access to all insights and customer access. Our engineers routinely work with customers to better understand their needs and create solutions that address real-world problems.
Editor’s Note
Aman Sharma is tackling one of AI’s biggest pain points—usability. Lamatic streamlines GenAI development with low-code tools, edge deployment, and built-in monitoring, making advanced AI accessible to developers and businesses without the usual complexity.
