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Schedule Interview NowAt Softaims, I have been fortunate to work in an environment that values creativity, precision, and long-term thinking. Each project presents a unique opportunity to transform abstract ideas into meaningful digital experiences that create real impact. I approach every challenge with curiosity and commitment, ensuring that every solution I design aligns not just with technical requirements, but also with human needs and business objectives. One of the most rewarding aspects of my journey here has been learning how to bridge the gap between innovation and practicality. I believe technology should simplify complexity, enhance efficiency, and empower people to do more with less friction. Whether building internal systems, optimizing workflows, or helping bring client visions to life, my focus remains on developing solutions that stand the test of time. Softaims has encouraged me to grow beyond coding—to think about design, communication, and sustainability in technology. I see every project as part of a larger ecosystem, where small details contribute to long-lasting results. My daily motivation comes from collaborating with people who share the same passion for doing meaningful work, and from seeing the tangible difference our efforts make for clients around the world. More than anything, I value the culture of learning and improvement that defines Softaims. It’s a place where ideas evolve through teamwork and constructive feedback. My goal is to continue refining my craft, exploring new approaches, and contributing to solutions that are not only efficient but also elegant in their simplicity.
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Our client required a robust AI chatbot solution for Telegram that could automate customer interactions and streamline business services like bookings, payments, and information dissemination. The goal was to create a digital assistant that could not only engage with customers but also integrate with business operations for a seamless user experience. Our team's contribution was comprehensive, covering every aspect of the chatbot's development and deployment. Leveraging our proprietary low-code platform and 'react-conversation' framework, we built a system that could interpret complex customer queries and execute a series of automated tasks (agents and jobs). We developed custom routing and commands that break down conversations into elemental components, enabling the chatbot to understand and respond to diverse client needs accurately. For the chatbot's memory, we integrated MongoDB, Redis, and Neo4j databases to store detailed context about each client, allowing the system to improve its interactions over time by remembering past requests and learning from each conversation. This setup has made our AI Business Assistant not just reactive, but proactive in enhancing the customer experience. By utilizing Google Cloud services, we ensured that our chatbot solution is scalable, reliable, and secure, capable of handling the demands of over 250 active business users in Telegram. Our role was to maintain and support these business assistants, ensuring their performance and adaptability. The project has been a success, demonstrated by the seamless operation of dozens of business assistants and the satisfaction of our client base. The AI Laboratory we previously developed plays a critical role in maintaining these chatbot systems, offering a clear interface for business owners to manage their digital assistants. This AI Business Assistant is more than a tool; it's a digital workforce multiplier, designed to help businesses improve their services and customer interactions without increasing their workload.
My client needed a responsive and versatile platform to swiftly create and deploy Telegram chatbots for businesses. We delivered the AI Laboratory - a web-based tool that allows users to build and tailor AI-driven assistants with ease. As the development team, we crafted the entire solution, which includes a user-friendly UI presenting a neural-graph for visual bot configuration. My custom 'react-conversation' framework marries low-code efficiency with Node-RED, and integrates with Google Cloud for scalability. In our role, we: - Designed the UI for configuring AI models and conversation parameters. - Implemented a low-code framework to streamline bot creation. - Developed the backend infrastructure for robust, scalable chatbot deployment. The AI Laboratory has successfully launched numerous business assistants, now serving over 250 users. Clients can effortlessly adjust prompts, choose AI vendors, and manage conversation settings for a tailored user experience. My tool is proven to enhance customer engagement, with rapid setup and flexible AI model integration at its core.
The challenge for this project was to develop a powerful low-code framework capable of deconstructing human conversation patterns and effectively managing client interactions for digital assistants. Named 'react-conversation,' this Node-RED framework was designed to respond to client demands dynamically, executing agents and jobs as needed and guiding conversations in meaningful directions. Our contribution to 'react-conversation' was in creating a sophisticated yet accessible framework that could be integrated seamlessly into various chatbot systems. The framework comprises four core packages: Auth Package: This module controls access to the chatbot services, enabling monetization strategies by regulating usage. Message Bus Package: It serves as a collection point for all types of client communications, including audio, video, PDFs, and text, storing them for downstream processing. IO Package: Utilizing advanced AI tools, this package converts various file types into text, preparing the content for the conversational analysis phase. Conversation Package: The heart of the framework, it disassembles client requests and employs a router to navigate the conversation flow, triggering appropriate commands and managing job queues. Integrated with our AI Laboratory, 'react-conversation' leverages a neural-graph UI to simplify AI configuration. This enables users to connect and manage AI chatbots within minutes, highlighting the framework's intuitive design. The low-code nature of 'react-conversation' provides users with the flexibility to map conversations onto flows that represent their unique business needs. Our Node-RED framework allows for the configuration of various AI aspects, such as language model vendor, conversational parameters, dynamic agent integration, and memory strategies. Currently, the framework is well-documented and nearing its release as an open-source library for the Node-RED community. This will empower users to manage conversations with AI support, making sophisticated chatbot development accessible to a broader audience. The success of 'react-conversation' lies in its adaptability and the empowerment it offers businesses in crafting interactive, intelligent digital assistants. It stands as a testament to our commitment to innovation and our expertise in creating tools that harness the power of AI for effective communication.
Bachelor of Commerce (BCom) in
2008-01-01-2012-01-01
in Ruby/ROR course
2014-01-01-2015-01-01
in Ruby on Rails developer
2015-01-01-2015-01-01