Discover how E42.ai, led by CEO Animesh Samuel, pioneers Cognitive Process Automation, surpassing traditional RPA by leveraging AI and NLP for unstructured data handling, streamlined enterprise processes, and cost-effective solutions with rapid ROI.
Read the full interview here:
TimesTech: How does E42.ai’s Cognitive Process Automation (CPA) differ from traditional Robotic Process Automation (RPA) and enable handling unstructured data for informed decision-making?
Mr Animesh: In today’s data-driven world, businesses are challenged with the complexity of information in various formats. While automation is essential, what truly empowers organizations is intelligent automation—a concept endorsed by Gartner’s projection of the global hyperautomation market reaching $1.1 trillion by 2026.
While Robotic Process Automation (RPA) can provide rule-based automation and handle in structured data, E42, a no-code Cognitive Process Automation (CPA) platform has generative AI, Natural Language Processing (NLP), machine learning, Intelligent Document Processing (IDP), and more technologies at the core. This allows the AI co-workers built on E42 to process unstructured data from various sources like emails, documents, and social media allowing for intelligent automation across enterprise functions from simple, repetitive tasks to complex processes that require understanding and decision-making.
Although RPA companies do offer automation, the solutions only work with templates and fall short in terms of processing unstructured data. The AI co-workers can comprehend and process unstructured data from various sources, thereby allowing organizations to extract valuable insights and make informed decisions. Additionally, the platform gives enterprises the ability to foresee and continuously bring process improvements in response to changes, trends, patterns, and more. This ensures that the AI co-workers are capable of understanding context, judgment, prediction, and learning, surpassing the capabilities of traditional RPA.
TimesTech: How does E42.ai streamline the process for enterprises by offering comprehensive solutions across various business functions, minimising the need for engaging multiple vendors?
Mr Animesh: Navigating the complexities of enterprise operations can be daunting, especially when multiple vendors are involved. Managing disparate systems, coordinating different software solutions, and ensuring seamless integration across various business functions can become overwhelming.
The AI co-workers, built on E42 simplify the process by providing end-to-end automation across various business functions such as finance, HR, and customer service, thereby streamlining processes and reducing the need for multiple vendors. By centralizing automation efforts on a single platform, organizations can streamline workflows, decrease complexity, and boost efficiency. This strategy mitigates the difficulties of managing multiple vendors and ensures uniformity and compatibility across various processes. These AI co-workers collaborate with each other resulting in enterprise-wide intelligence and improved business outcomes.
TimesTech: Can you explain how E42.ai ensures cost-effective automation with proven ROI through its ready-to-deploy solutions with a short implementation timeframe?
Mr Animesh: In the ever-changing world of enterprise operations, staying ahead necessitates not just automation but cost-effective solutions with a swift return on investment (ROI). That’s where E42 steps in.
We offer ready-to-deploy solutions that ensure cost-effective automation with a proven ROI and a low Total Cost of Ownership (TCO). Any AI co-worker built on the platform, once deployed, can automate at least 50% of tasks from day one, demonstrating a significantly shorter turnaround time (TAT). Our solutions, which leverage pre-built automation modules and customizable workflows, expedite the deployment process and minimize implementation costs. This enables businesses of all sizes to start using the solutions within 48 hours of deployment. These solutions streamline processes and minimize manual efforts, enhancing productivity and leading to measurable outcomes, and with a licensing model based on delivered value, significant cost savings and a quick ROI are ensured.
TimesTech: How does E42.ai leverage NLP, NLU, and NLG to enhance conversational AI capabilities, facilitating human-like interactions in enterprise automation?
Mr Animesh: The importance of NLP in business cannot be overstated. According to a Harvard Business Review article, NLP tools have advanced rapidly and can help with writing, coding, and discipline-specific reasoning.
Building on this foundation, E42 harnesses the power of NLP, along with natural language understanding and natural language generation (NLG), to bring human-like interactions via enterprise automation. The AI co-workers built on E42, equipped with these advanced technologies, understand and respond effectively to user queries and commands. This enables seamless communication with documents and comprehensive end-to-end process automation. By integrating conversational AI into workflows, we streamline communication, enhance user experience, and drive engagement, thereby improving the usability and accessibility of automation solutions across various business functions.
TimesTech: Regarding ethical AI and explainable AI, how does E42.ai ensure its AI agents make fair and ethical decisions while mitigating risks, especially in sensitive domains like finance and legal?
Mr Animesh: The intersection of ethics and AI is a critical area of focus, particularly when AI is entrusted with decision-making in high-stakes fields. E42 ensures that the AI co-workers built on the platform make fair and ethical decisions while mitigating risks, particularly in sensitive domains like finance and legal. Our approach begins with the implementation of on-premises LLMs, which bolster data security and transparency. These models undergo rigorous validation protocols, including stringent checks for biases and our commitment to compliance is reflected in our autoscaling PaaS cloud, which meets data residency requirements. This cloud-native infrastructure is also deployable on-prem or in private clouds, ensuring adaptability for sectors with specific compliance needs, such as BFSI and legal. Through optimal training parameters and transfer learning techniques, we minimize the risk of hallucinations and prompt toxicity in our AI algorithms.
Additionally, our commitment to explainable AI ensures transparency in decision-making processes, enabling stakeholders to understand and trust the outcomes. By prioritizing fairness, transparency, and regulatory compliance, we uphold ethical standards and foster trust in AI-driven solutions across sensitive domains.
TimesTech: How does E42.ai continue to innovate and stay ahead in the rapidly evolving landscape of enterprise automation, given its recognition by major research companies and software giants?
Mr Animesh: With the ascent and widespread use of generative AI, it becomes increasingly important for our R&D team to stay at the forefront of AI research. Leveraging generative AI and latest hardware, including GPUs and TPUs, is integral to our strategy, enabling us to scale up training and inference processes efficiently. Within our architecture, proprietary multimodal networks and LLM models for generative AI, facilitated through LLMOPs, play a crucial role.
Our team encourages innovative ideas and experiments with various architectures, training methodologies, and datasets. This iterative process allows us to identify the most effective solutions for specific challenges and continuously refine our models. In our development process, we’ve introduced new evaluation benchmarks to more accurately assess the capabilities of emerging models. The platform’s continuous enhancements bring about highly scalable, human-level cognition, covering a range of functionalities like image and document understanding, conversational AI, intelligent extraction, audio-video transcoding, and face recognition. Through these innovations, we not only meet supply and demand challenges but elevate the overall user experience with a platform that evolves at the forefront of AI capabilities.
