In the modern corporate landscape, contracts play an omnipresent role, regulating relationships, defining obligations, and shaping business outcomes. However, for decades, they have remained static, opaque, and difficult to understand.
In the modern corporate landscape, contracts play an omnipresent role, regulating relationships, defining obligations, and shaping business outcomes. However, for decades, they have remained static, opaque, and difficult to understand.
Aditya Gupta aims to change this situation. As Co-founder and CTO of Sirion, he is leading the transition from contracts as passive documents to contracts as intelligent systems powered by artificial intelligence, capable of reasoning, and integrated directly into business workflows.
Yet, his journey to this point began far from enterprise software, rooted in a deep interest in how systems function beneath the surface. Gupta started programming early, drawn to the idea that what is created once can be scaled infinitely. Over time, this interest transformed from writing code to designing systems capable of serving thousands, and then millions, of users. This progression led him to enterprise software, and subsequently to artificial intelligence, where systems move beyond deterministic logic to support reasoning and decision-making.
At the Indian Institute of Technology (IIT) in Kharagpur, Gupta immersed himself in an environment that emphasized first-principles thinking, problem-solving, and peer learning. Alongside his classmates, he learned to break down complex, ambiguous problems into solvable components.
One significant experience was working on autonomous robotic systems designed for Mars exploration. In such scenarios, human intervention is limited, forcing teams to consider communication gaps, system failures, and machine collaboration. The task was not just engineering, but developing systems capable of operating reliably in uncertain conditions.
By breaking these problems into smaller, manageable parts, Gupta and his team managed the complexity and created functional solutions. These early experiences continue to influence his approach today, combining systems design, scalability, and intelligent automation.
Sirion, founded in 2012 by Gupta, Ajay Agrawal, and Claude Marey, offers AI-powered contract lifecycle management software. Contract management, covering all stages from creation to renewal, has traditionally been a fragmented and error-prone process, despite its central role in business operations.
The founders of Sirion identified a critical gap: contracts form the backbone of enterprises, yet they are treated like rigid, static documents. Users often struggle to locate agreements, interpret obligations, or assess whether new contracts conflict with existing terms. While many CLM tools focused on storage and workflows, they largely ignored intelligence and usability.
Sirion decided to change this approach. Instead of viewing contracts as files stored in repositories, the company began to see them as living systems—entities that must be continuously understood, tracked, and acted upon. By combining Gupta's technical expertise with the legal experience of his co-founders, Sirion positioned itself at the intersection of law and technology.
A key part of this transformation was segmenting contracts into smaller, actionable components. Obligations could then be tracked, monitored, and reported in real-time, ensuring that decisions were based on historical context rather than being created from scratch.
Gupta notes: 'My role has evolved over time, but it is generally at the intersection of AI architecture, product, and strategy. One conscious choice I made was that AI would not be just an add-on layer. At Sirion, it is embedded into the core system. Whether it is clause extraction, risk analysis, or obligation tracking, AI is deeply integrated.'
For Gupta, contract management, like the underlying technology, must remain flexible and adaptive. The Sirion platform utilizes AI and Generative AI (GenAI) and is increasingly moving toward agentic systems. In this model, AI does more than just analyze or generate; it actively participates in workflows.
Sirion's systems are designed to understand contracts end-to-end: analyzing documents, identifying risks, and guiding users on next steps. By leveraging historical data and contextual information, AI surfaces relevant insights directly, reducing the need to manually sift through lengthy documents. In high-confidence scenarios, the system can even act autonomously, accelerating the decision-making process.
He emphasizes that there has also been a shift in the application of generative AI across the entire contract lifecycle. From drafting and negotiation to post-signature management, AI maintains context across different stages, transforming contracts into dynamic intelligence systems. These systems do not merely store information; they actively inform decisions, manage relationships, and drive outcomes.
Nevertheless, implementing AI in the legal domain comes with unique challenges. Accuracy is a non-negotiable requirement: 'almost right' is insufficient. Simultaneously, users must understand how and why decisions are made, making explainability critical. Scale adds another layer of complexity, as enterprises manage millions of contracts in various formats. Underlying it all is the issue of trust.
To address these issues, Sirion created a legal knowledge graph and ontology that anchors AI outputs in domain-specific understanding. Every recommendation is accompanied by clear citations, ensuring transparency. System design focuses on scalability and fault tolerance to handle enterprise-level workloads.
For Gupta, trust arises at the intersection of accuracy and clarity. By making AI decisions transparent and context-driven, Sirion enables users to rely confidently on intelligent systems.
He acknowledges that AI is still evolving. 'Nothing in AI is 100%. The closer we get to the high 90s, 98–99%, the more confident users become. Every decision remains probabilistic, but the system's role is to justify that probability and provide assurance that the outcome is reliable,' he explains.
Gupta views AI as a fundamental pillar of the future, comparable to the shift from telephony to the internet. Its applications span industries from healthcare and climate modeling to scientific discovery.
However, the real challenge lies not in creating possibilities, but in implementing them responsibly. Issues of governance, fairness, and equitable access remain central to the evolution of AI.
Gupta is particularly interested in the rise of agentic systems, which signal a shift from reactive tools to proactive systems capable of operating within workflows. He also points to the convergence of AI with knowledge graphs and the growing emphasis on domain-specific intelligence embedded in enterprise platforms.
He stresses that ethics is an integral part of this journey. Data bias can skew results, making meticulous data curation and the creation of 'golden records' crucial. Accountability and auditability ensure that every AI-driven decision can be traced.
'AI should augment human judgment, not replace it,' says Gupta, emphasizing the importance of transparency, fairness, and human oversight.
Beyond AI, he continues to monitor developments in space exploration, quantum computing, and emerging model architectures—areas that reflect his enduring interest in complex systems.
Sirion's technological path has been closely tied to AWS since 2014. Starting with core compute services, the company gradually expanded its stack to include serverless architectures and, more recently, AI capabilities through Bedrock. AWS has allowed Sirion to scale efficiently, offering a robust, globally deployed, and compliant infrastructure. The partnership extends beyond infrastructure, including close collaboration between Sirion and AWS's research and machine learning teams.
This joint implementation has helped Sirion tackle complex problems, refine model strategies, and accelerate its AI roadmap while maintaining stable performance and scalability.
For Gupta, maintaining the pace of AI development requires both discipline and curiosity. He dedicates time daily to reading about new research, technological shifts, and innovations in fields such as healthcare, generative AI, and quantum computing. Conversations are equally important, whether with colleagues from different disciplines or even with his children, whose questions often spark new perspectives. 'Inspiration is everywhere,' he says.
At the same time, he emphasizes the importance of balance. In a rapidly changing technological landscape, it is vital to stay grounded. Continuous learning, open dialogue, and time spent away from the screen help him maintain the clarity necessary for meaningful innovation.
From designing autonomous systems for Mars to creating intelligent contract ecosystems, Gupta's journey reflects a constant thread: curiosity transformed into scalable systems. At Sirion, this curiosity is now shaping the future of how businesses understand and act upon their most critical documents.
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