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Kognitos executives take on enterprise AI's proof problem at AI TechWorld 2026. CEO Binny Gill and Chief AI Officer Neeraj Mathur take the Santa Clara stage September 2 with the ROI question and a live look at neurosymbolic AI running real finance work - deterministically, auditably, in English as code. August 25, 2026 08:00 ET | Source: Kognitos Inc SAN JOSE, Calif., Aug. 25, 2026 (GLOBE NEWSWIRE) - Kognitos, the pioneer of neurosymbolic AI for business and finance automation, today announced its CEO and Founder Binny Gill and Chief AI Officer Neeraj Mathur will take the stage at AI TechWorld 2026 on September 2 at the Santa Clara Convention Center, tackling two questions that are becoming increasingly difficult for enterprises to ignore: Can AI automation prove its business value, and can it be trusted to execute mission-critical work? AI is moving into parts of the business where mistakes have consequences. In finance and operations, that means the standard for enterprise AI must be higher than simply producing a convincing answer or automating another task. The investment needs to deliver measurable business value. The work itself needs to run predictably, with logic that can be understood, governed and audited. That is the territory Gill and Mathur will cover at AI TechWorld. Gill will look at what businesses should count as return on AI automation, including where value builds over time rather than stopping at an initial efficiency gain. Mathur will show what happens when AI is put to work inside real financial processes, and why deterministic execution matters once AI starts acting on the systems that run the business. Binny Gill asks what AI is actually producing Gill will start his session at 10:00 a.m. on the AI TechWorld Main Stage, focusing on "Dr. Strangetoken or: How I Learned to Stop Prompting and Love the Tokens I Never Spent." His session takes aim at a problem facing executives as AI spending moves into operating budgets. Traditional automation metrics can capture cost savings or headcount efficiency, but they may miss the broader value AI creates across the business. Gill will draw on enterprise deployments to examine measures including cycle time compression, exception reduction, workforce reallocation and decision quality, as well as the difference between automation gains that plateau and those that compound as the business expands their use. "Businesses have never measured people by how much thinking they did in a day. We measure what they produced. AI should be no different," said Gill. "The conversation needs to move away from how much AI an organization is consuming, and towards the outcomes it is creating. If we cannot show where the value comes from, we do not have an AI strategy. We have an AI bill." Neeraj Mathur puts enterprise AI to work At 11:30 a.m. on the AI TechWorld Expo Stage, Mathur will take the next step with "Automating Enterprise Finance in Plain English: A Live Look at Neurosymbolic AI in Production." Through a live product walkthrough, Mathur will demonstrate how neurosymbolic AI can automate financial and operational workflows using English as code business instructions, including invoice processing, exception management, and orchestration across multiple enterprise systems. The session will show the difference between using probabilistic AI to understand intent and using deterministic execution to carry out approved business rules predictably and with an audit trail. "Finance is a useful proving ground for enterprise AI because there is nowhere for vague promises to hide," said Mathur. "Customers may begin with one or two processes such as accounts payable or reconciliation, but that is rarely where the story ends. Once you can show that AI can execute real work reliably, that the business can understand the logic and that the process can be governed, you start moving from individual automation projects towards finance transformation." That progression reflects what Mathur has seen among Kognitos customers, where initial finance use cases have expanded into broader finance transformation initiatives. The demonstration will give attendees a live view of that operating model, showing how plain-language processes can become executable automation while keeping the underlying business logic readable, governed and auditable. Event details * AI TechWorld 2026 takes place at the Santa Clara Convention Center in Santa Clara, California. * Binny Gill will present on September 2 from 10:00 a.m. to 10:25 a.m. on the Main Stage. * Neeraj Mathur will present on September 2 from 11:30 a.m. to 11:55 a.m. on the Expo Stage. About Kognitos Kognitos automates business operations with the first neurosymbolic AI platform engineered for deterministic, hallucination-free execution at enterprise scale. Built for finance, supply chain, and operations teams that cannot tolerate probabilistic errors, Kognitos turns tribal and system knowledge into documented, AI-refined automations using English as code, creating a dynamic system of record that enhances productivity and decision-making. Every workflow is readable, auditable, and governed in English, with humans in control of the logic that runs the business. With its patented Process Refinement Engine, Kognitos delivers faster ROI, lower costs, and empowered teams across hundreds of enterprise use cases. Headquartered in San Jose, California, Kognitos is backed by leading investors including Khosla Ventures, Prosperity7 Ventures, Engineering Capital, and Wipro Ventures.

Kognitos targets finance AI risks with new Context Graph platform. 5 August 2026 Kognitos has introduced a new artificial intelligence platform designed specifically for finance and accounting departments, aiming to address one of the biggest concerns surrounding enterprise AI: accuracy in high-risk financial processes. Announced at Ai4 2026 in Las Vegas, the company's new Context Graph for Finance is intended to help finance teams automate routine work while ensuring that every action follows predefined business rules instead of relying solely on the probabilistic outputs generated by traditional large language models. The launch reflects a broader trend across enterprise software, where organisations are moving beyond conversational AI towards systems capable of executing regulated business processes with greater transparency and control. A Different Approach to Enterprise AI Unlike general-purpose AI models that generate responses based on statistical probability, Kognitos has developed its platform around an organisation's own financial structure and operating procedures. The system creates a digital representation of key financial relationships, including suppliers, invoices, ledger accounts, approval hierarchies, spending policies and internal controls. AI agents then use this structured information when carrying out financial tasks, ensuring decisions are based on company-specific rules rather than generalised predictions. For finance departments, where incorrect journal entries, duplicate supplier payments or unauthorised approvals can lead to compliance issues, the ability to trace every automated action is becoming increasingly important. Initial Focus on Accounts Payable The first application of the platform is accounts payable, one of the most labour-intensive functions within finance organisations. Invoice verification, payment approvals, policy compliance and exception handling often involve multiple manual reviews across different business systems. By embedding organisational knowledge into its decision-making process, Kognitos aims to automate these workflows while maintaining oversight and producing a complete audit trail. The company plans to extend the platform into additional finance functions over time, creating a unified foundation for wider financial operations rather than deploying separate automation tools for individual tasks. Capturing Institutional Knowledge One of the platform's distinguishing features is its ability to preserve operational knowledge that often exists only within experienced finance employees. Many accounting processes rely on informal practices developed over years of experience, including handling unusual supplier situations, interpreting internal policies or managing recurring exceptions. Traditionally, this knowledge is difficult to document and can be lost when employees leave an organisation. Kognitos says its platform records these approved practices within a structured framework that can be updated as business policies evolve, allowing finance teams to refine automated processes without rebuilding AI models from scratch. Growing Demand for Governed AI The launch comes as finance executives face increasing pressure to improve efficiency while maintaining strict regulatory compliance. Unlike customer service or marketing applications, finance operations require systems that produce consistent, repeatable outcomes supported by comprehensive documentation. Every automated action may need to withstand internal reviews, external audits or regulatory scrutiny. As a result, many organisations are placing greater emphasis on AI platforms that provide explainable decision-making, human oversight and detailed audit records rather than purely conversational capabilities. Context Graphs Gain Industry Attention The announcement also highlights the growing interest in context graph technology within enterprise AI. Rather than relying solely on language models, context graphs organise relationships between business entities, policies, approvals and operational rules into structured networks that AI systems can reference during decision-making. Industry analysts increasingly view this approach as an important step towards making AI more suitable for regulated industries, where understanding organisational context is as important as interpreting natural language. Kognitos said it was recognised as a sample vendor for context graph technology in two Gartner Hype Cycle reports published in 2026, reflecting wider industry interest in context-aware enterprise AI. A Shift Towards Operational AI The introduction of Context Graph for Finance illustrates how enterprise AI is evolving from assisting users with information to executing business processes under defined governance. Rather than replacing finance professionals, platforms such as Kognitos are being designed to automate repetitive work while operating within established company controls and approval structures. As organisations continue integrating AI into core business functions, technologies that combine automation with transparency, traceability and policy compliance are likely to become increasingly important. For finance leaders, the focus is shifting from whether AI can perform a task to whether it can do so consistently, accurately and in a manner that satisfies auditors, regulators and corporate governance requirements.