TrueGradient.AI, a Self-Serve AI software platform provider for transforming global enterprises’ supply chain planning, has secured $700K in seed round funding led by Shastra VC, with participation from Neon, Relentless VC, and noted angel investors including Pratul Shroff, Akash Verma, Abhishek Kapur and Yogesh Kulkarni.
Founded by industry veterans Ankur Verma,Siddharth Shahi,Namrata Guptaand Jasneet Kohli, TrueGradient is built on the team’s collective experience at top-tier enterprises such as Amazon, Walmart, IBM, and Mondelēz and start-ups such as Antuit, Dunzo and Samya.
TrueGradient was born to tackle the challenge of poor value realisation in supply chain AI initiatives. Despite the promise of artificial intelligence, its implementation often falls short of expectations. A staggering 75% of AI projects fail to deliver significant results, particularly in supply chain planning, where inefficiencies can erode profit margins by up to 5%.At the heart of legacy systems’ underwhelming performance lies a fundamental issue: user dissatisfaction stemming from the rigidity of the platforms.
The rise of Self-Serve AI platforms aims to solve this issue by empowering frontline professionals—planners, analysts, and data scientists—allowing them to take control of AI tools. It grants them the autonomy to conduct experiments, fine-tune parameters, and run scenarios precisely tailored to their specific business contexts.
TrueGradient is creating the industry’s first Self-Serve platform at the intersection of AutoML and supply chain planning. The platform drives end-to-end planning decisions, helping companies improve service levels while minimising costs. Key functionalities include demand forecasting and optimisation of the network, inventory, price, promotion, and assortment. The platform utilises an AI Neural Engine to help companies realise doubledigit forecast accuracy improvement, up to 30% reduction in days of supply, and up to 30% reduction in promotion spending.
“The fresh capital will accelerate the product development and fuel global expansion. We’re committed to building a world-class solution that sets new industry standards. Our focus remains on delighting our user community with exceptional experiences,” said Ankur Verma, CEO of TrueGradient. “TrueGradient AI acts as a complimentary resource for the supply chain team, enabling them to build tailored solutions for their specific business requirements” added Namrata Gupta, COO at TrueGradient.
The seed round was led by Shastra VC, a prominent venture capital fund, “What differentiates TrueGradient is its deep IP in Neural Net Architecture and engineering, which is the underlying innovation enabling a Self-Serve system. The self-serve approach and super quick, smooth onboarding could be game changers for SMBs and mid-market. The accuracy their models drive can generate significant value for enterprises” said Ashis Nayak, Founding Partner at Shastra VC.
Within the first 12 months of their journey, TrueGradient has built a loyal customer base in India and North America, consistently delivering exceptional value.
“We firmly believe that the lackluster performance of traditional systems stems from a clear and fundamental problem: dissatisfied users, or low user adoption. To fulfill our mission of delighting our user community, every feature we develop is aimed at making the platform more intuitive, flexible, and self-service oriented,” said Jasneet Kohli, CRO at TrueGradient. “To ensure our self-serve application delivers an effortless user experience, we’re also harnessing the power of Large Language Models across our entire platform. This advanced technology enhances everything from streamlining data integrations to providing responsive customer support, creating a smooth and intuitive journey for our users,” addedSiddharth Shahi, CTO at TrueGradient.
TrueGradient AI was founded to address speed-to-value gaps in supply chain planning and analytics initiatives. Through our innovative Self-Serve AI Supply Chain Planning platform, we are helping companies grow revenue and margin by improving demand forecast accuracy, inventory, and promotion investment decisions. The platform uses causal neural models, probabilistic machine learning, and reinforcement learning to maximise service at the lowest cost.
