Bengaluru-based startup Simplismart announced a $14 million Series B funding round on October 27, 2026. The round was led by Dallas Venture Capital, with Nvidia also participating. The deal valued the four-year-old startup at approximately $100 million including the new investment. The new funds will go toward expanding the company's AI model inference engine and orchestration platform, as well as growth in North America and other global markets.
Funding round details
The round was entirely primary investment, meaning the $14 million went directly to the company. Dallas Venture Capital led the round, joined by Accel, Shastra VC, and Micromax, while Nvidia was noted among the round's participants. Given the investment size and valuation figures, this deal is a significant milestone for a relatively young startup outside the circle of large AI infrastructure companies. At the same time, the round finances the company's move to its next stage of growth, including expanding the platform and entering new markets. According to TechCrunch, the deal is being assessed precisely as a bet on a software solution aimed at running AI models more efficiently. The names on the investor list, and Nvidia's participation, show that interest in this direction continues to grow. The official announcement of the round confirms the same goal: the funds will be spent on developing the AI inference engine and orchestration platform. This decision targets the problem at the center of the company's work, advancing the question of using compute power efficiently when running models.
How Simplismart's technology works
Simplismart's software sits between AI models and compute infrastructure. By tuning the process of deploying and managing models, it optimizes response speed, request throughput, and compute costs. The goal is to let customers get more value from their existing GPU fleet, and in some cases to run models with fewer GPUs. This approach matters especially where compute power is limited or expensive, because the efficiency gained from each GPU directly affects serving costs. The platform takes on the task of managing model inference and organizes the connection between infrastructure and model. As a result, companies can answer more requests with the same hardware capacity or handle the same workload with less capacity. This kind of optimization is especially noticeable in heavy workloads such as video generation, where every second of latency and every additional GPU translates directly into cost.
According to TechCrunch, Simplismart's software operates between models and compute infrastructure and optimizes response speed, request throughput, and compute costs.
Customers and revenue figures
The company demonstrated the practical result of its technology with a concrete example. AI video creation platform InVideo cut GPU serving costs by 56 percent with the help of Simplismart. The company also works with HeyGen, Higgsfield, and enterprise AI startup Ema. Indian cloud provider Yotta uses Simplismart's technology within Shakti Studio for serverless AI inference. This customer list shows the technology being applied across diverse areas, from video creation to enterprise solutions and cloud infrastructure. Financial figures also confirm the growth pace. The company's annualized revenue run rate grew 14-fold over the past six months, reaching an eight-figure sum. This figure is based not on contracted recurring revenue but on customers' recent usage volume. More than half of revenue comes from the US, showing that the company's main market is already North America. The new investment announcement specifically highlights further expansion in that market as a goal. The EIN Presswire announcement likewise points to expanding the inference engine and orchestration platform and growing in global markets as the round's main goal.
Partnership with Nvidia and next plans
Nvidia's involvement is not limited to financial investment alone. Alongside the investment, Nvidia also worked with Simplismart on technical integrations, including a collaboration noted around the company's Dynamo inference software. In addition, Nvidia helped introduce the startup to potential customers and partners. This kind of partnership can matter for a young company in terms of technical fit and go-to-market, because integration with a leading player in the GPU ecosystem builds customer trust. The next plans are clearly set out in the announcement: expanding the inference engine and orchestration platform and growing in North America and other global markets. Given that more than half of revenue already comes from the US, these plans aim to further strengthen an existing strong position. At the same time, the core promise of the company's technology remains unchanged: helping customers get more value from their existing GPU capacity and, in some cases, making it possible to run models with fewer GPUs. The funding round, customer examples, and technical partnership with Nvidia together define the next stage of work in this direction.
