As global demand for artificial intelligence accelerates and strains graphics processing unit (GPU) availability, semiconductor powerhouse Nvidia has joined a $14 million Series B funding round for Simplismart, a Bengaluru-based AI software startup.
Simplismart develops orchestration software engineered to optimize how artificial intelligence models run on existing computing infrastructure, empowering enterprises to maintain high performance while utilizing fewer GPUs.
The investment round was led by Dallas Venture Capital, with participation from Nvidia, Accel, Shastra VC, and Micromax. This fresh influx of capital values the four-year-old startup at approximately $100 million post-money. As businesses worldwide allocate immense budgets toward acquiring high-performance hardware, operating large-scale AI applications reliably and cost-effectively remains one of the industry's most pressing architectural roadblocks.
Bridging AI Models and Infrastructure for Optimal Inference
In the current artificial intelligence ecosystem, different enterprise workloads demand distinct trade-offs across response speeds, total operational costs, and overall model accuracy. Manually configuring and fine-tuning deployment setups to meet precise enterprise criteria requires extensive engineering overhead. Simplismart resolves this challenge by positioning its software directly between AI models and underlying computing hardware, automatically configuring deployment parameters to align with specific business targets.
The startup's proprietary platform adjusts fundamental variables such as response latency, request handling throughput, and overall compute power consumption. By dynamically balancing these levers, enterprise engineering teams can extract significantly greater utility from their existing GPU investments without manually building complex custom infrastructure.
"Nobody actually needs the fastest or the cheapest inference. Companies instead need to run AI models at speeds and costs that make sense for their specific applications."
— Amritanshu Jain, Co-founder and CEO, Simplismart
Core Features and Proven Enterprise Results
Simplismart delivers a flexible deployment framework that supports cloud-native, on-premises, and hybrid enterprise environments. Beyond core inference execution, the platform provides automated resource scaling, model fine-tuning utilities, and detailed telemetry for real-time performance monitoring. Cloud service providers can also leverage Simplismart’s infrastructure stack to build and deliver custom serverless AI inference offerings directly to their client bases.
Key Technical & Commercial Capabilities
- Dynamic Compute Optimization: Tailors latency and throughput thresholds based on strict business requirements.
- Deployment Versatility: Operates seamlessly via Simplismart's platform, private cloud configurations, or on-premises servers.
- Infrastructure Management: Integrates auto-scaling rules alongside full performance monitoring and model fine-tuning tools.
- Serverless Enablement: Empowers cloud partners to build robust serverless AI inference services.
The operational impact of Simplismart's software is already evident across major generative AI platforms. Video-generation provider InVideo successfully reduced its GPU serving expenses by 56% after adopting Simplismart's infrastructure stack. Additional clients leveraging the technology include synthetic media creators HeyGen and Higgsfield, along with enterprise AI platform Ema. Furthermore, major Indian cloud provider Yotta utilizes Simplismart software to power serverless inference capabilities within its Shakti Studio environment.
Financial Traction and Strategic Nvidia Integration
Reflecting strong commercial demand, Simplismart's annualized revenue run rate expanded 14-fold over the past six months, reaching an eight-figure total. This financial metric reflects actual recent customer platform usage rather than long-term contracted software subscriptions, and excludes pass-through payments made to third-party infrastructure providers. Remarkably, more than 50% of the company's total revenue originates from U.S.-based clients, despite maintaining a larger overall volume of customer accounts in India.
Alongside financial backing, Nvidia is actively collaborating with Simplismart on deep technical integrations, specifically surrounding Nvidia’s Dynamo inference software stack. Simplismart engineers are partnering directly with Nvidia solutions architects to refine software interoperability, while Nvidia has begun introducing the startup to prospective enterprise partners and customers globally.
While backing software designed to minimize required GPU counts might seem counterintuitive for a hardware manufacturer, Jain emphasized that making inference significantly more affordable and accessible expands overall market demand. By reducing operational overhead, more organizations can deploy production-grade AI applications, driving long-term demand for high-end computing hardware.
Market Positioning and Expansion Plans
The market for AI model inference software is increasingly competitive, with hyperscalers such as Amazon Web Services, Google Cloud, and Microsoft Azure expanding their own internal optimization suites, alongside Nvidia's first-party software division. However, Simplismart maintains a competitive edge among clients driven by strict service-level agreements (SLAs) and tight total cost of ownership (TCO) constraints by avoiding generic presets in favor of bespoke workload management.
Founded in 2022 by former Oracle engineer Amritanshu Jain and former Google engineer Devansh Ghatak—who initially met during their academic studies at BITS Pilani—Simplismart currently employs a team of 58 specialists. The company intends to direct the newly secured $14 million toward expanding its operational footprint in the United States, hiring engineering talent, and deepening research and development across its core inference engine.