Simplismart
AI inference infrastructure and MLOps platform
CORE INFO
Simplismart sells infrastructure software to businesses running generative-AI models in production. Customers use it to deploy and optimize models across managed APIs, dedicated GPUs, private clouds, and on-premises environments while managing latency, cost, scaling, and data controls.
- Series B: $14 million led by Dallas Venture Capital, with NVIDIA, Accel, Shastra VC, and Micromax participating; the round was announced on October 27, 2026, at an approximately $100 million post-money valuation.techcrunch.com
- Revenue run rate: Annualized revenue reportedly grew 14× over the preceding six months, reaching an eight-figure annualized run rate.techcrunch.commoneycontrol.com
- TechCrunch covered Simplismart's funding round and its software for helping companies run AI models with fewer GPUs.techcrunch.com
WHY WE WOULD WORK AT SIMPLISMART
Shape AI's Production Future
Help businesses move generative AI from demos into reliable production through Simplismart's inference and MLOps platform. Your work supports real workloads across healthcare, education, media, voice AI, and enterprise software.
Solve Hard Systems Problems
Work hands-on with CUDA, vLLM, TensorRT-LLM, quantization, KV caching, tensor parallelism, Kubernetes, and Slurm. Optimize the full model-to-GPU stack for latency, throughput, cost, and scale.
Join a High-Growth Company
Simplismart has raised at least $21M, including a $14M Series B backed by Dallas Venture Capital, NVIDIA, and Accel. Reported annualized revenue run rate grew 14× in six months, creating meaningful room to build and advance.
Own Customer-Critical Impact
Your work can directly improve production systems used by companies such as HeyGen, InVideo, Ema, Shiprocket, and Tata 1mg. Customer case studies include 56% lower inference costs, sub-second routing, and 95% prescription-processing accuracy.
Build for a Global Market
More than half of Simplismart's reported revenue comes from the U.S., while the company serves customers across India and international markets. Help expand infrastructure that runs across public cloud, private VPCs, BYOC, on-premises, and air-gapped environments.
Work Where Ownership Matters
Join a 58-person team building a focused platform around a clear principle: one size does not fit all. Engineers and operators can make visible contributions as Simplismart expands its model APIs, dedicated GPU deployments, and custom inference engine.
MARKET AND TRACTION
GROWTH TACTICS
MARKET POSITION
NOTABLE CUSTOMERS
✦ KEY METRICKEY METRICS
✦ KEY METRICCOMPETITIVE ADVANTAGE
PRODUCT AND TECH
AI Model Serving
SimpliLLM, SimpliDiffuse, SimpliScribe, and SimpliSpeak support production workloads across language, diffusion, image, speech-to-text, and voice models. Customers can serve open-source, fine-tuned, and custom models through APIs.
Inference Optimization
Simplismart optimizes model-to-GPU performance using CUDA kernels, quantization, batching, KV caching, tensor parallelism, FlashAttention, speculative decoding, and serving frameworks such as vLLM, Triton, TensorRT-LLM, and LMDeploy.
GPU Orchestration
The platform manages dedicated GPU deployments across hardware including T4, L40S, A100, H100, H200, and B200. Autoscaling, scale-to-zero, scheduling, and Kubernetes or Slurm integration help balance latency, throughput, and infrastructure cost.
Flexible Deployments
Simplismart offers managed APIs, dedicated GPU environments, bring-your-own-cloud, private-VPC, on-premises, and air-gapped deployments. This enables organizations to control data location, network isolation, and compliance requirements.
Model Lifecycle Management
The MLOps platform supports model selection, fine-tuning, deployment, monitoring, and ongoing performance optimization. Customers can import custom weights from cloud repositories and monitor production inference across their environments.