What types of AI models can be deployed with Simplismart?

Simplismart supports a wide range of generative AI models, including Large Language Models (LLMs), Vision-Language Models (VLMs), Diffusion models for image generation, and Speech models for transcription and translation. You can also import your own custom models from various cloud repositories.

Does Simplismart support deployment in private clouds or on-premise?

Yes, Simplismart offers BYOC (Bring Your Own Cloud) and on-premise deployment options. This allows you to deploy the platform in your private cloud, on-premises data center, or regulated environment, ensuring full control over your hardware and compliance requirements.

How does Simplismart optimize inference performance and cost?

Simplismart utilizes a modular inference stack with custom-built CUDA kernels, paged attention, and various backend optimizations like KV Caching and quantization. This allows for rapid auto-scaling, lowest TTFT and E2E latency, or maximized throughput at affordable costs, adapting to specific use case needs.

Simplismart

Simplismart is an MLOps platform that enables fine-tuning and deployment of GenAI models with a fast inference engine. It offers scalable, cost-effective deployment across various cloud providers and on-premise setups.

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At a glance

Pricing

Paid · Usage-based · Enterprise

Free tier

API

Yes

Skill level

Advanced

About

What is Simplismart?

Simplismart is an MLOps platform designed for fine-tuning and deploying generative AI models with a focus on speed and efficiency. It provides a fast inference engine and allows users to deploy models in their own cloud or on-premise environments, with native integration across 15+ cloud providers. The platform supports a wide range of models including LLMs, VLMs, Diffusion, and Speech models, and offers a library of over 150 open-source models or the option to import custom weights. Key features include rapid auto-scaling for spiky traffic, modular inference stack with custom CUDA kernels for optimized latency and throughput, and enterprise-grade security with GDPR, ISO 27001, and SOC 2 compliance.

Best used for

Ideal for developers and data scientists who need to deploy and scale generative AI models, optimize inference performance, and manage deployments across multiple cloud providers. Especially valuable for achieving low latency for voice agents, high throughput for document processing, and cost-effective content generation.

Capabilities

Key features

Fine-tune GenAI models
Fastest inference engine
Deploy to AWS/Azure/GCP
Rapid auto-scaling
Custom CUDA kernels
150+ open-source models
Import custom models

Audience

developer data scientist startup founder enterprise b2b developers teams

Integrations

awsazuregcp

FAQs

Common questions

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