
Simplismart
Fastest Inference Engine for your GenAI Workloads on your Premises11-50 EmployeesActively Hiring
- B2B
- Early StageStartup in initial stages
Simplismart careers
There are 4 major bottlenecks for enterprises to adopt Generative AI -
1. Standardization- There is a need to standardize the workflow orchestration of fine-tuning a model to deploying it and finally observing it in production. Enterprises are planning to build these orchestration layers in-house (imagine pre/post Databricks era for ETL pipelines).
2. Cost- A major concern for enterprises at this point is to justify the RoI for the use-cases(reduce costs/ adding a revenue stream) they want to adopt GenAI for.
3. Data Privacy- Enterprises are concerned about data going out of their cloud, more so with industries like BFSI and Healthcare.
4. Control- Enterprises need precise control over a robust infrastructure to justify their SLAs and want to get rid of constraints like downtime and rate-limits that come with 3rd party APIs.
Simplismart is a cloud and model-agnostic MLOps workflow orchestration platform that helps organizations fine-tune, deploy, and observe models at scale using a declarative standardized language similar to Terraform.
We are focusing on speeding up GenAI models like text-to-image (SDXL), speech-to-text, and open-source LLMs. There is a need to solve the tooling layer to tackle problems like grid-search for most optimal serving performance, multi-tenancy LoRA serving and fast/ efficient scaling.
Simplismart is the fastest inference engine on Nvidia GPUs, supporting upto 280+ tokens/ sec. with Llama3-8B on a single H100 machine.
1. Standardization- There is a need to standardize the workflow orchestration of fine-tuning a model to deploying it and finally observing it in production. Enterprises are planning to build these orchestration layers in-house (imagine pre/post Databricks era for ETL pipelines).
2. Cost- A major concern for enterprises at this point is to justify the RoI for the use-cases(reduce costs/ adding a revenue stream) they want to adopt GenAI for.
3. Data Privacy- Enterprises are concerned about data going out of their cloud, more so with industries like BFSI and Healthcare.
4. Control- Enterprises need precise control over a robust infrastructure to justify their SLAs and want to get rid of constraints like downtime and rate-limits that come with 3rd party APIs.
Simplismart is a cloud and model-agnostic MLOps workflow orchestration platform that helps organizations fine-tune, deploy, and observe models at scale using a declarative standardized language similar to Terraform.
We are focusing on speeding up GenAI models like text-to-image (SDXL), speech-to-text, and open-source LLMs. There is a need to solve the tooling layer to tackle problems like grid-search for most optimal serving performance, multi-tenancy LoRA serving and fast/ efficient scaling.
Simplismart is the fastest inference engine on Nvidia GPUs, supporting upto 280+ tokens/ sec. with Llama3-8B on a single H100 machine.
Finance Controller
In office • Bengaluru
3 days ago
Developer Advocate
In office • Bengaluru
1 week ago
Business Development Representative
In office • Bengaluru
₹15L – ₹20L1 month ago
Admin & Facilities Associate
In office • Bengaluru
1 month ago
Site Reliability Engineer (SRE)
In office • Bengaluru
1 month ago
Technical Support Engineer
In office • Bengaluru
No equity1 month ago
Pre-Sales
In office • Bengaluru
1 month ago
Account Executive
In office • Bengaluru
1 month ago
Product Manager
In office • Bengaluru
1 month ago
Growth Associate
In office • Bengaluru
1 month ago
Devansh Ghatak
Worked as Machine Learning Engineer in Google and Avaamo. CS from BITS Pilani. Love building new things.
Amritanshu Jain
Building Simplismart
Valuation
$0
Funded over
3 rounds
Latest round
