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TrueFoundry takes care of the dirty details of production machine learning so you can focus on using ML to deliver value. Training jobs, inference services, LLMs, GPUs and more. On your own infra.

Harness power to deploy and fine-tune Large Language Models on your own Infra

Our LLMOps platform allows you to deploy the best LLMs like Llama2 and Falcon-40B to quickly drive innovation and achieve your business objectives

Deploy Falcon 40B and Llama Models via TrueFoundry - Alternative to GPT Models

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Deploying services using TrueFoundry
LLMOps to enable Q&A on their data
ML Deployments and finetuning jobs on TrueFoundry
ML Deployments and finetuning jobs on TrueFoundry
Cost saving and ease of Kubernetes management using TrueFoundry
Large Language Models for Community benefit

Deploy and fine-tune Llama-2 on your own Cloud

The ChatGPT moment of the open source world is here- Meta released its latest set of open-source large language models called Llama-2,  a collection of pre-trained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters.

How TrueFoundry makes hosting open-source LLM deployments faster, cheaper and secure?

Faster Finetuning
Rapid iteration on own data over open-source LLMs
Lower Cost
Of inference and fine-tuning the best across repos of models
Data Security
Everything on your own infra including on-prem
Time to Value
Get GenAI Apps launched in days instead of months

10x faster LLM deployments


Model repo of open-source LLMs

Access our ready to use model repo of best LLMs and foundation models including Dolly, Llama, Alpaca, Vicuna etc

Deploy LLMs at one click

Optimal settings for deployment and model loading behind the hood with one click deployment

Deploy any HuggingFace model

Native integrations to deploy any HuggingFace models including transformers library and other open-source library

Access auto-generated API end-points

Deploy behind a model server or as a Fast API endpoint. Test OpenAPI specs and integrate API endpoints directly into your product
Check our Model Catalogue
Model catalogue of popular open-source LLMs
Deploy LLMs at one click using TrueFoundry
Deploy HuggingFace or any open source model on TrueFoundry
TrueFoundry auto-generates OpenAPI endpoints when you deploy models

Finetune on your own data


One click finetuning job

Run a finetuning job to be able to try different versions of the model with optimal runtime

Over your own data

Point to your own data path on S3, Databricks, Azure Blob storage and we handle the rest - Infra, node failures, workflows

Hyperparameter tuning

Python APIs to expose parameters for tuning across multiple fine-tuning jobs and checkpoints for avoiding failures issues

Compare across finetuning jobs

Compare metrics across finetuning jobs to select model version that is optimal for your use case and track chain of prompts
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Create finetune jobs in a single click
Use LLMs with your own data on your own cloud
TrueFoundry allows hyperparameter tuning across multiple jobs
Compare finetune jobs to select optimal model version

Only Platform to get your GenAI App running in days


Host Fine-tuned Model

Host fine-tuned Model behind selected Model servers and GPUs and integrate with your Applications

Wrap a WebApp on your LLM

Expose a WebApp for Quick testing of your GenAI App with different teams

Control Ethical Quality

Integration with Guardrails to control the ethical quality of Large language models
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Lower costs with full security


Everything on your own infra

Run on your own infra including multi-cloud instances over AWS, GCP, Azure and on-prem. Your data and model never leaves your firewall

Optimal infra for running

Recommended infra for optimal performance and cost with pre-built specs and right choice of CPUs/GPUs. Use of LoRA

Better resource management

Get overview of underutilization of resources across services and models. Easily adjust resources to ensure better utilization and save costs
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Connect your cluster on TrueFoundry to keep data on your own cloud
Choose from a list of resource configurations to deploy and finetune LLMs
Get reports to review resource utilisation across deployments

Demo watch TrueFoundry LLMOps live in action


Deploy Falcon 40B on any Cloud using TrueFoundry at 40% cheaper cost

Deploy Falcon 40B on any Cloud using TrueFoundry at 40% cheaper cost

In this article, we discuss about deploying Falcon model on your own cloud. The Technology Innovation Institute in Abu Dhabi has developed Falcon, an innovative series of language models. These models, released under the Apache 2.0 license, represent a significant advancement in the field. Notably, Falcon-40B stands out as a truly open model, surpassing numerous closed-source models in its capabilities. This development brings tremendous opportunities for professionals, enthusiasts, and the industry as it paves the way for various exciting applications.

Easy LLMOps to deploy and Finetune Llama-2

Easy LLMOps to deploy and Finetune Llama-2

The ChatGPT moment of the open source world is here - Meta released its latest set of open-source large language models, called Llama 2 - a collection of pre-trained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters.

LLMs in Production - E-Book

LLMs in Production - E-Book

After attending the LLMs in Production conference organized by the MLOps Community in San Francisco, we realized the immense value in compiling the knowledge and insights shared by esteemed speakers into a comprehensive eBook. That's why we partnered with the vibrant MLOps Community to curate this valuable resource, designed to equip you with the knowledge and insights needed to navigate the complex landscape of LLMs in production.

E book
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LLMOps CoE: The next frontier in the MLOps Landscape

LLMOps CoE: The next frontier in the MLOps Landscape

In this blog, we will explore the importance of LLMOps and how it tackles the challenges associated with LLMs, such as iteration, prompt management and testing complexities. We also go a step further and suggest how you can get started on your LLMOps journey.

The $360K question about Large Language Models Economics

The $360K question about Large Language Models Economics

The purpose of this article is to educate the reader about how Large Language Models (LLM) pricing works. This is motivated by our conversations with multiple companies using LLMs commercially. We realized in these conversations that LLM economics is often misunderstood, leaving a huge scope for optimization.


TrueFoundry integrates with different LLM Tools, Clouds, Version Control, Databases, Model Training, Serving and Runtime Tools

Testimonials TrueFoundry makes your ML team 10x faster

"We have been facing issues deploying and fine-tuning models on our own infra, but the way TrueFoundry is built and the roadmap to come,  it will definitely make LLMOps easier for other companies too."
Testimonial author: Liming
CTO at NomadHealth
"TrueFoundry is helping solve the Q&A answering problem on our own dataset, which for us is a big challenge given the model and data ownership was critical to us. We associated with them due to a superfast onboarding process and their willingness to work closely with the team."
Testimonial author: Sridhar
Head of ML at Calyx
"Using the TrueFoundry platform, we are able to train and deploy a 7Bn LLM for Q&A that is finetuned with our own data within 2 weeks and achieve leading results"
Testimonial author: Anonymous Global ML Head at a Fortune 500 company
Global ML Head
Fortune 100 Company
"Today, the Platform team doesn't trust me to deploy LLMs because they think I will screw up or leak data or incur huge costs, especially given the size of models. The Workspace concept with limits and isolation solves the problem and will help build more trust with the Platform team"
Testimonial author: Michael
Senior Data Scientist
"Getting started with Documentation to final Production of my model was only 45 minutes for me with TrueFoundry. Deploying models using a simple code block with all inference functions seems very handy and easy to use."
Testimonial author: Anonymous Kaggle Grandmaster
Kaggle GrandMaster
"It's great to see the tech architecture built in such a platform agnostic way. This is one of the most thoughtful architectures I have seen for any ML System being built and that gives me the confidence to deploy it in my infrastructure"
Testimonial author: Majd
DevOps Manager at BeyondLimits

A LLMOps stack that just works on your environment

TrueFoundry LLMOps Solution