The Universal GenAI Inference Engine

Unlock 55X savings on the Total Cost of Ownership for your GenAI solutions!

Trusted By Global Brands

GenAI Made Practical, Profitable & Scalable!

Bud Runtime is a Generative AI serving and inference optimization software stack that delivers state-of-the-art performance across any hardware and OS. It ensures production-ready deployments on CPUs, HPUs, NPUs, and GPUs.

Save up to 55% on the total cost of ownership of your GenAI solutions.

Unlock 12X better inference performance on client devices

Achieve up to 130% better inference performance in the cloud

Universal inference: Hardware, Model architecture and OS agnostic.

Get GPU-like performance for GenAI solutions with CPUs.

Supports On-prem, Cloud & Edge Deployments

Built-in Cluster Management

Built-in LLM Gaurdrails and model monitoring

Advanced LLM Observability

Active Prompt Analysis, Prompt Optimisations

Supports Model Editing, Model Merging

White House & EU AI Guidelines compliant

Secure: Compliant with CWE and MITRE ATT&CK

GenAI ROI Analysis, Reporting & Analtics

Enterprise support, User management

Delivering State-of-the-Art Performance Across CPUs, GPUs, NPUs, and HPUs.

Throughput Increase

60-200%

Using Bud Runtime on CPUs with accelerators

Speed Increase

12X

Compared to LLaMa CPP on RTX 4790 & CPU

Supports Model Pruning, Layer Removal & Quantisation

Supports matrix multiplication free transformers

Supports 1-bit & 1.58 bit architectures.

Load 40B LLM on an RTX 24GB Model on FP16.

Output token/sec

All experiments with LaMa 2 7B

[Uses a LLaMa-2 7B with FP16 on GPUs & BF16 on CPUs, without using optimisations that require fine tuning or pruning like Medusa, Eagle, speculative decoding]

Easily Integrate with
Your Existing Infrastructure

Unifined APIs

A single, unified set of APIs for building portable GenAI applications that can scale across various hardware architectures, platforms, clouds, clients, edge, and web environments, ensuring consistent and reliable performance in all deployments.

GPU like Performance & Scalability with CPUs

For the first time, Bud Runtime has made CPU inference throughput, latency, and scalability comparable to NVIDIA GPUs. Additionally, Bud Runtime delivers state-of-the-art performance across various hardware types, including HPUs, AMD ArCOM, and AMD/Arm CPUs.

Hybrid Inferencing

Current GPU systems often underutilize CPUs and RAM after model loading. Bud Runtime takes advantage of this unused infrastructure to boost throughput by 60-70%. It enables the scaling of GenAI applications across various hardware and operating systems within the same cluster, allowing for seamless operation on NVIDIA, Intel, and AMD devices simultaneously.

Inference Acceleration
for LLMs on CPUs

Our estimates shows that CPU usage for Inference could reduce the power consumption of LLMs by 48.9% while providing production ready throughput and latency.

Easy to Use

Intuitive Dashboard

Insightful Analytics and Reports

Seamless model management

Post production management

Metrics, prompts, cache, compression management

Hit ratio, robustness management

LLaMa Index

LangChain

Guidance

Haystack

Easy to Develop

Shareable and easy to use interface for model testing & comparison

Analyse decoding methods using a UI

Programming language for LLMs

Chat history & function calling

LLaMa Index

LangChain

Guidance

Haystack

Easy to Deploy

One click deployment & production.

Hardware agnostic deployment

Operating System agnostic

Hybrid Inference

LLaMa Index

LangChain

Guidance

Haystack

Gen AI Production
Ready Stack

Streamline GenAI development with Bud’s serving stack that enables building portable, scalable and reliable applications across diverse platforms and architectures, all through a singular API for peak performance.

Technology Use Cases such as RAG, Summarisation, and STT, showcasing how our SDKs empower a broad spectrum of AI applications.