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.

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 ROCm, 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.

Cloud Deployments
Client Deployments
Edge Deployments
Operating Systems
Third-Party APIs.
Multiple Modalities
Text
Image
Audio
Embedding

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.

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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

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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

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Easy to Deploy

  • One click deployment & production.

  • Hardware agnostic deployment

  • Operating System agnostic

  • Hybrid Inference

LLaMa Index

LangChain

Guidance

Haystack

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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.

Application Modules
Sales Agent and Coding Agent
Technology Use Cases
Technology Use Cases such as RAG, Summarisation, and STT, showcasing how our SDKs empower a broad spectrum of AI applications.
Client SDKs
HTTP, GRPC, Streaming, and integrations with tools like Haystack and LangChain.
Security and Compliance
LLM Security, Observability, and advanced Prompt Management systems
Performance Optimization
Prompt Management, Templating, Routing, Caching, and Compression strategies, along with Model Optimizations.
System Architecture
Serving System & Management infrastructure, which supports scalability and efficient management of AI operations. Built to handle large-scale deployments and complex computational tasks.
Development Frameworks & Bud Models
Pytorch, TensorFlow, and Deepspeed, enhanced by Bud Models and Model Optimizations.
Bud Runtime
Technology Use Cases such as RAG, Summarisation, and STT, showcasing how our SDKs empower a broad spectrum of AI applications.
OS Layer
Windown, Linux, Mac, Web
Hardware Layer
Intel Xeon processors and Nvidia GPUs to HPUs and Arm-based devices.