CompactifAI

CompactifAI

Multiverse Computing
+
+

Related Products

  • Dragonfly
    16 Ratings
    Visit Website
  • RaimaDB
    9 Ratings
    Visit Website
  • RunPod
    205 Ratings
    Visit Website
  • CLEAR
    1 Rating
    Visit Website
  • kama DEI
    8 Ratings
    Visit Website
  • Google AI Studio
    11 Ratings
    Visit Website
  • Zengo Wallet
    413 Ratings
    Visit Website
  • LM-Kit.NET
    23 Ratings
    Visit Website
  • TinyPNG
    49 Ratings
    Visit Website
  • Teradata VantageCloud
    992 Ratings
    Visit Website

About

CompactifAI from Multiverse Computing is an AI model compression platform designed to make advanced AI systems like large language models (LLMs) faster, cheaper, more energy efficient, and portable by drastically reducing model size without significantly sacrificing performance. Using advanced quantum-inspired techniques such as tensor networks to “compress” foundational AI models, CompactifAI cuts memory and storage requirements so models can run with lower computational overhead and be deployed anywhere, from cloud and on-premises to edge and mobile devices, via a managed API or private deployment. It accelerates inference, lowers energy and hardware costs, supports privacy-preserving local execution, and enables specialized, efficient AI models tailored to specific tasks, helping teams overcome hardware limits and sustainability challenges associated with traditional AI deployments.

About

Tensormesh is a caching layer built specifically for large-language-model inference workloads that enables organizations to reuse intermediate computations, drastically reduce GPU usage, and accelerate time-to-first-token and latency. It works by capturing and reusing key-value cache states that are normally thrown away after each inference, thereby cutting redundant compute and delivering “up to 10x faster inference” while substantially lowering GPU load. It supports deployments in public cloud or on-premises, with full observability and enterprise-grade control, SDKs/APIs, and dashboards for integration into existing inference pipelines, and compatibility with inference engines such as vLLM out of the box. Tensormesh emphasizes performance at scale, including sub-millisecond repeated queries, while optimizing every layer of inference from caching through computation.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI developers, machine learning engineers, and organizations that need to deploy large language models (LLMs) and other AI systems more efficiently, cost-effectively, and sustainably

Audience

Enterprises and AI infrastructure teams wanting a tool to reduce latency and cost while maintaining full control over deployment and data

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Multiverse Computing
Founded: 2019
Basque Country
multiversecomputing.com/compactifai

Company Information

Tensormesh
Founded: 2025
United States
www.tensormesh.ai/

Alternatives

Alternatives

Categories

Categories

Integrations

Amazon Web Services (AWS)
Llama
Mistral AI

Integrations

Amazon Web Services (AWS)
Llama
Mistral AI
Claim CompactifAI and update features and information
Claim CompactifAI and update features and information
Claim Tensormesh and update features and information
Claim Tensormesh and update features and information