Description
Kibbu is designed to help organizations cut down on AI cloud inference expenses by leveraging existing hardware. By running AI workloads on idle laptops, workstations, and servers, companies can significantly reduce their reliance on cloud services. This approach not only saves costs but also ensures that cloud resources remain available for tasks that require them. Kibbu's setup process is straightforward, allowing users to sign up, add nodes, obtain an API key, and configure preferences in just a few minutes.
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The platform supports various AI models and provides memory and speed estimates to help users determine the best fit for their hardware. Kibbu emphasizes data privacy, offering zero data retention and allowing users to decide which workloads can access external providers. For stricter data requirements, Kibbu can be deployed within a company's infrastructure.
Kibbu is suitable for recurring, latency-tolerant jobs such as document processing, enrichment, and embedding batches. It supports Macs, Windows, and Linux systems, with or without a GPU, and can run on employee laptops when they are idle and plugged in. The platform also offers solutions for edge and datacenter environments, making it scalable for enterprise use.
By using Kibbu, companies can evaluate the cost and performance of running AI workloads locally and decide on further expansion based on these metrics. This approach ensures that businesses can optimize their AI operations without compromising on quality or data security.
- CategoryMLOps & Model Deployment
- Pricing ModelContact for pricing
- DeploymentOn-premise, Cloud
- PlatformsMac, Windows, Linux
kibbu's Core Features
Local AI workload execution
Cloud inference cost reduction
Zero data retention
On-premise deployment option
Supports multiple AI models
Memory and speed estimation
Integration with existing hardware
Scalable for edge and datacenter
How to use kibbu?
Sign up: Use your work email
Add node: Through the admin console
Get API key: Change your current API key
Configure: Set preferences for models and data display
kibbu's Use Cases
- Document Processing
- Embedding Batches
- Data Enrichment
- Background Agent Steps
- Synthetic Data Generation
