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Description
Locai provides a robust infrastructure and tools designed to facilitate large-scale AI operations off the cloud. All processes occur on your own hardware, whether on-premises or within a private cloud, ensuring that your data remains within your control.
The platform encompasses a comprehensive suite of functionalities. Locai Link serves as the inference runtime, enabling the deployment of large language models, audio transcription, video processing, and image recognition across various hardware types, including workstations, servers, and edge devices. Meanwhile, Locai Control functions as the orchestration layer, allowing users to oversee models, updates, and policies for entire fleets of machines from a single interface, ensuring seamless integration by enabling outputs from one model to feed into another for effective multimodal data fusion. To top it off, Locai Workspace offers teams a private AI environment equipped with chat, document management, and assistants, all supported by models that operate within the organization.
Locai’s architecture is hardware-agnostic and compatible with a variety of models, including GGUF, ONNX, and TFLite. Developed in the UK with a focus on regulated sectors such as financial services, nuclear energy, defense, and critical infrastructure, Locai offers a free starting point for users to explore its capabilities. This adaptability makes Locai an appealing choice for organizations seeking secure AI solutions that fit their specific needs.
Description
NetApp AIPod presents a holistic AI infrastructure solution aimed at simplifying the deployment and oversight of artificial intelligence workloads. By incorporating NVIDIA-validated turnkey solutions like the NVIDIA DGX BasePOD™ alongside NetApp's cloud-integrated all-flash storage, AIPod brings together analytics, training, and inference into one unified and scalable system. This integration allows organizations to efficiently execute AI workflows, encompassing everything from model training to fine-tuning and inference, while also prioritizing data management and security. With a preconfigured infrastructure tailored for AI operations, NetApp AIPod minimizes complexity, speeds up the path to insights, and ensures smooth integration in hybrid cloud settings. Furthermore, its design empowers businesses to leverage AI capabilities more effectively, ultimately enhancing their competitive edge in the market.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
NVIDIA DIGITS
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Locai
Founded
2026
Country
United Kingdom
Website
www.locai.co.uk
Vendor Details
Company Name
NetApp
Founded
1992
Country
United States
Website
www.netapp.com/artificial-intelligence/aipod/
Product Features
Product Features
Artificial Intelligence
Chatbot
No
For Healthcare
No
For Sales
No
For eCommerce
No
Image Recognition
No
Machine Learning
No
Multi-Language
No
Natural Language Processing
No
Predictive Analytics
No
Process/Workflow Automation
No
Rules-Based Automation
No
Virtual Personal Assistant (VPA)
No
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No
