EXEM

Inverstor Relations

Woodpecker

A Self Service AI Platform
From Data Exploration
to Model Deployment

Woodpecker is a container-based self-service AI platform that empowers enterprise analysts to independently manage their analytics pipelines.

woodpecker

Provide an optimized environment
for AI model development

All-in-one support for model development,
training, and deployment

Provide graph visualization solutions
for intuitive data exploration

Ensure efficient resource management
of AI infrastructure

Features

Woodpecker offers a variety of model development tools, including Jupyter, R studio, VS Code. Enabling anyone to start machine learning projects with ease.

  • Stable AI Infrastructure
    Management
    Support Kubernetes-based
    clustering and container monitoring
  • Convenient AI Model
    Development Setup
    Easily build AI model development
    environments without complex
    infrastructure setups
  • Optimized Analysis Images
    Provide images with sample code
    and essential libraries pre-installed
  • Diverse Development
    Environments
    Support multiple languages
    and IDEs, including Python and R
  • Data Visualization
    Deliver deep insights with tools
    for pattern analysis and outlier detection
  • Model Training Scheduling
    Offer job scheduling, automation
    features for AI model training tasks
  • Automated Model
    Deployment APIs
    Simplifies AI model deployment
    to perform real-time predictions
    and inferences
  • Query Editor
    Access databases directly
    and execute SQL commands seamlessly

Monitoring View

Home
Resource
Schedule Timeline

Home

The Home page of Woodpecker serves as a unified interface for real-time monitoring of project resources (CPU, memory, disk) and instant access to analytical tools. It provides a comprehensive view of model training schedules, a model bookmarking feature, and notification alerts for important updates.

Resource

The Resource monitoring page displays resource utilization for AI model development environments and deployment tasks through intuitive graphs. It supports efficient resource management by providing detailed, time-based insights into actual resource usage and comprehensive *GPU information.

· GPU Details: GPU Memory, GPU Clock, Memory Clock, GPU Utilization, Persistence Mode, Power Usage, Power Limits, Temperature, Fan Speed

Schedule Timeline

The Schedule Timeline offers a clear, intuitive overview of all user schedules. It organizes reservation and recurring schedules in chronological order and includes detailed information about users, servers, and schedule-specific tasks.

Workspace

Project Overview
Model Serving
Query Editor

Project Overview

The Project Overview page simplifies the creation of AI model development environments. Users can monitor the real-time
status of created projects and use the provided analytical tools
for seamless, one-stop processes of data exploration, model development, and training.

Model Serving

The Model Serving page automates API endpoint generation by allowing users to upload models and input basic information.
The generated URL enables instant model invocation and
real-time result utilization.

Query Editor

The Query Editor provides direct access to databases, enabling users to execute SQL commands and visualize data in various chart formats. This functionality simplifies the analysis of
complex data patterns and helps uncover hidden anomalies intuitively.

Architecture

architecture

Elevate Your IT Stability,
with EXEM Solutions.

Inquiry

captcha image

Thank you for your contact
and we will reach out to you soon!