Name: Peoplegeist
Author: Peoplegeist

Call Center Workforce Optimization

Help Desk

Web and Video Conferencing

Customer Support

Chatbot

Functional Testing

Kubernetes Monitoring

No-Code Development

Development

Admissions and Enrollment

Classroom Management

Education

Business Intelligence (BI)

Collaboration

Facility Management

Statistical Analysis

Workspace Planning

Enterprise

Accounting

Accounts Payable

Financial Planning and Analysis (FP&A)

Hedge Fund

Finance and Accounting

Applicant Tracking

Corporate Learning Management

HR Management

Payroll

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

3D Printing

Block Storage

Cloud Data Warehouse

Cloud Storage

Configuration Management Databases

Deception Technology

Encryption Key Management

Fraud Detection

Integration Platform as a Service (iPaaS)

IoT Device Management

Load Balancing

Network Performance Monitoring

Operating Systems

SOA Governance

SaaS Backup

Server Virtualization

Service Desk Outsourcing

Vector Databases

WiFi Hotspot

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

Content Management

Customer Success

Digital Content Creation

Email Marketing

Market Intelligence

Marketing Automation

Referral Marketing

Social Media Management

Survey & Forms Building

Usability Testing

Web Analytics

Marketing

Project Management

Professional Services

Customer Onboarding

Customer Relationship Management (CRM)

Field Sales Software

Sales Performance Management

Sales

Agriculture

Construction Takeoff and Estimating

Dealer Management

Direct Secure Messaging

Equipment Rental

Fleet Management

Insurance Suites

PCB Design

Rental Property Management

Restaurant Management

Vertical-Specific

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The Peoplegeist Text-AI for Manufacturing is a software solution designed to analyze maintenance documentation in manufacturing industries. According to the vendor, it aims to help reduce downtime, improve quality, and facilitate knowledge capture and sharing for small to large manufacturing companies. This solution is utilized by maintenance managers, technicians, production managers, quality assurance professionals, operations managers, and manufacturing engineers in industries such as automotive, food and beverage, pharmaceuticals, chemicals, and electronics.

## Key Features

**Reduce repeating errors**: According to the vendor, this feature allows users to identify recurring issues in maintenance comments and automatically generate pareto charts for analysis, eliminating the need for manual categorization or classification-tree.

**Share knowledge**: The vendor claims that this feature enables the transformation of maintenance documentation into troubleshooting guides by identifying documented maintenance actions for specific problems, facilitating easy knowledge sharing within the team.

**Capture & share knowledge**: According to the vendor, this feature accelerates troubleshooting time by converting maintenance comments into guides. It allows users to access troubleshooting knowledge from colleagues without having to read through all reports, with no additional work required for sharing experience.

**Use TextAI and NLP to analyze maintenance comments**: The vendor states that this feature leverages NLP AI to comprehend manufacturing problems and solutions in maintenance logs, eliminating the need for manual categorization or extensive log reading. The AI creates breakdown analysis charts for downtime analysis, maintenance prediction, and identification of training gaps. Users can query the AI for potential solutions based on past experiences.

**Multilingual support**: According to the vendor, this feature works across 50 languages, allowing employees to use it in their native language. Cross-lingual analysis helps identify problem patterns across different sites and facilitates knowledge sharing among teams working in various languages.

**Unlock knowledge in maintenance comments**: The vendor claims that this feature automates the reading and summarizing of shift log, maintenance, and MES log comments. It generates pareto charts of production issues, provides hints for root-cause analysis, and suggests resolution steps to expedite troubleshooting.

**Save downtime**: According to the vendor, this feature aims to decrease downtime by reducing mean time to repair (MTTR) and minimizing incidents (MTBF). Implementation is fast, with no need for an IT project. The vendor also states that discussions about events not being categorized correctly can be avoided.

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