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Epicor Connected Process ControlEpicor Connected Process Control offers an intuitive software solution designed to create and manage digital work instructions while maintaining strict process control, effectively minimizing the chances of errors in operations. By integrating IoT devices, it captures comprehensive time studies and detailed process data, including images, at the task level, providing unprecedented real-time visibility and quality oversight. The eFlex system is versatile enough to accommodate countless product variations and thousands of components, catering to both component-based and model-based manufacturers alike. Furthermore, work instructions seamlessly connect to the Bill of Materials, guaranteeing that products are assembled correctly every time, even when modifications occur during production. This advanced system intelligently adapts to variations in models and components, ensuring that only the relevant work instructions for the current build at the station are presented, enhancing efficiency and accuracy throughout the manufacturing process. In this way, Epicor empowers manufacturers to maintain high standards of quality control while adapting to the dynamic nature of production demands.
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What is Sawmills?
Sawmills emerges as the leading smart telemetry management platform, enabling organizations to efficiently oversee their logs, metrics, and traces prior to incurring costs associated with traditional observability solutions. Its groundbreaking application of AI for noise detection distinguishes it from competitors, allowing Sawmills to effectively reduce waste, improve data integrity, and implement governance controls.
In contrast to traditional filtering techniques and manually developed rules that often struggle with scalability, Sawmills utilizes AI to assess telemetry data in real-time, uncovering noise patterns, duplicate events, low-value attributes, excessive cardinality, PII/policy violations, and faulty schemas. For each identified issue, Sawmills proposes a relevant course of action, including options like filtering, redacting, aggregating, downsampling, normalizing, enriching, and it also possesses the capability to auto-remediate with the requisite approvals, service level agreements, and rollback procedures. This forward-thinking strategy not only pushes oversight upstream but also markedly reduces waste, elevates the quality of data collected, and automates governance, ultimately resulting in more streamlined data management practices throughout various enterprises. Furthermore, by embracing this innovative approach, businesses can unlock new levels of operational efficiency and data-driven decision-making.
What is Dash0?
Engineering teams that adopt OpenTelemetry often hit the same wall: instrumentation is standardized, but the backend receiving it is not. Dash0 was built to close that gap.
Every signal, whether a trace, a log record, a metric, or the resource emitting it, is stored against OpenTelemetry semantic conventions and correlated automatically. A request that ran long can be examined next to the log lines it produced and the pod it ran on, with no manual joins and no hopping between products.
Ingestion happens through a standard OTLP endpoint. Nothing proprietary gets deployed, and existing instrumentation keeps working untouched. Because the wire format is open, data can be redirected to a different destination later without changes to application code.
Prometheus users are treated as first-class. Full PromQL is supported, existing recording and alerting rules carry over, and Grafana dashboard definitions import directly. Cluster-level collection is handled by a dedicated Kubernetes operator covering workloads, nodes, and control plane components.
Visualization runs on Perses, with dashboard, check, and alert definitions expressed declaratively and kept under version control. Investigations start broad and get narrow: heatmaps expose the shape of a latency distribution, then filters on high-cardinality attributes isolate the affected requests.
Machine learning is applied to telemetry during processing rather than surfaced as a chatbot. Log AI assigns severity to records that arrive without it, discovers recurring patterns, and clusters similar entries, turning noisy third-party output into something queryable. For failing requests, the SIFT methodology structures the path from symptom to root cause.
Consumption stays transparent throughout. Teams can identify which services, attributes, and log volumes are responsible for their bill and reduce them at the source, before the invoice arrives.
Integrations Supported
Slack
All Quiet
Altinity
Atlantis
BigHand AlertManager
Bindplane
Cline
Confluent
GitHub
Google Chat
Integrations Supported
Slack
All Quiet
Altinity
Atlantis
BigHand AlertManager
Bindplane
Cline
Confluent
GitHub
Google Chat
API Availability
Has API
API Availability
Has API
Pricing Information
$0
Pricing is dependent on ingestion. Average customers are ROI positive within months.
Free Version
Free Trial Offered?
Pricing Information
$0.00 per month
Completely transparent usage based pricing
Free Version
Free Trial Offered?
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Sawmills.ai
Date Founded
2024
Company Location
United States
Company Website
sawmills.ai
Company Facts
Organization Name
Dash0
Date Founded
2023
Company Location
United States
Company Website
www.dash0.com
Categories and Features
Categories and Features
Application Performance Monitoring (APM)
Baseline Manager
Diagnostic Tools
Full Transaction Diagnostics
Performance Control
Resource Management
Root-Cause Diagnosis
Server Performance
Trace Individual Transactions
Database Monitoring
Anomaly Detection
Autodiscovery
Capacity Planning
Dashboard
Dependency Tracking
Historical Trend Analysis
Multitenancy
Notifications / Alerts
Performance Monitoring
Permissions / Access Controls
Predictive Analytics
Prioritization
Query Analysis
Resource Optimization
Troubleshooting
IT Alerting
Alert Noise Reduction
Alert Routing
Dynamic Notifications
Enriched Incident Context
Escalation Policies
Incident History Audit
Multi-User Alerting
Multiple Alert Types
On-Call Management
Rich HTML Email Notifications
IT Infrastructure Monitoring
Alerts / Notifications
Application Monitoring
Bandwidth Monitoring
Capacity Planning
Configuration Change Management
Data Movement Monitoring
Health Monitoring
Multi-Platform Support
Performance Monitoring
Point-in-Time Visibility
Reporting / Analytics
Virtual Machine Monitoring
Log Management
Archiving
Audit Trails
Compliance Reporting
Consolidation
Data Visualization
Event Logs
Network Logs
Remediation
Syslogs
Thresholds
Web Logs
Website Monitoring
Availability Testing
Event Logs
Event-Based Notifications
FTP Monitoring
Mail Server Monitoring
Maintenance Scheduling
Performance Metrics
Real Time Monitoring
Transaction Monitoring
Uptime Reporting