Official source monitor
Company news, backed by original sources.
Follow official updates, independent coverage and dated attention signals. Full originals open after free sign-up and an external-link warning.
Observation window
90 days
Published by official sources. Dates are shown in UTC.
Updated Oct 9, 2026, 07:31 PM UTC
Official updates
12
Published in this view
Companies publishing
1
Distinct companies in this window
Days with activity
10
Days with at least one update
Independent stories
0
0 verified US tech publishers
Cross-company mentions
0
Independent stories associated with another company
Open prediction markets
0
Separate from hiring rankings
The infographic
Augury official publishing pulse
Publication cadence
When the updates appeared
Daily publication dates in UTC. Bars count posts; the line counts distinct companies.
| Date UTC | Updates | Companies |
|---|---|---|
| 2026-07-12 | 0 | 0 |
| 2026-07-13 | 0 | 0 |
| 2026-07-14 | 0 | 0 |
| 2026-07-15 | 0 | 0 |
| 2026-07-16 | 0 | 0 |
| 2026-07-17 | 0 | 0 |
| 2026-07-18 | 0 | 0 |
| 2026-07-19 | 0 | 0 |
| 2026-07-20 | 0 | 0 |
| 2026-07-21 | 0 | 0 |
| 2026-07-22 | 0 | 0 |
| 2026-07-23 | 0 | 0 |
| 2026-07-24 | 0 | 0 |
| 2026-07-25 | 0 | 0 |
| 2026-07-26 | 0 | 0 |
| 2026-07-27 | 0 | 0 |
| 2026-07-28 | 0 | 0 |
| 2026-07-29 | 0 | 0 |
| 2026-07-30 | 0 | 0 |
| 2026-07-31 | 0 | 0 |
| 2026-08-01 | 0 | 0 |
| 2026-08-02 | 0 | 0 |
| 2026-08-03 | 0 | 0 |
| 2026-08-04 | 0 | 0 |
| 2026-08-05 | 0 | 0 |
| 2026-08-06 | 0 | 0 |
| 2026-08-07 | 0 | 0 |
| 2026-08-08 | 0 | 0 |
| 2026-08-09 | 0 | 0 |
| 2026-08-10 | 0 | 0 |
| 2026-08-11 | 0 | 0 |
| 2026-08-12 | 0 | 0 |
| 2026-08-13 | 0 | 0 |
| 2026-08-14 | 0 | 0 |
| 2026-08-15 | 0 | 0 |
| 2026-08-16 | 0 | 0 |
| 2026-08-17 | 0 | 0 |
| 2026-08-18 | 0 | 0 |
| 2026-08-19 | 0 | 0 |
| 2026-08-20 | 0 | 0 |
| 2026-08-21 | 0 | 0 |
| 2026-08-22 | 0 | 0 |
| 2026-08-23 | 0 | 0 |
| 2026-08-24 | 0 | 0 |
| 2026-08-25 | 0 | 0 |
| 2026-08-26 | 0 | 0 |
| 2026-08-27 | 0 | 0 |
| 2026-08-28 | 0 | 0 |
| 2026-08-29 | 0 | 0 |
| 2026-08-30 | 0 | 0 |
| 2026-08-31 | 0 | 0 |
| 2026-09-01 | 0 | 0 |
| 2026-09-02 | 0 | 0 |
| 2026-09-03 | 0 | 0 |
| 2026-09-04 | 0 | 0 |
| 2026-09-05 | 0 | 0 |
| 2026-09-06 | 0 | 0 |
| 2026-09-07 | 0 | 0 |
| 2026-09-08 | 0 | 0 |
| 2026-09-09 | 1 | 1 |
| 2026-09-10 | 1 | 1 |
| 2026-09-11 | 0 | 0 |
| 2026-09-12 | 0 | 0 |
| 2026-09-13 | 0 | 0 |
| 2026-09-14 | 0 | 0 |
| 2026-09-15 | 1 | 1 |
| 2026-09-16 | 0 | 0 |
| 2026-09-17 | 1 | 1 |
| 2026-09-18 | 0 | 0 |
| 2026-09-19 | 0 | 0 |
| 2026-09-20 | 0 | 0 |
| 2026-09-21 | 0 | 0 |
| 2026-09-22 | 0 | 0 |
| 2026-09-23 | 0 | 0 |
| 2026-09-24 | 0 | 0 |
| 2026-09-25 | 0 | 0 |
| 2026-09-26 | 0 | 0 |
| 2026-09-27 | 0 | 0 |
| 2026-09-28 | 2 | 1 |
| 2026-09-29 | 1 | 1 |
| 2026-09-30 | 1 | 1 |
| 2026-10-01 | 0 | 0 |
| 2026-10-02 | 2 | 1 |
| 2026-10-03 | 0 | 0 |
| 2026-10-04 | 0 | 0 |
| 2026-10-05 | 0 | 0 |
| 2026-10-06 | 1 | 1 |
| 2026-10-07 | 0 | 0 |
| 2026-10-08 | 1 | 1 |
| 2026-10-09 | 0 | 0 |
Source breadth
Who published most
Official updates from the most active companies in this view.
| Company | Updates |
|---|---|
| Augury | 12 |
Coverage map
Official posts and independent mentions
One story may mention several companies. Bars follow its publication date and count it once in this view.
| Date UTC | Official posts | Independent stories |
|---|---|---|
| 2026-07-12 | 0 | 0 |
| 2026-07-13 | 0 | 0 |
| 2026-07-14 | 0 | 0 |
| 2026-07-15 | 0 | 0 |
| 2026-07-16 | 0 | 0 |
| 2026-07-17 | 0 | 0 |
| 2026-07-18 | 0 | 0 |
| 2026-07-19 | 0 | 0 |
| 2026-07-20 | 0 | 0 |
| 2026-07-21 | 0 | 0 |
| 2026-07-22 | 0 | 0 |
| 2026-07-23 | 0 | 0 |
| 2026-07-24 | 0 | 0 |
| 2026-07-25 | 0 | 0 |
| 2026-07-26 | 0 | 0 |
| 2026-07-27 | 0 | 0 |
| 2026-07-28 | 0 | 0 |
| 2026-07-29 | 0 | 0 |
| 2026-07-30 | 0 | 0 |
| 2026-07-31 | 0 | 0 |
| 2026-08-01 | 0 | 0 |
| 2026-08-02 | 0 | 0 |
| 2026-08-03 | 0 | 0 |
| 2026-08-04 | 0 | 0 |
| 2026-08-05 | 0 | 0 |
| 2026-08-06 | 0 | 0 |
| 2026-08-07 | 0 | 0 |
| 2026-08-08 | 0 | 0 |
| 2026-08-09 | 0 | 0 |
| 2026-08-10 | 0 | 0 |
| 2026-08-11 | 0 | 0 |
| 2026-08-12 | 0 | 0 |
| 2026-08-13 | 0 | 0 |
| 2026-08-14 | 0 | 0 |
| 2026-08-15 | 0 | 0 |
| 2026-08-16 | 0 | 0 |
| 2026-08-17 | 0 | 0 |
| 2026-08-18 | 0 | 0 |
| 2026-08-19 | 0 | 0 |
| 2026-08-20 | 0 | 0 |
| 2026-08-21 | 0 | 0 |
| 2026-08-22 | 0 | 0 |
| 2026-08-23 | 0 | 0 |
| 2026-08-24 | 0 | 0 |
| 2026-08-25 | 0 | 0 |
| 2026-08-26 | 0 | 0 |
| 2026-08-27 | 0 | 0 |
| 2026-08-28 | 0 | 0 |
| 2026-08-29 | 0 | 0 |
| 2026-08-30 | 0 | 0 |
| 2026-08-31 | 0 | 0 |
| 2026-09-01 | 0 | 0 |
| 2026-09-02 | 0 | 0 |
| 2026-09-03 | 0 | 0 |
| 2026-09-04 | 0 | 0 |
| 2026-09-05 | 0 | 0 |
| 2026-09-06 | 0 | 0 |
| 2026-09-07 | 0 | 0 |
| 2026-09-08 | 0 | 0 |
| 2026-09-09 | 1 | 0 |
| 2026-09-10 | 1 | 0 |
| 2026-09-11 | 0 | 0 |
| 2026-09-12 | 0 | 0 |
| 2026-09-13 | 0 | 0 |
| 2026-09-14 | 0 | 0 |
| 2026-09-15 | 1 | 0 |
| 2026-09-16 | 0 | 0 |
| 2026-09-17 | 1 | 0 |
| 2026-09-18 | 0 | 0 |
| 2026-09-19 | 0 | 0 |
| 2026-09-20 | 0 | 0 |
| 2026-09-21 | 0 | 0 |
| 2026-09-22 | 0 | 0 |
| 2026-09-23 | 0 | 0 |
| 2026-09-24 | 0 | 0 |
| 2026-09-25 | 0 | 0 |
| 2026-09-26 | 0 | 0 |
| 2026-09-27 | 0 | 0 |
| 2026-09-28 | 2 | 0 |
| 2026-09-29 | 1 | 0 |
| 2026-09-30 | 1 | 0 |
| 2026-10-01 | 0 | 0 |
| 2026-10-02 | 2 | 0 |
| 2026-10-03 | 0 | 0 |
| 2026-10-04 | 0 | 0 |
| 2026-10-05 | 0 | 0 |
| 2026-10-06 | 1 | 0 |
| 2026-10-07 | 0 | 0 |
| 2026-10-08 | 1 | 0 |
| 2026-10-09 | 0 | 0 |
Official charts count the selected company’s own feed; independent mentions include stories from other publishers. Charts cover only ingested sources, not all market news. Stock prices and prediction markets provide context; neither proves a hiring change nor affects the hiring ranking.
Seven-day attention radar
Search and prediction signals
Google Trends shows a traffic bucket for a trending search cluster, not searches for this employer alone. Polymarket markets reflect their own question and trading activity. Neither is a hiring indicator.
No verified company matches for this signal filter yet. The monitor will keep checking.
Data source: Google Trends and Polymarket. Only exact company-name matches are shown; ambiguous names are excluded.
Chronological feed
Latest about Augury
12 stories · page 1 of 1
augury.com
Root Cause Analysis in Manufacturing: A Guide
Key highlights: What is root cause analysis in manufacturing? Root cause analysis in manufacturing is a structured investigation that traces an equipment failure, quality defect, or process upset to its underlying cause. Then the team puts a fix in place to keep the failure from recurring. The symptom is the evidence: a failed bearing, an... The post Root Ca
augury.com
How to Minimize Downtime Costs
Key highlights: What are downtime costs? Downtime costs are the total financial impact of any period when equipment scheduled to run isn’t producing, including lost output, recovery costs, and effects on schedules and customers. Downtime cost type What it includes Where to find the number Lost production Output lost during the stoppage and while the... The p
augury.com
Agentic AI in Manufacturing: Applications and Benefits
AI agents are one of the next big steps for artificial intelligence (AI) in industrial manufacturing. Specialized AI agents can understand your specific process context, reason through complex multistep challenges, and perform independent actions across systems so your teams can move faster (and more accurately) than ever. In this article, you’ll learn how a
augury.com
Asset Condition Monitoring: Analysis and Management
Key highlights: What is asset condition monitoring and how does it work in manufacturing? Asset condition monitoring is the ongoing collection and analysis of equipment health data. It helps your team find developing faults and act before they become failures. ISO 17359 is the international guideline for setting up condition monitoring programs. It lists par
augury.com
Knowledge Doesn’t Have to Retire
A customer’s senior process engineer, let’s call him “Bill,” is 66 and ready to retire. He knows the plant better than anyone alive, and without him, nobody else could tell you why one fix works and another doesn’t. “I wish we could capture everything in his head,” the customer told me. There was real truth... The po
augury.com
Predictive maintenance software: A buyer’s guide
Key highlights: What is predictive maintenance software for manufacturing? Predictive maintenance software for manufacturing continuously monitors equipment condition and flags developing faults before they cause a breakdown. Sensors mounted on critical assets stream vibration, temperature, and other condition data into AI models. These models are trained to
augury.com
People First, Everywhere: A Conversation With Dana Teplitsky
You’re new to manufacturing. What made you say yes to Augury? A few things came together. First, I wanted to join a global company that was expanding its footprint, because that’s work I’ve done before and love doing. Augury’s roots in Israel were part of the draw, too. I admire the pace, intellect, and resilience... The post People First,
augury.com
Machine Learning in Manufacturing: Use Cases, Applications, and Adopting Agentic AI
It’s a perpetual goal in manufacturing: produce more, higher-quality products at minimum cost.  Machine learning (ML) is the technology that makes this goal achievable at scale. It’s also what helps manufacturers extend the life of their assets, improve yield while reducing waste, and lower maintenance costs.  This article covers how ML works in ma
augury.com
The Benefits of Predictive Maintenance: Uptime, ROI, and Data-Backed Results
With the right predictive maintenance solution, manufacturing teams can transform maintenance from a reactive and panicky “fire-fighting” workflow into a strategy that directly impacts operational efficiency and bottom-line performance.  Predictive maintenance empowers teams to make the right decisions based on real-time equipment conditions, making it
augury.com
Overall Line Efficiency (OLE): Formula, Calculation, and How It Compares to OEE
Overall Equipment Effectiveness (OEE) is a widely accepted and utilized manufacturing evaluation method. While still an essential metric for manufacturers, Overall Equipment Effectiveness (OEE) is limited in its ability to give your manufacturing teams the “big picture.”  To respond to this need for a better-suited metric, a technique known as Overall L
augury.com
“Knowledge is the new gold”: Ronen Salomon on the OKF Industrial Profile
You lead hardware and ecosystem work at Augury. How did you end up building a knowledge format? I’ve been at Augury for seven years, building sensors and systems. In that time, we built sensors, gateways, the lab, test guidelines, and the team around all of it. There was no cookbook for any of that. We... The post “Knowledge is the new gold”
augury.com
Using Manufacturing AI Agents for Real-Time Process Optimization
Plant floors are more tech-enabled than ever before. The problem is that highly skilled production and process Subject Matter Experts (SMEs) are still stuck being the “glue” between the different data systems running within your operations. Manually combining data from your historian, MES, ERP, and CMMS systems is time-consuming, ineffective, and a waste of
Follow the story to its source.
Explore the charts and previews openly. A free account opens full originals on their verified publisher sites, after an external-link warning.
- 01Explore
News and context stay open
- 02Join for free
No payment for source links
- 03Open source
Full source article
ApplyDjinn registration and opening the source link are free. The destination site may have its own access rules.