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ThousandEyes: Technology, History, Companies & Art
ThousandEyes, Inc. is a network intelligence company headquartered in San Francisco with offices in Dublin, London, Mexico City, Kraków, Lisbon, Sydney and Austin, Texas. The company produces software that analyzes the performance of local and wide area networks, servers and applications. On May 29, 2020, Cisco announced it would be acquiring ThousandEyes.
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ThousandEyes topic overview
The analysis highlights Technology, History, Companies and Art as prominent areas in the source structure around ThousandEyes.
Related topics
34
Source areas
5
Connected nodes
39
Extracted relationships
75
Concept neighborhoods
18
Bridge connections
39
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Business · 9 topics
Overview · 9 topics
Technology · 8 topics
History · 4 topics
Recognition · 4 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Founded
2010; 16 years ago (2010) Mountain View, California
Industry
Software · SaaS
Headquarters
San Francisco, California
Key people
Mohit Lad (CEO and co-founder) Ricardo Oliveira (CTO and co-founder)
Type
Private
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How ThousandEyes connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around ThousandEyes shows recurring relationship patterns in the source. For example, ThousandEyes → Additionally, Autonomous System, Cyclops, DNS, Google Ventures, Greek, GV, In, In February, June, Lad, Mohit Lad, National Science Foundation, Ricardo Oliveira, Salesforce, Salesforce Ventures, Sequoia Capital, Series, Sutter Hill Ventures, Tenaya Capital Another extracted example is ThousandEyes → Application Performance Monitoring, Battery Ventures, Bay Area Best Places, Best Workplaces, Credit Suisse AG's, Disruptive Technology Recognition, DTR, Forbes, Fortune, Gartner Cool Vendors, Glassdoor, Highest-Rated Private Cloud-Computing Companies, Hottest Startups, In November, IT Infrastructure, IT Operations Analytics, Program, San Francisco Business Times, Texas, Work. Use these groups to spot repeated connection types before inspecting the individual relationships.
ThousandEyes
Top relations
related to history· 23
ThousandEyes → Additionally, Autonomous System, Cyclops, DNS, Google Ventures, Greek, GV, In, In February, June, Lad, Mohit Lad, National Science Foundation, Ricardo Oliveira, Salesforce, Salesforce Ventures, Sequoia Capital, Series, Sutter Hill Ventures, Tenaya Capital
related to Recognition· 21
ThousandEyes → Application Performance Monitoring, Battery Ventures, Bay Area Best Places, Best Workplaces, Credit Suisse AG's, Disruptive Technology Recognition, DTR, Forbes, Fortune, Gartner Cool Vendors, Glassdoor, Highest-Rated Private Cloud-Computing Companies, Hottest Startups, In November, IT Infrastructure, IT Operations Analytics, Program, San Francisco Business Times, Texas, Work
related to Business· 16
ThousandEyes → Billion, Cisco, DocuSign, EBay, Equinix, GV, In August, In May, Its, Salesforce, Sequoia Capital, ServiceNow, Sutter Hill Ventures, Tenaya Capital, Twitter, US
related to Technology· 8
ThousandEyes → BGP, DNS, HTTP, HTTPS, SaaS, SNMP, The, VoIP
Industry· 2
ThousandEyes → SaaS, Software
Founded· 1
ThousandEyes → 2010; 16 years ago (2010) Mountain View, California
Headquarters· 1
ThousandEyes → San Francisco, California
Key people· 1
ThousandEyes → Mohit Lad (CEO and co-founder) Ricardo Oliveira (CTO and co-founder)
Type· 1
ThousandEyes → Private
Website· 1
ThousandEyes → www.thousandeyes.com
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 75 structured relationships around ThousandEyes. Examples in this analysis include ThousandEyes → Founded → 2010; 16 years ago (2010) Mountain View, California and ThousandEyes → Headquarters → San Francisco, California. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
ThousandEyes
Founded
2010; 16 years ago (2010) Mountain View, California
1.00
infobox
ThousandEyes
Headquarters
San Francisco, California
1.00
infobox
ThousandEyes
Industry
Software
1.00
infobox
ThousandEyes
Industry
SaaS
1.00
infobox
ThousandEyes
Key people
Mohit Lad (CEO and co-founder) Ricardo Oliveira (CTO and co-founder)
1.00
infobox
ThousandEyes
Type
Private
1.00
infobox
ThousandEyes
Website
www.thousandeyes.com
1.00
infobox
ThousandEyes
related to Business
Sequoia Capital
0.60
section
ThousandEyes
related to Business
Sutter Hill Ventures
0.60
section
ThousandEyes
related to Business
Salesforce
0.60
section
ThousandEyes
related to Business
Tenaya Capital
0.60
section
ThousandEyes
related to Business
GV
0.60
section
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around ThousandEyes bring nearby vocabulary together. In this analysis, examples include Recognized, Companies and Work. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
san francisco
Francisco
San
Texas
Area
Business
Inc
Mohit
Private
Saas
Software
Thousandeyes
Lad
sequoia capital
Sequoia
Hill
Salesforce
Sutter
Round
Investors
Joined
Tenaya
Series
Ventures
Gv
Led
tenaya capital
Sequoia
Round
Hill
Investors
Joined
Salesforce
Sutter
Tenaya
Series
Ventures
Gv
Led
sutter hill ventures
Salesforce
Sutter
Sequoia
Ventures
Investors
Joined
Tenaya
Round
Gv
Led
Series
Work
gv
Investors
Tenaya
Series
Round
Ventures
Hill
Joined
Led
Salesforce
Sutter
Sequoia
Thousandeyes
network intelligence
Product
Monitoring
Company
Saas
Texas
Francisco
Performance
San
Thousandeyes
network tomography
Product
Monitoring
Company
Saas
Texas
Francisco
Performance
San
Thousandeyes
business
Inc
Recognition
Technology
Texas
Francisco
Recognized
San
Work
Thousandeyes
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For ThousandEyes, one of the stronger structural bridges in this analysis connects ThousandEyes with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
ThousandEyes
Nodes40
Edges39
Triples75
Avg. degree1.95
Density0.05
Components1
Source & methodology
TTTA analyzes the structure around ThousandEyes to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Technology, History, Companies & Art, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
