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Twilio: History, Technology & Companies
Twilio Inc. is an American cloud communications company based in San Francisco, California, which provides programmable communication tools for making and receiving phone calls, sending and receiving text messages, and performing other communication functions using its web service APIs. Founded in 2008, the company received multiple rounds of funding…
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Twilio topic overview
The analysis highlights History, Technology and Companies as prominent areas in the source structure around Twilio.
Related topics
48
Source areas
5
Connected nodes
53
Extracted relationships
106
Concept neighborhoods
17
Bridge connections
53
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.
History · 25 topics
Overview · 9 topics
Security incidents · 5 topics
Technology · 5 topics
Acquisitions · 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
2008; 18 years ago (2008) in Seattle, Washington, U.S.
Founders
Jeff Lawson · Evan Cooke · John Wolthuis
Industry
Communications
Headquarters
Rincon Center San Francisco, California, U.S.
Employees
5,587 (2025)
Key people
Khozema Shipchandler (CEO) · Mark Simms (CTO)
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 Twilio 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 Twilio shows recurring relationship patterns in the source. For example, Twilio → An, API, California, Evan Cooke, February, Global, GroupMe, January, Jeff Lawson, John Wolthuis, July, May, Michigan, On November, San Francisco, Seattle, Seed, September, SMS, Startups Another extracted example is Twilio → Authy, Beepsend, Berlin, Clef, Colorado-based, Combinator, Core Network Dynamics GmbH, Czech Republic, Denver, Germany-based, In February, In November, In October, In September, Kurento WebRTC, March, Prague, SendGrid, September, Swedish-based SMS. Use these groups to spot repeated connection types before inspecting the individual relationships.
Twilio
Top relations
related to history· 26
Twilio → An, API, California, Evan Cooke, February, Global, GroupMe, January, Jeff Lawson, John Wolthuis, July, May, Michigan, On November, San Francisco, Seattle, Seed, September, SMS, Startups
related to Acquisitions· 22
Twilio → Authy, Beepsend, Berlin, Clef, Colorado-based, Combinator, Core Network Dynamics GmbH, Czech Republic, Denver, Germany-based, In February, In November, In October, In September, Kurento WebRTC, March, Prague, SendGrid, September, Swedish-based SMS
related to Technology· 13
Twilio → Amazon Web Services, API, APIs, HTTP Webhook, In June, Kyle Conroy, One, OpenVBX, Python, Rather, SIP, Stashboard, TwiML
related to Security incidents· 12
Twilio → Authy, In, In October, July, June, On August, ShinyHunters, Signal, SMS, The, Twilio API, Twilio's
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 106 structured relationships around Twilio. Examples in this analysis include Twilio → ASN → .mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:r… and Twilio → Employees → 5,587 (2025). The table shows each extracted connection, where it came from and its confidence.
2008; 18 years ago (2008) in Seattle, Washington, U.S.
1.00
infobox
Twilio
Founders
Jeff Lawson
1.00
infobox
Twilio
Founders
Evan Cooke
1.00
infobox
Twilio
Founders
John Wolthuis
1.00
infobox
Twilio
Headquarters
Rincon Center San Francisco, California, U.S.
1.00
infobox
Twilio
Industry
Communications
1.00
infobox
Twilio
Key people
Khozema Shipchandler (CEO)
1.00
infobox
Twilio
Key people
Mark Simms (CTO)
1.00
infobox
Twilio
Net income
US$33.8 million (2025)
1.00
infobox
Twilio
Operating income
US$158 million (2025)
1.00
infobox
Twilio
Products
Voice
1.00
infobox
Twilio
Products
SMS
1.00
infobox
Twilio
Products
MMS
1.00
infobox
Twilio
Products
SIP trunking
1.00
infobox
Twilio
Products
WebRTC
1.00
infobox
Twilio
Products
2FA
1.00
infobox
Twilio
Products
Call Center
1.00
infobox
Twilio
Revenue
US$5.07 billion (2025)
1.00
infobox
Twilio
Subsidiaries
Authy
1.00
infobox
Twilio
Subsidiaries
SendGrid
1.00
infobox
Twilio
Total assets
US$9.77 billion (2025)
1.00
infobox
Twilio
Total equity
US$7.82 billion (2025)
1.00
infobox
Twilio
Traded as
NYSE: TWLO (Class A)
1.00
infobox
Twilio
Traded as
S&P 400 component
1.00
infobox
Twilio
Type of business
Public
1.00
infobox
Twilio
URL
twilio.com
1.00
infobox
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 Twilio bring nearby vocabulary together. In this analysis, examples include Announced, Data and Million. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Twilio
Announced
Data
Million
Platform
Acquired
Authy
2fa
Acquire
Service
Using
Customer
July
twilio
Announced
Data
Million
Platform
Acquired
Authy
2fa
Acquire
Service
Using
Customer
July
authy
2fa
Sendgrid
Service
Employees
Twilio
Data
Million
California
Communications
Francisco
Lawson
San
san francisco
California
Francisco
San
Seattle
Lawson
Sendgrid
2fa
Billion
Founded
Inc
Jeff
Service
data breaches
Twilio
Business
Customer
Platform
Announced
Million
2fa
Acquire
Api
Billion
Inc
Messaging
boku, inc.
California
Communications
Francisco
San
Acquire
Business
Service
Using
Phone
Twilio
Company
Data
api
July
Phone
Acquire
Messaging
Public
Service
Sms
February
Authy
Twilio's
Company
Data
phone calls
Api
San
Acquire
Business
Service
Twilio
Using
July
Authy
Data
Announced
Million
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 Twilio, one of the stronger structural bridges in this analysis connects Twilio with History. 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.
Twilio
Nodes54
Edges53
Triples106
Avg. degree1.96
Density0.037037
Components1
Source & methodology
TTTA analyzes the structure around Twilio to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Technology & Companies, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
