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{{Short description|AI cyber security company}}
{{Short description|AI cyber security company}}
{{Primary sources|date=October 2023}}

{{Infobox company
{{Infobox company
| name = Vectra AI
| name = Vectra AI
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== History ==
== History ==

'''The Origin as TraceVector'''

The history of Vectra AI, formerly known as TraceVector [[Limited liability company|LLC]], traces its roots back to 2008 when it was founded in [[New York City]] by a group of 4 cybersecurity professionals. Tracevector's mission was to offer security professionals an automated [[Intrusion detection system|Network Intrusion Detection System]] that could address the escalating and sophisticated [[Cyberattack|cyber-attacks]] that have increased dramatically in recent years.<ref>{{Cite web |title=Archive of TraceVector's website |url=https://web.archive.org/web/20100525082748/http:/www.tracevector.com/}}</ref>

TraceVector raised $5.3 million in [[Series A round|Series A]] funding in January 2012 and Hitesh Sheth became its President and CEO.
[[File:TraceVector-logo.jpg|thumb|TraceVector's logo]]
[[File:TraceVector-logo.jpg|thumb|TraceVector's logo]]
Vectra AI, formerly known as TraceVector, was founded in 2008 by a group of 4 cybersecurity professionals. Its mission was to offer security professionals an automated [[untrusion detection system]] that could address the escalating and sophisticated [[Cyberattack|cyber-attacks]] which had increased dramatically in recent years.<ref>{{Cite web |title=Archive of TraceVector's website |url=https://web.archive.org/web/20100525082748/http:/www.tracevector.com/}}</ref> TraceVector raised $5.3 million in [[Series A round|Series A]] funding in January 2012 and Hitesh Sheth became its President and CEO.{{Citation needed|date=October 2023}}. The company decided to relocate its headquarters to [[San Jose, California]].
This move marked a significant turning point for the company, which also decided to relocate its headquarters to [[San Jose, California]], to work on the [[Beta (software testing)|beta]] version of the platform.


The company underwent a rebranding and emerged as "Vectra Networks" in 2014 adopting the tagline "Security That Thinks".{{Citation needed|date=October 2023}}


In March 2015, Vectra launched the S-series sensor,<ref>{{Cite web |title=Vectra Networks ships a new sensor for its attack-detection gear |url=https://www.networkworld.com/article/2903056/vectra-networks-ships-a-new-sensor-for-its-attack-detection-gear.html |website=Network World}}</ref> announced record bookings growth of nearly 400 percent in 2015 over 2014 and expanded its business into [[Europe, the Middle East and Africa|EMEA]].<ref>{{Cite web |title=Vectra Networks Expands into EMEA |url=https://www.vectra.ai/news/vectra-networks-expands-into-emea |website=Vectra Networks website}}</ref>


Vectra Networks was granted its first U.S. [[patent]] on January 12, 2016. This patent covers a system for real-time network traffic monitoring to spot potential [[Zero-day (computing)|zero-day]] cyberattacks. By the end of 2017, Vectra was issued seven additional U.S. patents and is on a rapid growth trajectory with 2017 revenue growth of roughly 140% compared to 2016.{{Citation needed|date=October 2023}}
'''The Incorporation as Vectra Networks'''


With the new leadership, the company underwent a rebranding and emerged as "Vectra Networks" in 2014 adopting the tagline “Security That Thinks”.
In 2018, Vectra Networks underwent another rebranding, changing its name to Vectra AI and its product name to Cognito.{{Citation needed|date=October 2023}}

In March 2014, Vectra launched the X-series platform. It monitors both internal and internet-bound traffic, offers automated reporting, and prioritizes alerts, helping [[Security analysis|security analysts]] swiftly address the most critical risks.

In March 2015, Vectra launched the S-series sensor,<ref>{{Cite web |title=Vectra Networks ships a new sensor for its attack-detection gear |url=https://www.networkworld.com/article/2903056/vectra-networks-ships-a-new-sensor-for-its-attack-detection-gear.html |website=Network World}}</ref> announced record bookings growth of nearly 400 percent in 2015 over 2014 and expands its business<ref>{{Cite web |title=Vectra Networks Expands into EMEA |url=https://www.vectra.ai/news/vectra-networks-expands-into-emea |website=Vectra Networks website}}</ref> into [[Europe, the Middle East and Africa|EMEA]].

Vectra Networks was granted its first U.S. [[patent]] on January 12, 2016. This patent covers a system for real-time network traffic monitoring to spot potential [[Zero-day (computing)|zero-day]] cyberattacks.

By the end of 2017, Vectra was issued seven additional U.S. patents and is on a rapid growth trajectory with 2017 revenue growth of roughly 140% compared to 2016.



'''The Rebranding as Vectra AI'''

In 2018, Vectra Networks underwent another rebranding, changing its name to Vectra AI and its product name to [https://www.vectra.ai/products/cognito-platform Cognito].

During the first half of 2018, the company experienced impressive growth, marking a 138% increase <ref>{{Cite web |title=Vectra announces 138% growth in new annual recurring revenue during the first half of 2018, AI platform expansion and key cybersecurity partnership |url=https://www.vectra.ai/news/vectra-announces-138-growth-in-new-annual-recurring-revenue-during-the-first-half-of-2018-ai-platform-expansion-and-key-cybersecurity-partnership |website=Vectra.ai}}</ref>compared to the same period in 2017.

On January 25, 2022, Vectra AI completed the acquisition of Siriux,<ref>{{Cite web |title=Vectra Acquires Siriux Security Technologies to Extend Leadership in Identity and SaaS Threat Management |url=https://www.prnewswire.com/news-releases/vectra-acquires-siriux-security-technologies-to-extend-leadership-in-identity-and-saas-threat-management-301466871.html |website=PR Newswire}}</ref> a network management software company.[[File:Vectra-Networks-Logo.jpg|alt=Vectra Networks Logo|thumb|Former Vectra Networks Logo before rebranding to Vectra AI]]


== Product ==
== Product ==
Vectra AI employs a unique array of [[artificial intelligence]] techniques,<ref>{{Cite web |title=The data science behind Vectra AI threat detection models |url=https://www.tempestns.com/wp-content/uploads/2020/09/Vectra-DataScienceBehindCognito-wp.pdf}}</ref> including [[Supervised learning|supervised]] (pre-trained), [[Unsupervised learning|unsupervised machine learning]] and [[deep learning]] techniques, to detect and respond to in-progress [[Cyberattack|cyberattacks]] in real time.
Vectra AI employs [[artificial intelligence]] techniques,<ref>{{Cite web |title=The data science behind Vectra AI threat detection models |url=https://www.tempestns.com/wp-content/uploads/2020/09/Vectra-DataScienceBehindCognito-wp.pdf}}</ref> including [[Supervised learning|supervised]] (pre-trained), [[Unsupervised learning|unsupervised machine learning]] and [[deep learning]] techniques, to detect and respond to in-progress [[Cyberattack|cyberattacks]] in real time.
The product's algorithms continuously learn the behavioral norms of devices, user accounts, ports and protocols to identify signs of compromise across enterprise infrastructure. [[Threat (computer)|Threats]] are automatically triaged, scored and correlated<ref>{{Cite web |title=Understanding Vectra AI |url=https://content.vectra.ai/hubfs/downloadable-assets/Understanding-Vectra-AI-2022.pdf}}</ref> to compromised hosts, and attack behaviors are correlated across hosts to provide the “narrative” of developing attacks. These threats are prioritized on an intuitive [[user interface]]<ref>{{Cite web |title=Vectra Analyst User Experiences (Respond vs Quadrant) |url=https://support.vectra.ai/s/article/KB-VS-1673}}</ref> while alerting and remediation actions are taken with other security technologies.<ref>{{Cite web |title=29 Integrations with Vectra AI |url=https://sourceforge.net/software/product/Vectra-AI/integrations/ |publisher=[[SourceForge]]}}</ref>[[File:Vectra-AI-X-series.jpg|alt=Vectra AI's x-series appliance|thumb|Vectra AI's x-series appliance]]
The product's algorithms continuously learn the behavioral norms of devices, user accounts, ports and protocols to identify signs of compromise across enterprise infrastructure. [[Threat (computer)|Threats]] are automatically triaged, scored and correlated<ref>{{Cite web |title=Understanding Vectra AI |url=https://content.vectra.ai/hubfs/downloadable-assets/Understanding-Vectra-AI-2022.pdf}}</ref> to compromised hosts, and attack behaviors are correlated across hosts to provide the “narrative” of developing attacks. These threats are prioritized, <ref>{{Cite web |title=Vectra Analyst User Experiences (Respond vs Quadrant) |url=https://support.vectra.ai/s/article/KB-VS-1673}}</ref> while alerting and remediation actions are taken with other security technologies.<ref>{{Cite web |title=29 Integrations with Vectra AI |url=https://sourceforge.net/software/product/Vectra-AI/integrations/ |publisher=[[SourceForge]]}}</ref>[[File:Vectra-AI-X-series.jpg|alt=Vectra AI's x-series appliance|thumb|Vectra AI's x-series appliance]]
[[File:Cognito-Vectra.jpg|alt=Vectra Cognito|thumb|Vectra Cognito]]
[[File:Cognito-Vectra.jpg|alt=Vectra Cognito|thumb|Vectra Cognito]]


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== Funding ==
== Funding ==
Vectra AI raised a total of $350 million<ref>{{Cite web |title=Vectra AI Joins Security Unicorn Pack at $1.2B Valuation |url=https://www.sdxcentral.com/articles/news/vectra-ai-joins-security-unicorn-pack-at-1-2b-valuation/2021/04/ |website=SDX Central}}</ref> in funding and is considered a [[Unicorn (finance)|Unicorn]] with its $1.2 billion [[Valuation (finance)|valuation]].
Vectra AI raised a total of $350 million<ref>{{Cite web |title=Vectra AI Joins Security Unicorn Pack at $1.2B Valuation |url=https://www.sdxcentral.com/articles/news/vectra-ai-joins-security-unicorn-pack-at-1-2b-valuation/2021/04/ |website=SDX Central}}</ref> in funding and is considered a [[Unicorn (finance)|Unicorn]] with its $1.2 billion [[Valuation (finance)|valuation]].{{Citation needed|date=October 2023}}
{| class="wikitable"
|+
|'''Deal Type'''
|'''Date'''
|'''Amount'''
|'''Investors'''
|-
|Seed Round
|01-Jan-2010
|$500k
|
|-
|Series A
|03-Jan-2012
|$5.3M<ref>{{Cite web |title=TraceVector Closes $5.3M |url=https://vcnewsdaily.com/tracevector/venture-capital-funding/nrqyscktbr |website=VC News Daily}}</ref>
|Khosla Ventures, IA Ventures
|-
|Series B
|26-Aug-2013
|$8M<ref>{{Cite web |title=Network security startup TraceVector raises $8M |url=https://www.bizjournals.com/sanjose/news/2013/04/02/network-security-startup-tracevector.html |website=Silicon Valley Business Journal}}</ref>
|Khosla Ventures, IA Ventures
|-
|Series C
|05-Aug-2014
|$25M<ref>{{Cite web |title=Vectra Networks Receives $25M in Series C Financing |url=https://www.finsmes.com/2014/08/vectra-networks-receives-25m-in-series-c-financing.html |website=FINSMES}}</ref>
|Accel Partners, Khosla Ventures, IA Ventures, AME Cloud Ventures, Intel Capital, Juniper Networks (Junos Innovation Fund)
|-
|Series D
|18-Mar-2016
|Undisclosed<ref>{{Cite web |title=Wipro Ventures Invests In US-Based Cyber Security Startup Vectra |url=https://www.vccircle.com/wipro-ventures-invests-us-based-cyber-security-startup-vectra |website=VC Circle}}</ref>
|Wipro
|-
|Series D
|20-Feb-2018
|$36M<ref>{{Cite web |title=Hacker Detection Firm Vectra Networks Raises $36 Million |url=https://www.securityweek.com/hacker-detection-firm-vectra-networks-raises-36-million/ |website=Security Week}}</ref>
|Atlantic Bridge, Ireland Strategic Investment Fund, Nissho Electronics Corp, Khosla Ventures, Accel Partners, IA Ventures, AME Cloud Ventures, DAG Ventures and Wipro Ventures
|-
|Series E
|10-Jun-2019
|$100M<ref>{{Cite web |title=Vectra lands $100M Series E investment for AI-driven network security |url=https://techcrunch.com/2019/06/10/vectra-lands-100m-series-e-investment-for-ai-driven-network-security/ |website=TechCrunch}}</ref>
|TCS, Accel, Khosla Ventures
|-
|Series F
|29-Apr-2021
|$130M<ref>{{Cite web |title=Vectra AI picks up $130M at a $1.2B valuation for its network approach to threat detection and response |url=https://techcrunch.com/2021/04/29/vectra-ai-picks-up-130m-at-a-1-2b-valuation-for-its-network-approach-to-threat-detection-and-response/ |website=TechCrunch}}</ref>
|Blackstone
|}

== Patents references ==
{{Cite patent|country=US|number=20160149936|title=Method and system for detecting threats using passive cluster mapping|status=patent|pubdate=2016-05-26|fdate=2015-11-17|gdate=2018-05-29|invent1=Lopes Pegna|invent2=Beauchesne|inventor1-first=David|inventor2-first=Nicolas|assign1=Vectra Networks, Inc.|url=https://worldwide.espacenet.com/patent/search/family/056011396/publication/US2016149936A1?q=vectra%20networks}}

{{Cite patent|country=US|number=20150264068|title=Method and system for detecting bot behavior|status=patent|pubdate=2015-09-17|fdate=2015-03-10|gdate=2018-03-27|invent1=Beauschesne|inventor1-first=Nicolas|assign1=Vectra Networks, Inc.|url=https://worldwide.espacenet.com/patent/search/family/054070274/publication/US2015264068A1?q=vectra%20networks}}

{{Cite patent|country=US|number=20150312211|title=Method and system for generating durable host identifiers using network artifacts|status=patent|pubdate=2015-10-29|fdate=2015-03-10|gdate=2017-12-19|invent1=Beauchesne|invent2=Sher Gill|invent3=Kourosh Tavakoli|inventor1-first=Nicolas|inventor2-first=Monty|inventor3-first=Oliver|assign1=Vectra Networks, Inc.|url=https://worldwide.espacenet.com/patent/search/family/054072349/publication/US2015312211A1?q=vectra%20networks}}

{{Cite patent|country=US|number=20160191551|title=Method and system for detecting threats using metadata vectors|status=patent|pubdate=2016-06-30|fdate=2015-11-17|gdate=2017-12-26|invent1=BEAUCHESNE|invent2=PEGNA|invent3=LYNN|inventor1-first=NICOLAS|inventor2-first=DAVID LOPES|inventor3-first=KARL|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/056014474/publication/US2016191551A1?q=vectra%20networks}}

{{Cite patent|country=US|number=2015264083|title=Malicious relay detection on networks|status=patent|pubdate=2015-09-17|fdate=2015-03-10|gdate=2017-04-18|invent1=PRENGER|invent2=BEAUCHESNE|invent3=LYNN|inventor1-first=RYAN JAMES|inventor2-first=NICOLAS|inventor3-first=KARL MATTHEW|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/054070284/publication/US2015264083A1?q=vectra%20networks}}

{{Cite patent|country=US|number=10033752|title=System for implementing threat detection using daily network traffic community outliers|status=patent|gdate=2018-07-24|invent1=PEGNA|invent2=MHATRE|invent3=BRDICZKA|inventor1-first=DAVID LOPES|inventor2-first=HIMANSHU|inventor3-first=OLIVER|assign1=VECTRA NETWORKS|url=https://worldwide.espacenet.com/patent/search/family/055910013/publication/US10033752B2?q=vectra%20networks}}

{{Cite patent|country=US|number=9602533|title=Detecting network reconnaissance by tracking intranet dark-net communications|status=patent|pubdate=2015-09-17|fdate=2015-03-10|gdate=2017-03-21|invent1=BEAUCHESNE|invent2=YOON|inventor1-first=NICOLAS|inventor2-first=SUNGWOOK|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/054070281/publication/US2015264078A1?q=vectra%20networks}}

{{Cite patent|country=US|number=2016191563|title=System for detecting threats using scenario-based tracking of internal and external network traffic|status=patent|pubdate=2016-06-30|fdate=2015-11-02|gdate=2018-02-20|invent1=BEAUCHESNE|invent2=PEGNA|inventor1-first=NICOLAS|inventor2-first=DAVID LOPES|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/055909669/publication/US2016191563A1?q=vectra%20networks}}

{{Cite patent|country=US|number=2015264073|title=SYSTEM AND METHOD FOR DETECTING INTRUSIONS THROUGH REAL-TIME PROCESSING OF TRAFFIC WITH EXTENSIVE HISTORICAL PERSPECTIVE|status=application|pubdate=2015-09-17|fdate=2015-03-10|invent1=TAVAKOLI|invent2=MA|invent3=HUANG|invent4=PANNING|inventor1-first=OLIVER KOUROSH|inventor2-first=TAO|inventor3-first=VENABLE|inventor4-first=JEFFREY CHARLES|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/054070278/publication/US2015264073A1?q=vectra%20networks}}

{{Cite patent|country=US|number=2015264069|title=Method and system for detecting external control of compromised hosts|status=patent|pubdate=2015-09-17|fdate=2015-03-10|gdate=2016-08-02|invent1=BEAUCHESNE|invent2=RYAN JAMES|inventor1-first=NICOLAS|inventor2-first=PRENGER|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/054070275/publication/US2015264069A1?q=vectra%20networks}}

{{Cite patent|country=US|number=20210105290|title=METHOD AND SYSTEM FOR DETECTING MALICIOUS PAYLOADS|status=application|pubdate=2018-03-15|invent1=BEAUCHESNE|invent2=MANCINI|inventor1-first=NICOLAS|inventor2-first=JOHN STEVEN|assign1=VECTRA AI INC|url=https://worldwide.espacenet.com/patent/search/family/059858890/publication/US2021105290A1?q=us20210105290}}

{{Cite patent|country=US|number=10050985|title=System for implementing threat detection using threat and risk assessment of asset-actor interactions|status=patent|fdate=2015-11-02|gdate=2018-08-14|invent1=MHATRE|invent2=DAVID LOPES|invent3=BRDICZKA|inventor1-first=HIMANSHU|inventor2-first=PEGNA|inventor3-first=OLIVER|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/055909670/publication/US10050985B2?q=vectra%20networks}}

{{Cite patent|country=US|number=10404730|title=High-volume network threat trace engine|status=patent|fdate=2017-02-21|gdate=2019-09-03|invent1=VENABLE|inventor1-first=SR JEFFREY CHARLES|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/067770265/publication/US10404730B1?q=vectra%20networks}}

{{Cite patent|country=US|number=2015082433|title=Systems and methods for capturing, replaying, or analyzing time-series data|status=patent|pubdate=2015-03-19|fdate=2014-06-19|gdate=2016-01-12|invent1=HARLACHER|invent2=ABENE|inventor1-first=JAMES|inventor2-first=MARK|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/050433852/publication/US2015082433A1?q=vectra%20networks}}

{{Cite patent|country=EP|number=3355547|title=Method and system for learning representations of network flow traffic|status=patent|pubdate=2018-08-01|fdate=2018-01-27|gdate=2020-12-29|invent1=SILVER|invent2=KAZEROUNIAN|inventor1-first=MATTHEW R|inventor2-first=SOHROB|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/061131998/publication/EP3355547A1?q=vectra%20networks}}

{{Cite patent|country=EP|number=3484122|title=Malicious relay and jump-system detection using behavioral indicators of actors|status=patent|pubdate=2019-05-15|fdate=2018-10-18|gdate=2021-11-23|invent1=MHATRE|invent2=BEAUCHESNE|inventor1-first=HIMANSHU|inventor2-first=NICOLAS|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/064308531/publication/EP3484122A1?q=vectra%20networks}}

{{Cite patent|country=US|number=2015264061|title=System and method for detecting network intrusions using layered host scoring|status=patent|pubdate=2015-09-17|fdate=2015-03-10|gdate=2017-02-07|invent1=IBATULLIN|invent2=PRENGER|invent3=BEAUCHESNE|invent4=LYNN|inventor1-first=OSKAR|inventor2-first=RYAN JAMES|inventor3-first=NICOLAS|inventor4-first=KARL MATTHEW|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/054070270/publication/US2015264061A1?q=vectra%20networks}}

{{Cite patent|country=EP|number=3117557|title=Method and system for detecting algorithm-generated domains|status=patent|pubdate=2017-01-18|fdate=2015-03-10|gdate=2017-10-31|invent1=HARLACHER|invent2=SOOD|invent3=IBATULLIN|inventor1-first=JAMES PATRICK|inventor2-first=ADITYA|inventor3-first=OSKAR|assign1=EP3117557|url=https://worldwide.espacenet.com/patent/search/family/054070276/publication/EP3117557A1?q=vectra%20networks}}

{{Cite patent|country=US|number=10623428|title=Method and system for detecting suspicious administrative activity|status=patent|fdate=2017-09-12|gdate=2020-04-14|invent1=BEAUCHESNE|invent2=NI|inventor1-first=NICOLAS|inventor2-first=KEVIN SONG-KAI|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/059858564/publication/US10623428B2?q=vectra%20networks}}

{{Cite patent|country=US|number=2018115570|title=SYSTEM AND METHOD FOR CATEGORIZING MALWARE|status=application|pubdate=2018-04-26|fdate=2017-10-26|invent1=OLLMANN|inventor1-first=GUNTER DANIEL|assign1=VECTRA NETWORKS INC|url=https://worldwide.espacenet.com/patent/search/family/061969913/publication/US2018115570A1?q=vectra%20networks}}

{{Cite patent|country=US|number=11330005|title=Privileged account breach detections based on behavioral access patterns|status=patent|fdate=2019-04-15|gdate=2022-05-10|invent1=BEAUCHESNE|invent2=MHATRE|invent3=HANNAH|inventor1-first=NICOLAS|inventor2-first=HIMANSHU|inventor3-first=DANIEL CARLTON|assign1=VECTRA NETWORKS INC|assign2=VECTRA AI INC|url=https://worldwide.espacenet.com/patent/search/family/070289713/publication/US11330005B2?q=vectra%20networks}}

{{Cite patent|country=US|number=2021092140|title=METHOD, PRODUCT, AND SYSTEM FOR DETECTING MALICIOUS NETWORK ACTIVITY USING A GRAPH MIXTURE DENSITY NEURAL NETWORK|status=application|pubdate=2021-03-25|fdate=2020-09-23|invent1=KAZEROUNIAN|invent2=HANNAH|invent3=OIKARINEN|inventor1-first=SOHROB|inventor2-first=DANIEL CARLTON|inventor3-first=TUOMAS P|assign1=VECTRA AI INC|url=https://worldwide.espacenet.com/patent/search/family/072615674/publication/US2021092140A1?q=vectra%20networks}}

{{Cite patent|country=US|number=11595416|title=Method, product, and system for maintaining an ensemble of hierarchical machine learning models for detection of security risks and breaches in a network|status=patent|fdate=2020-04-28|gdate=2023-02-28|invent1=CHEN|invent2=BEAUCHESNE|invent3=MHATRE|invent4=HIMANSHU|inventor1-first=HSIN|inventor2-first=NICOLAS|inventor3-first=MANCINI|inventor4-first=JOHN STEVEN|assign1=VECTRA AI INC|url=https://worldwide.espacenet.com/patent/search/family/070804525/publication/US11595416B2?q=us11595416}}


== References ==
== References ==

Revision as of 01:56, 2 October 2023

Vectra AI
FormerlyTraceVector
Vectra Networks
Company typePrivately held
IndustryCybersecurity
Network security
Cloud security
Founded2012; 12 years ago (2012)
FoundersMark Abene, James Harlacher, Marc Rogers, Steven Lutz
Headquarters
San Jose, California
,
U.S.
Number of locations
11 offices; 3 Security Operations Centers (2023)
Area served
North America, Europe, Middle East, Africa, Australia/New Zealand, Japan and Asia-Pacific
Key people
Hitesh Sheth (CEO)

Scott Dussault (CFO) Willem Hendrickx (CRO)

Oliver Tavakoli (CTO)
ProductsVectra AI Cybersecurity Platform (formerly Cognito Platform), Vectra Detect, Vectra Recall, Vectra Stream
ServicesMDR (Managed security service)
Number of employees
580
Websitewww.vectra.ai

Vectra AI, Inc. is a cybersecurity company specializing in AI applied to network detection and response (NDR) solutions. Established in 2012, Vectra AI now operates in 113 countries from its headquarters in San Jose, California.

History

TraceVector's logo

Vectra AI, formerly known as TraceVector, was founded in 2008 by a group of 4 cybersecurity professionals. Its mission was to offer security professionals an automated untrusion detection system that could address the escalating and sophisticated cyber-attacks which had increased dramatically in recent years.[1] TraceVector raised $5.3 million in Series A funding in January 2012 and Hitesh Sheth became its President and CEO.[citation needed]. The company decided to relocate its headquarters to San Jose, California.

The company underwent a rebranding and emerged as "Vectra Networks" in 2014 adopting the tagline "Security That Thinks".[citation needed]

In March 2015, Vectra launched the S-series sensor,[2] announced record bookings growth of nearly 400 percent in 2015 over 2014 and expanded its business into EMEA.[3]

Vectra Networks was granted its first U.S. patent on January 12, 2016. This patent covers a system for real-time network traffic monitoring to spot potential zero-day cyberattacks. By the end of 2017, Vectra was issued seven additional U.S. patents and is on a rapid growth trajectory with 2017 revenue growth of roughly 140% compared to 2016.[citation needed]

In 2018, Vectra Networks underwent another rebranding, changing its name to Vectra AI and its product name to Cognito.[citation needed]

Product

Vectra AI employs artificial intelligence techniques,[4] including supervised (pre-trained), unsupervised machine learning and deep learning techniques, to detect and respond to in-progress cyberattacks in real time.

The product's algorithms continuously learn the behavioral norms of devices, user accounts, ports and protocols to identify signs of compromise across enterprise infrastructure. Threats are automatically triaged, scored and correlated[5] to compromised hosts, and attack behaviors are correlated across hosts to provide the “narrative” of developing attacks. These threats are prioritized, [6] while alerting and remediation actions are taken with other security technologies.[7]

Vectra AI's x-series appliance
Vectra AI's x-series appliance
Vectra Cognito
Vectra Cognito

Investors

Vectra AI has secured investments from a diverse group of investors, including Khosla Ventures, IA Ventures, Accel Partners, Atlantic Bridge, Wipro Ventures, AME Cloud Ventures, Intel Capital, DAG Ventures, Ireland Strategic Investment Fund, Junos Innovation Fund (Juniper), Nissho Electronics, Silver Lake, TCV, and Blackstone.[8]

Funding

Vectra AI raised a total of $350 million[9] in funding and is considered a Unicorn with its $1.2 billion valuation.[citation needed]

References

  1. ^ "Archive of TraceVector's website".
  2. ^ "Vectra Networks ships a new sensor for its attack-detection gear". Network World.
  3. ^ "Vectra Networks Expands into EMEA". Vectra Networks website.
  4. ^ "The data science behind Vectra AI threat detection models" (PDF).
  5. ^ "Understanding Vectra AI" (PDF).
  6. ^ "Vectra Analyst User Experiences (Respond vs Quadrant)".
  7. ^ "29 Integrations with Vectra AI". SourceForge.
  8. ^ "Vectra AI's Investors". Vectra AI's website.
  9. ^ "Vectra AI Joins Security Unicorn Pack at $1.2B Valuation". SDX Central.

Further reading

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