About Elemendar.
We Are Hiring!
About Us
Elemendar was founded in 2017 by Giorgos Georgopoulos and Syra Marshall at the UK’s first GCHQ / NCSC Cyber Accelerator, powered by Wayra UK, to develop Cyber Threat Intelligence (CTI) enrichment capabilities.
Elemendar is the leader in developing AI to translate CTI into machine readable and instantly actionable data. This can be fed into systems such as SIEMs and TIPs directly to reduce risk and return valuable time to analysts at the forefront of organisations’ defence across enterprise, government and law enforcement. Elemendar’s technology is used by both government and private customers.
Our AI automates the reading and translation of CTI from human authored unstructured text and documents into machine readable and actionable data output as STIX 2.0 and incorporating MITRE ATT&CK™. Our technology utilises leading-edge Machine Learning (ML) and Natural Language Processing (NLP) technologies.
Our Team
We have created Elemendar as we are passionate about security. Organisations and cyber analysts are drowning in critical CTI and we want to make it usable for all, not only the 1% who can afford analyst teams.
Giorgos Georgopoulos
CEO, Founder
Syra Marshall
CTO, Founder
Devon Barrett
Founder, Head of Machine Learning
ART RICHARDS
Head of Engineering & Operations
Stewart Bertram
Head of CTI
Chris Evett
Director of Strategy
Renee Griffiths
Outreach Development Manager
Rita Anjana
Machine Learning Engineer
Evans Odeh
Software Engineer
Cameron Worsley
User Experience Lead
Abdulah Fawaz
Machine Learning Engineer
Ben Strickson
Machine Learning Engineer
Sue Gibson
Talent & People Consultant
Elizabeth Brogan
Administration Manager
Fatai Balogun
Software Engineer
Ragini Gurumurthy
Junior CTI Analyst
Investors & Advisors
Jon Geater
David Moloney
Jami Jenkins
Sven Ripper
Lawrence Lundy-Bryan
What We Do
Elemendar translates unstructured reports into STIX outputs for Cyber Analysts.
Our AI makes your analysts more efficient, instantly flagging threats.
We read reports in seconds, not hours.
Save your analysts’ time.
Empower them to focus on what’s most important.
Where We’re Going
READ
C.T.I. is read and translated into STIX2.
REMEMBER
Networks are built by correlating across source C.T.I. docs.
REASON
Relationships are understood between multiple data points. Network analysis to find patterns
ORCHESTRATE
Patterns are used to share enriched context with other tools going both ways. Iterative machine-led action on C.T.I.