Exaforce
announced $75 million in Series A funding led by marquee
investors Khosla Ventures, Mayfield, and Thomvest Ventures to develop
its Agentic SOC Platform that combines AI agents (called "Exabots") with
advanced data exploration to give enterprises a tenfold reduction in
human-led SOC work, while dramatically improving security outcomes.
Founded by tech leaders with multiple successes and extensive expertise
in AI and cybersecurity at companies such as Google, F5, and Palo Alto
Networks, Exaforce has developed the industry's first multi-model AI for
solving challenges in security and operations. This new approach blends
large language models (LLMs) with semantic and behavioral models into a
powerful AI engine that unlocks unprecedented accuracy, repeatability,
and productivity for the SOC.
"We believe Exaforce's multi-model approach is unique in the industry
and will dramatically reduce the false positives and investigation times
we experience in our cloud and SaaS environments," said Pranay Anand,
Vice President at NTT Data. "The platform augments our SOC teams by
delivering streamlined security operations and faster incident response
for every client, freeing up more time to focus on proactive threat
hunting."
SOC Challenges = Real + Growing Need
Enterprises are asking for a SOC solution that is better at delivering
effective and consistent response to threats, faster at detecting and
investigating issues, and cheaper to scale defenses on demand without
scaling people.
SOC analysts face a deluge of alerts-most of which are false
positives-leaving them burdened with massive datasets and manual tasks
like log stitching, user validation, and ticket management, which drain
resources and slow response times. Detection engineers, meanwhile,
struggle with the threat coverage for cloud environments where native
threat detection is often lacking and traditional SIEMs offer inadequate
coverage. This forces them to write and maintain complex sets of
SQL/python code, yet major detection gaps remain. Simultaneously, threat
hunters are mired in manual, time-consuming workflows that impede
proactive threat detection, making it difficult to stay ahead of
attackers.
The well-documented shortage of skilled security professionals
exacerbates these issues, making it difficult for organizations to
maintain expertise across all SOC roles. As a result, SOCs risk burnout,
delayed response, and increased exposure to growing threats.
Exaforce Is the Right Team to Propel the SOC
Solving these challenges requires an innovative team with concentrated backgrounds in cybersecurity, AI, and cloud operations. Exaforce's founding team unites expertise across all three - with firsthand experience leading the world's most complex SOC environments.
They've operated large scale security services at F5, protecting the
world's biggest banks and social networks, designed the complex models
underlying Google's AI services, spearheaded the industry-leading cloud
security platform at Palo Alto Networks, and successfully founded and
scaled multiple startups. Through these experiences, Exaforce's founding
team has gained a front-row seat to the problems faced in today's SOC
and a nuanced grasp of AI's potential and pitfalls.
"At Mayfield, we invest in founders first and foremost, which is why we
backed Exaforce at the ideation stage in our third collaboration with
Ankur Singla," said Navin Chaddha, Managing Partner at Mayfield. "What
excites us is how Exaforce is reimagining the massive opportunity of
developing AI teammates to offload complex tasks that help humans
increase productivity and efficacy, and they are starting with the SOC
market where the problems of skills and talent are acute. The team's
progress since those initial whiteboard sessions-securing a dozen
enterprise design partners, and delivering 10x improvements in SOC
efficiency-validates our early conviction that Exaforce is building
something revolutionary in the collaborative intelligence era."
Industry's First Multi-Model AI Built for Security & Operations
The right AI solution for the SOC must analyze enormous volumes of logs,
cloud telemetry, and threat data to make rapid, high-stakes decisions.
Agentic solutions that rely solely on LLMs can only review a fraction of
that data at once, resulting in incomplete problem analysis and
reasoning that is unreliable and hallucination-prone.
Exaforce
overcomes this technical barrier with a multi-model (aka layered) AI
engine that is purpose-built for security and operations. It applies
these models in combination, starting with a semantic data model, along
with statistical and behavioral models, to extract key insights,
behaviors, and relationships from raw data, then performs deeper
analysis with knowledge models. This structured use of multiple models
not only rightsizes, but also improves the quality of SOC data, which is
then fed into LLMs-enabling end-to-end reasoning across the full scope
of data. This approach avoids the blind spots of systems that use only
LLMs and delivers more accurate, repeatable results.
While in stealth, the company has been collaborating with over 10
leading enterprises across technology, AI software, energy, and
manufacturing markets to refine this multi-model approach, and
delivering significant gains to their SOC teams in the process.
"Our vision is to empower SOC teams with an intelligent platform that
allows humans to collaborate seamlessly with AI agents-integrating
precise human oversight with advanced automation," said Ankur Singla,
co-founder and CEO of Exaforce. "By harnessing Exabots alongside
advanced data exploration, we reduce false positives and eliminate
tedious busywork-all while giving humans the flexibility to choose where
they want to be hands-on. This approach has already delivered 10x
improvements to our design partners. Our design partners have already
seen tenfold improvements using this approach."