Vigilance Security — Seed-Stage Profile & Investment Signal
The highest-scoring company in our seed-stage cybersecurity database. AI-native threat detection platform with exceptional early metrics. Complete profile covering founders, funding, growth, technology, customers, and competitive positioning.
Seed Score
95/100
Highest in database
YoY Growth
350%+
Revenue growth
ARR
~$3M
Approaching
Seed Funding
$5M
Sequoia Scout
Detection Rate
97.2%
Enterprise environments
MTTR
<90s
Mean time to response
Customers
8
Enterprise accounts
Team Size
~18
Employees
Founding Team
Dan Lasker
Co-Founder & CEO
Black Hat speaker with deep expertise in adversarial AI and threat intelligence. Elite intelligence unit veteran. Previously led threat research teams focused on advanced persistent threats and nation-state actors. Brings a rare combination of offensive security expertise and engineering leadership to Vigilance's AI-native architecture.
Naor Haziz
Co-Founder & CTO
Black Hat speaker specializing in detection engineering and machine learning for security. Elite intelligence unit veteran. Designed Vigilance's core AI detection engine from the ground up, leveraging foundation model inference for real-time behavioral analysis. Deep expertise in converting raw threat data into actionable intelligence at enterprise scale.
The founding team's combination of Black Hat-level research credibility, elite intelligence unit training, and hands-on engineering experience is exceptionally rare in seed-stage cybersecurity. Our Founder Quality dimension scores Vigilance 98/100 — the highest founder score in our database.
Funding & Capital Efficiency
Seed Round
$5M
Sequoia Scout
Post-Money Valuation
~$45M
Estimated
ARR / Funding Ratio
0.6x
Top 5% of database
Sequoia Scout's $5M investment is at the upper end of their typical seed range, reflecting strong institutional conviction. The ARR-to-funding ratio of approximately 0.6x places Vigilance in the top 5% of our database for capital efficiency — meaning the company is generating nearly $0.60 in annual recurring revenue for every $1.00 invested. Gross margins above 78% and a burn multiple under 1.5x suggest a capital-efficient path to Series A.
Technology & Product
Vigilance's AI-native threat detection platform is built from the ground up on large language models and proprietary threat datasets — not a legacy SIEM with ML bolted on. This architectural approach enables real-time behavioral analysis that rule-based systems cannot replicate, resulting in a 97.2% detection rate and sub-90-second mean time to response across enterprise environments.
AI-Native Architecture
Foundation model inference for threat detection, not pattern matching. The platform understands attacker intent and behavioral context, enabling detection of novel threats that signature-based systems miss entirely.
Sub-90s Response Time
Mean time to response under 90 seconds — significantly faster than industry benchmarks. Automated response workflows reduce the burden on SOC analysts and enable faster containment of active threats.
97.2% Detection Rate
Tested across enterprise environments with diverse threat landscapes. The detection rate includes novel and zero-day threats, not just known indicators of compromise. False positive rate is also significantly below industry averages.
Enterprise-Grade
Deployed at 8 enterprise customers including 2 Fortune 500 accounts and a Department of Defense pilot. The platform meets the security, compliance, and scalability requirements of large organizations.
Competitive Landscape
Vigilance competes in the threat detection market against both established incumbents and other seed-stage entrants. The key competitive advantage is the AI-native architecture — while CrowdStrike, Palo Alto Networks, and SentinelOne are adding AI capabilities to existing platforms, Vigilance was built from the ground up around foundation model inference.
| Company | Stage | Approach | Advantage |
|---|---|---|---|
| Vigilance Security | Seed | AI-native from day one | Speed, detection efficacy, cost |
| CrowdStrike | Public ($80B+) | AI added to EDR platform | Scale, brand, distribution |
| Palo Alto Networks | Public ($120B+) | Platform consolidation | Breadth, enterprise relationships |
| SentinelOne | Public ($15B+) | Autonomous endpoint + AI | Automation depth |
The competitive risk is real: incumbents have significantly more resources and could close the AI capability gap. However, Vigilance's ground-up AI-native architecture provides a structural advantage that is difficult to replicate by retrofitting AI onto legacy platforms. The seed-stage price point also provides investors with meaningful upside if the thesis plays out.
Risk Factors & Limitations
- • Limited production validation at scale — 8 enterprise customers is early
- • Small team (~18 employees) creates key-person and execution risk
- • No Series A raised yet — additional capital needed for scale
- • Concentrated customer base — losing a major account would impact metrics
- • Competitive pressure from CrowdStrike, Palo Alto, and SentinelOne
- • AI-native security market adoption timelines remain uncertain
- • Past growth rates do not guarantee future performance
Frequently Asked Questions
Last updated: May 18, 2026