Vectra AI vs Signzy

Vectra AI has a disclosed valuation of $1.4B, while Signzy's valuation is not publicly available, making a direct size comparison difficult. Vectra AI employs 650 people.

Vectra AI has raised more in total funding at $425M, compared to Signzy's $26M — a gap of $399M. Combined, the two companies have completed 8 known funding rounds.

Vectra AI leads with an Awaira Score of 66/100, while Signzy sits at 63/100. That 3-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Vectra AI was founded by Hitesh Sheth in 2012. Signzy was founded by Nikhil Idnani in 2015. Visit each company's profile on Awaira for a full founder biography.

Vectra AI: Vectra AI is a cybersecurity company founded in 2012 that specializes in AI-driven threat detection and response. The company develops network detection and response (NDR) and cloud detection and response (CDR) platforms designed to identify and investigate cyberattacks in real-time. Its core technology uses machine learning algorithms to analyze network traffic and cloud activity, distinguishing between normal behavior and malicious threats without relying solely on signature-based detection. Vectra's primary products include Cognito for network security and Cognito for cloud environments. These platforms provide threat hunting, incident investigation, and threat prioritization capabilities. The company serves enterprise customers across various sectors, including financial services, healthcare, and critical infrastructure. With a valuation of $1.2 billion and total funding of $425 million across Series F and earlier rounds, Vectra operates in the competitive AI security market alongside companies like CrowdStrike and Palo Alto Networks. The company has established itself in the detection and response segment rather than prevention-focused solutions. Vectra competes on its behavioral analytics approach and cloud-native capabilities. The company has demonstrated steady growth within the cybersecurity industry, driven by increasing demand for advanced threat detection and the shift toward cloud infrastructure. Its positioning reflects broader industry trends toward AI-augmented security operations. Vectra pioneered the network detection and response category by applying AI-driven behavioral analytics to identify advanced threats that signature-based tools miss. Signzy: Signzy is a digital identity verification and KYC automation platform that uses AI-powered document analysis, liveness detection, and database integration to enable financial institutions and regulated businesses to onboard customers remotely with regulatory compliance. The platform processes identity documents, conducts video KYC, and provides risk scoring through APIs that integrate with banking and fintech onboarding workflows.\n\nThe company raised approximately $26M in Series B funding from investors including Vertex Ventures and Arkam Ventures, and serves a large base of banks, NBFCs, insurance companies, and fintech platforms in India. Signzy processed tens of millions of KYC verifications and has been recognized by the Reserve Bank of India for its video KYC framework contributions.\n\nVideo KYC and digital identity verification have become mandatory for regulated financial services in India, creating a large and recurring market for compliant identity infrastructure. Signzy's deep regulatory expertise and production track record across India's financial system give it a significant advantage over generic identity verification platforms that lack India-specific compliance depth.

Vectra AI got there first, launching in 2012 — that's 3 years of extra runway. Signzy didn't arrive until 2015. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Vectra AI has about 650 employees; Signzy has about 200-500. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Vectra AI and Signzy compete in AI Security, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.