Traditional security is reactive. AI-powered security is predictive. We build intelligent security infrastructure that detects threats before they materialize — protecting your data, AI systems, and business continuity.
Protecting 300+ businesses & AI-first organizations globally
Modern attacks are sophisticated, adaptive, and AI-assisted. Defending with static rules is like fighting an adaptive adversary with a fixed playbook.
AI-powered attacks iterate through authentication patterns at machine speed — traditional rate limiting is no longer sufficient.
LLM APIs and AI model endpoints introduce new attack surfaces that conventional security tooling wasn't designed to protect.
Prompt injection targets LLM-powered applications — a category most security teams haven't operationalized a response to yet.
Attackers extract training data from improperly secured AI models through inference attacks — bypassing traditional perimeter controls entirely.
Supply chain attacks target AI dependencies, model weights, and third-party APIs — introducing vulnerabilities deep inside trusted pipelines.
Sophisticated threats move quietly through systems for weeks — exfiltrating data long before any static rule fires an alert.
ML models that detect behavioral anomalies before they become incidents. LLM-assisted threat analysis that contextualizes alerts instantly. Intelligent access control that adapts to risk signals in real time.
ML-driven risk scoring evaluates every access request against behavioral baselines, device fingerprints, location patterns, and time-of-access norms. Unusual patterns trigger step-up authentication automatically — your system learns what normal looks like and enforces it.
ML behavioral analytics across network, application, and API layers. Anomaly detection identifies novel attack patterns never seen before. LLM-assisted alert triage generates plain-language incident summaries, severity assessments, and recommended response actions.
Security architected at the model layer — not just the perimeter. We implement prompt injection defenses, output validation, rate limiting and abuse detection for AI APIs, model access authentication, and data leakage prevention controls. Security reviews of RAG architectures, vector databases, and third-party AI API integrations.
Data protection infrastructure that puts your business in a defensible position across GDPR, SOC 2, ISO 27001, and sector-specific frameworks. Encryption at rest and in transit, data classification and retention policy enforcement, privacy-by-design architecture for AI systems processing personal data, and automated compliance evidence collection.
We don't just audit — we architect, implement, and continuously evolve your security posture to match the AI threat landscape as it grows.
Start Security Assessment →The businesses most exposed to emerging threats are the ones that have moved fastest on AI adoption without updating their security posture. Every LLM integration, every ML model endpoint, every AI-powered workflow is a potential vector.
Behavioral threat monitoring that identifies novel attack patterns across all your AI systems and endpoints.
Real-time risk scoring that adjusts authentication requirements dynamically based on behavioral signals.
Prompt injection defense, output validation, API hardening — security at the model layer, not just the perimeter.
The data governance controls that regulators and enterprise clients require before a contract is signed.
Security posture monitoring and incident response planning that keeps pace with your technology evolution.
Enterprise clients increasingly require compliance certification before a contract is signed. We build it in from the start — not as an afterthought.
Traditional security is reactive — it fires alerts based on known signatures and static rules. AI-powered security is predictive: ML behavioral models identify novel attack patterns that have never been seen before, adapting in real time as the threat landscape evolves. Our systems detect threats before they materialize into incidents, not after they have already caused damage.
Prompt injection is an attack where malicious input manipulates an LLM into ignoring its instructions or leaking sensitive data. We implement multi-layer defenses: input sanitization, system prompt hardening, output validation layers, and API abuse detection — all specifically engineered for LLM-powered applications that standard security frameworks don't yet address.
Our ML-based behavioral monitoring detects anomalies in near real-time — typically within 4ms of a behavioral deviation. Automated response actions (blocking, step-up authentication, rate limiting) are triggered instantly without human intervention. LLM-assisted triage generates incident summaries and recommended actions for your security team within seconds.
We build compliance architecture for GDPR, SOC 2 Type I & II, ISO 27001, HIPAA, PCI-DSS, and OWASP Top 10. For businesses using ML models trained on customer data, we implement the data governance controls that regulators and enterprise clients increasingly require before contract signature — including automated evidence collection.
We augment and amplify your existing security team. Our LLM-assisted triage reduces analyst workload by automating incident summarization, severity scoring, and response recommendations — so your team focuses on strategic decisions rather than alert fatigue. We handle the AI-specific security gaps that most teams haven't yet operationalized a response to.
AI-shaped threats require AI-grade defenses. Every LLM integration, every ML endpoint, every AI-powered workflow is a potential attack surface. Let's secure all of it — predictively.