- We’ll be at RSA Conference 2026, Moscone Center, San Francisco | 23rd - 26th March, 2026 | N-6473
| Triage alerts automatically | Analyzes and prioritizes alerts instantly based on risk, context and behavioral cues |
| Detect zero-day threats | Behavior analytics, anomaly modelling and outlier detection to detect stealthy attacks |
| Automated correlation | Links weak and scattered signals into a meaningful threat storyline |
| Predictive hunting | Surface likely hypotheses and investigation paths |
| AI powered decision making | Receive guidance with root cause analysis, incident summaries and knowledge of threat tactics |
| Always learning | Improved accuracy over time through analyst feedback and evolving behavioral patterns |
| Investigate in natural language | Ask questions in plain English and get instant responses |
Vehere Vision AI combines deep neural networks, signature-based detection, and behavioral analytics to generate high-fidelity alerts. By categorizing anomalies into high, medium, and low risk, it empowers rapid, precise threat detection and response at scaleÂ
Vehere Vision AI groups similar behaviors together and isolates signals that don’t fit any known pattern to identify rare, unusual, or emerging threats
Vehere Vision AI provides clear, contextual reasoning mapped to MITRE techniques, historical behavior, and contributing factors
Vehere Vision AI connects alerts with session data and live threat intelligenceÂ
Vehere Vision AI learns from analyst decisions capturing recurring judgement patterns. This feedback continuously refines the model, improving accuracy and adapting to each organization’s environment
Analyst can initiate autonomous, policy-aligned actions such as isolating suspicious activity, enriching investigations, or triggering response workflows
Automates detection and triage, reducing noise and analyst fatigue
Lowers Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR) for faster containment
Processes massive volumes of raw network data and converts it into clear, prioritized insights
Exposes lateral movement, insider threats, and anomalies invisible to perimeter and endpoint defenses
Continuously refines detection models with evolving attack patterns, ensuring resilience against emerging threats
No. Vehere Vision AI is not just an LLM or chat interface. It combines predictive, generative, and agentic AI models to detect threats, explain risk, and drive action. LLM enables interaction, explanation and autonomous actions.
Vehere Vision AI is powered by a hybrid AI framework that unifies supervised, unsupervised, deep learning, and large language models over real-time and historical network dataÂ
Vehere Vision AI learns normal behaviour across users, devices, and applications, then detects anomalies, outliers, and suspicious sequences that indicate known, unknown, and zero-day threats.Â
It automatically enriches alerts with context, explains why they matter, enables natural-language investigations, and guides next steps, enabling analysts of any skill level to investigate faster and more confidently.Â
By correlating weak signals, assigning risk scores, learning from analyst feedback, and suppressing noise over time, Vision AI surfaces fewer but higher-confidence, actionable alerts.Â
