Find Sensitive-Data Risk Before It Becomes a Breach
A proposed AI platform that identifies sensitive information, monitors suspicious data-access activity, and helps security teams prioritize and investigate potential threats faster — without replacing human judgment on consequential actions.
Sensitive data is scattered, and rule-based monitoring is too slow to catch it
As applications, cloud infrastructure and storage grow, maintaining visibility and consistent security controls becomes harder. Traditional approaches rely on predefined rules, manual investigations and disconnected monitoring tools — which delays threat detection, increases exposure risk, and makes it hard for security teams to prioritize critical incidents like insider threats and data exfiltration.
Want Centralized Visibility Into Your Sensitive Data and Access Risk?
We'll scope a pilot around your existing data sources and security controls — measuring detection performance and false-positive rates before any production commitment.
Centralized visibility, with security teams still in control
Sensitive data discovery
Identifies and classifies sensitive information — PII, financial records, confidential documents and credentials — across supported data sources.
Intelligent access monitoring & anomaly detection
Monitors access events and flags deviations from expected behavior: unusual downloads, unexpected queries, abnormal access to sensitive resources.
AI-assisted investigation
Summarizes security events, correlates related evidence, and recommends investigation and remediation steps for every significant alert.
Proposed implementation phases
- 1Discovery and Security Assessment — identify critical data assets, sensitive-data categories and priority threat scenarios
- 2Data Integration and Threat Detection — integrate data sources, implement classification, configure security rules
- 3AI-Assisted Investigation and Response — build the security dashboard, correlate events, integrate response workflows
- 4Pilot Deployment and Optimization — test against representative scenarios and measure detection performance
Security teams stay in control
Anomalies are treated as investigation signals, not automatic proof of malicious activity. Security teams retain control over consequential actions — revoking access, isolating resources, or initiating incident response — while the platform maintains a full audit trail for compliance and governance.
Where this stands today
This is a proposed solution, not a delivered build. Quantitative targets for detection performance and false-positive rates should be established after assessing the existing security environment and measuring baseline performance during a pilot — no figures are assumed at this stage.
Security-first is our default, not an add-on
AWS Advanced Tier Partner
Certified cloud and AI delivery, so your detection platform runs on infrastructure built to AWS Well-Architected standards from day one.
Pilot-first engagement
We assess your existing environment and validate detection performance before any production rollout commitment.
Security-first by default
DevSecOps is our core discipline — IAM, encryption and secrets management are built in, not retrofitted.
Auditable AI decisions
Every alert, investigation summary and response action is logged for compliance, audit and governance requirements.
Trusted by forward-thinking teams
AWS-Certified Experts Delivering Cloud Excellence.
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Your Sensitive Data and Threats?
Tell us about your data sources and current security stack — we'll help you scope a detection and investigation pilot with clear baseline metrics.