Turn AWS Security Signals Into Clear, Evidence-Backed Action
AWS can generate deep security findings, resource state, identity evidence, runtime detections, and logs. The hard part is deciding what matters, how the signals connect, what changed, and what to do next. Aegisify Digital Intelligence turns that fragmented cloud evidence into prioritized context for security, engineering, and leadership teams.
More Security Data Does Not Automatically Create Better Decisions
AWS environments can span many accounts, Regions, services, identities, workloads, controls, and security products. Each source sees part of the story. Teams still have to connect exposure, vulnerability, identity, data sensitivity, runtime activity, drift, and business importance before they can act with confidence.
Findings live in different services
Posture, threat detection, vulnerability, access, data, networking, and audit evidence can arrive from different AWS-native sources.
Severity alone is not enough
A high-severity issue may matter less than a reachable, exploitable path to a crown-jewel workload with active threat evidence.
Raw logs still need context
DI is designed to query the smallest relevant evidence window and preserve case-specific evidence instead of copying every AWS log into another warehouse.
One Intelligence Layer Across the AWS Security Lifecycle
The current DI AWS product is organized around the jobs cloud security teams perform every day—from understanding the estate to investigating incidents and proving what happened.
Cloud Command Center
Risk-first visibility into the protected AWS estate, coverage, critical issues, and workload utilization.
Critical Risks & Attack Paths
Connect network, IAM, vulnerability, data, and resource relationships into evidence-backed paths instead of isolated alerts.
Assets & Digital Twin
Normalize AWS accounts, Regions, services, workloads, configuration state, relationships, and collection health.
Vulnerability Intelligence
Use AWS-native vulnerability findings and enrich prioritization with exposure, identity, exploitability, and business context.
Identity & Entitlements
Bring access analysis, observed behavior, trust relationships, and identity evidence into the same investigation context.
Data Security
Correlate sensitive-data signals with access, encryption, exposure, criticality, and attack-path context.
Runtime Threats
Use AWS runtime and threat-detection findings as source evidence, then correlate them with configuration and behavior.
Code & Supply Chain
Bring supported AWS-native code, dependency, image, and IaC findings into cloud risk and investigation workflows.
AI Security
Track supported AWS AI security posture and runtime signals while keeping claims constrained to verified coverage.
Inspector Investigations
Build bounded, evidence-backed investigations with explicit distinctions between verified facts, strong evidence, inference, and unknowns.
Evidence & Behavior
Preserve source identity, hashes, timestamps, actor context, and case evidence without turning AI narrative into proof.
Coverage, Drift & Reports
See what is monitored, what changed, what coverage is missing, and how the security state evolves over time.
AWS Runs the Native Security Engines. DI Turns the Results Into Intelligence.
Choose the Page That Matches the Question You Are Trying to Answer
DI Compared With Wiz and Orca
See how the operating models differ across pricing, security engines, runtime, data, identity, attack paths, investigations, and current product gaps.
Pricing & AWS-Native Benefits
Understand Protected Workloads, public pricing anchors, AWS-native service costs, and why this architecture can matter for regulated and government environments.
Core DI Benefits
See how Digital Intelligence helps teams prioritize cloud risk, preserve evidence, reduce duplicated telemetry, track drift, and make investigations repeatable.
DI Threat Intelligence
See how GuardDuty intelligence, CISA KEV, FIRST EPSS, runtime context, vulnerability data, and DI evidence can improve prioritization.
Keep Provider Evidence Close to the Environment That Produced It
DI is AWS-first today. That focus supports deeper use of AWS-native resource semantics, findings, account/Region context, IAM relationships, networking evidence, and customer-owned telemetry.
Customer-owned telemetry
High-volume raw AWS telemetry stays in the customer environment by default. DI stores compact state, normalized signals, and case evidence.
Missing visibility stays visible
Permission failures, unsupported Regions, partial scans, and unavailable services should be shown as coverage limitations—not converted into false healthy states.
Partition-aware design
AWS Commercial and AWS GovCloud (US) have different partitions, endpoints, service availability, and boundary considerations. DI is designed to keep those differences explicit.
Questions Buyers Usually Ask First
Is Digital Intelligence another AWS scanner?
Not by design. DI uses AWS-native security engines where AWS already provides mature capabilities, then focuses Aegisify engineering on normalization, correlation, evidence, attack paths, behavior, investigations, reporting, workflow, and workload visibility.
Does DI copy all of my AWS logs into Aegisify?
No by default. The architecture keeps high-volume raw AWS telemetry in the customer's AWS environment and uses bounded query-in-place workflows when investigations need raw evidence.
Does DI replace Security Hub, GuardDuty, Inspector, Config, or Access Analyzer?
No. Those services can remain the source engines for posture, threat, vulnerability, configuration, or access evidence. DI adds cross-signal intelligence and workflow around them.
Is DI multi-cloud?
DI IaaS is AWS-focused today. The product should be evaluated on AWS depth and the AWS-native operating model rather than on claims of current Azure or GCP parity.
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