UAE-first. Global by architecture.
SYBERIS begins with UAE cyber exposure and regulatory intelligence, with an architecture designed to expand across jurisdictions, regulatory frameworks and security ecosystems.
Understand your exposure. Know your obligations. Know what to do.
Expansion model
From a beachhead to a jurisdiction-agnostic layer.
Roadmap stages are clearly labelled. SYBERIS does not claim coverage of jurisdictions or frameworks that are not implemented in the product today.
UAE IA, PDPL, ADGM, DIFC and ISO 27001:2022 mappings implemented in the product.
Neighbouring regulatory regimes reuse the same framework registry — not available today.
Long-term vision. Additional jurisdictions plug into the same requirement → control → evidence model.
Vision stage: cross-jurisdiction intelligence over a shared regulatory graph.
Product loop
One loop. Every assessment feeds the next.
Every assessment creates context for the next one.
Historical exposure and scan history are stored and used for trend and regression detection today. Learning that changes prioritization automatically is in development, not live.
Why SYBERIS?
Detection is not the hard part. Decisions are.
Know your exposure
Understand your organization's external cyber exposure, security findings and evolving risk posture.
Know your obligations
Map applicable security controls and regulatory requirements against available technical and compliance evidence.
Know what to do
Prioritize remediation, assign actions, collect evidence and verify improvement.
From detection to decision to verification.
Intelligence engine
From security data to actionable intelligence
External APIs and data providers are inputs. SYBERIS transforms, correlates and contextualizes that data into security and regulatory intelligence — it does not own or operate the upstream data sources.
Every provider response is translated into one internal finding model before it reaches scoring or the UI.
Severity, exposure, corroboration and remediation state are combined by a deterministic, inspectable model.
Findings only close against uploaded verification evidence, never on an AI opinion.
Scheduled re-assessment and drift detection.
Architecture
Provider-independent by design
SYBERIS is designed around a normalized intelligence layer so individual external providers can be replaced without redesigning the customer experience or core risk and compliance models.
APIs are inputs. Intelligence is the product.
SYBERIS normalizes security observations, regulatory requirements and evidence into an explainable intelligence layer that organizations can act on.
- Reputation & threat intelligence providers
- Vulnerability intelligence (CVE/CVSS)
- DNS & certificate observation
- First-party HTTP/TLS collection
When a provider is unavailable
User-facing state when sources are degraded: “Some intelligence sources are currently unavailable. Results may be incomplete.” — shown with last successful update, provider status and data completeness.
Measurement
Three scores. Three independent methodologies.
SYBERIS deliberately keeps asset risk, organizational exposure and regulatory readiness separate. A clean scan does not make a control compliant, and one domain's score is not an organization's exposure.
Asset risk score
Security risk of one scanned asset or domain, derived from that asset's active findings and their severities.
Per-asset severity weighting with per-severity caps.
Cyber exposure score
Organizational exposure across monitored assets. Scored per asset; the workspace score reflects the most exposed asset rather than a sum.
Deterministic contributors, each attributable to listed findings.
Regulatory readiness
Evidence-backed readiness against applicable controls — never derived by averaging technical findings.
In-scope controls only; partial credit for partially evidenced controls.
How every score is presented
Where inputs are missing, SYBERIS shows “Insufficient evidence” or “Assessment incomplete” instead of inventing a number. Scores rendered in the UI come from the same model the assessment itself uses.
Evidence-first compliance
A control is compliant when evidence says so
AI-generated text is never treated as regulatory evidence. Every compliance claim carries a provenance state.
Derived from a technical observation SYBERIS made directly.
Uploaded by your team and attached to the control.
Reviewed and accepted against the control requirement.
Present but not yet reviewed.
Excluded from scope with a recorded reason.
The honest default. Not the same as compliant.
Roadmap
Today → Next → Future
- Exposure assessmentLIVE
- Security findingsLIVE
- Risk scoringLIVE
- UAE regulatory mapping (implemented frameworks)LIVE
- Compliance assessmentLIVE
- Remediation workflowLIVE
- EvidenceLIVE
- ReportingLIVE
- Continuous monitoringIN DEVELOPMENT
- Historical postureLIVE
- Regulatory change detectionROADMAP
- Asset graphROADMAP
- Evidence graphROADMAP
- IntegrationsROADMAP
- AI-assisted workflowsIN DEVELOPMENT
- Predictive exposureROADMAP
- Regulatory knowledge graphROADMAP
- Advanced agent orchestrationROADMAP
- Automated evidence collectionROADMAP
- Controlled remediationROADMAP
- Multi-jurisdiction intelligenceROADMAP
- Global regulatory intelligenceROADMAP
AI posture
AI is the execution layer, not the moat.
Each stage is a planned capability, not a shipped one. Only AI-assisted explanation is available today.
AI-assisted explanations
AI-assisted triage
Agent-assisted investigation
Agent-assisted evidence & compliance workflows
Controlled remediation workflows
Multi-agent cyber intelligence
No autonomous destructive action is ever taken without explicit human authorization.
Trust
Designed for trust
Evidence-backed. Explainable. Timestamped.
Every finding carries its observation, target, detector and confidence.
Each point of a score is attributable to a listed contributor.
State changes record actor, timestamp and previous value.
Workspace data is enforced at the database layer, not in the UI.
Vendor formats never reach the frontend directly.
Recommendations require approval before anything changes.
Missing evidence stays missing.
Observed, customer-provided or unverified — always labelled.
SYBERIS holds no security certifications today and makes no “100% secure” claim. Certification status will be stated only when accredited audits are completed.
Moat
Where the long-term moat comes from
The long-term advantage is not access to a single API. It is the intelligence accumulated from security observations, regulatory mappings, evidence, remediation outcomes and longitudinal exposure data.
Regulatory intelligence
UAE IA, PDPL, ADGM, DIFC and ISO 27001:2022 requirement → control → evidence mappings implemented in product.
Normalized security data
One internal finding model behind every provider, so intelligence is not tied to a vendor format.
Exposure history
Timestamped assessment history per asset — the base layer for longitudinal intelligence.
Evidence & workflow graph
Linking evidence, controls, owners and remediation outcomes into one queryable graph.
Proprietary risk intelligence
Building toward: risk models informed by accumulated remediation outcomes across assessments.
Pillars 04 and 05 are stated as capabilities SYBERIS is building toward, not as an existing proprietary moat.
Why UAE?
Our beachhead, chosen deliberately
Cloud and internet-facing adoption is expanding faster than in-house security capacity.
Boards, insurers and counterparties increasingly ask for demonstrable posture.
Federal, ADGM and DIFC regimes coexist for the same organization.
Obligations are known; the evidence trail is usually the missing part.
Under-served by enterprise-priced GRC and exposure tooling.
Neighbouring markets share the structure, not the specifics.
UAE is our beachhead. The architecture is designed for international expansion.
Founder vision
The long-term vision
Cybersecurity should not require organizations to assemble disconnected tools just to understand their exposure, regulatory obligations, evidence and remediation priorities.
SYBERIS is building the intelligence layer that connects those pieces into one continuously evolving security and regulatory picture.
UAE exposure intelligence
Continuous monitoring + compliance workflow
UAE regulatory intelligence engine
GCC expansion
Predictive cyber intelligence
Global regulatory intelligence platform
Honest assessment
Risks we are actively designing against
Multi-provider architecture plus first-party collection.
UAE regulatory intelligence wedge, not another scanner.
Evidence provenance, confidence levels and transparent scoring.
Authoritative primary sources and qualified human review.
SME-first motion with partner and enterprise expansion.
AI is the execution layer; the regulatory model is the moat.
Partner, MSP and MSSP distribution.
Building the intelligence layer for the next generation of cyber risk.
UAE-first. Global by architecture.
SYBERIS provides security and compliance intelligence and does not replace qualified legal, regulatory or cybersecurity advice.
Explore SYBERIS