Receives structured intelligence from participating CNIS™ products.
Federated security intelligence
Findings are useful. Connected findings decide.
INFERA™ — the federation layer behind RixNexis™ — brings complementary CNIS™ intelligence together so security leadership can understand relationships and combined security context, not a pile of disconnected findings.
Tap to pulse
ERI · RixTrace™Federated
TRI · RixIntel™Federated
CRI · RixControl™Partial coverage
ORI · RixLogix™Federated
VERDICT · INFERA™Combining
ERI · RixTrace™Federated
TRI · RixIntel™Federated
CRI · RixControl™Partial coverage
ORI · RixLogix™Federated
VERDICT · INFERA™Combining
ENGINE INFERA™
PLATFORM CNIS™
STATUS FEDERATING
Federated
Partial coverage
Combining
4CNIS™ modules illustrated
2Cross-module relationships shown
1Combined VERDICT produced
Evidence-awareBands pending design sign-off
Not a roll-up
Relationships, not just more dashboards
Federation receives structured intelligence from participating CNIS™ products and connects relevant findings into a broader organizational security picture — run by the INFERA™ engine across the CNIS™ platform.
Supporting context is preserved throughout, so a combined result can be understood rather than treated as an unexplained number. Every additional CNIS™ module a customer adopts makes the combined picture more valuable, not just more crowded.
CNIS™ architecture
INFERA™ speaks the same language as the rest of CNIS™
Every module — INFERA™ included — moves evidence through the same three-stage framework before it reaches a decision-maker.
S
Signals
Structured intelligence received from participating CNIS™ products — exposure, threat, control, and operational findings.
→S
Scenarios
Signals connected into the credible cross-module relationships that matter — not a flat merge of unrelated findings.
→I
Intelligence
A structured VERDICT your team — and the rest of CNIS™ — can act on directly.
// SIGNALS → SCENARIOS → INTELLIGENCE — the SSI framework CyberNeurix Pulse runs across cybersecurity and neurotechnology alike.
Beyond a single number
A combined picture is a state, not a score
A cross-module security picture can't be reduced to one static figure. INFERA™ reads and reports what a scenario currently is, not just where it sits on a scale.
Active
A credible, corroborated scenario supported by fresh evidence across the modules it depends on.
Emerging
A scenario that is forming, but not yet fully corroborated across the modules that would confirm it.
Insufficient
Evidence doesn't yet support a scenario either way — never rendered as a favorable result by default.
Contained
A previously active scenario that is no longer progressing, tracked rather than dropped from view.
Product
These four findings are all real. What do they mean together?
Not another generic dashboard roll-up. INFERA™ focuses on whether complementary CNIS™ intelligence, brought together, reveals relationships that matter for the whole organization.
Receive
Connect
Connects relevant findings into a broader organizational security picture.
Preserve
Preserves supporting context so a combined result can be understood, not treated as an unexplained number.
Federate
Provides the federation layer through which CNIS™ becomes more valuable as customers adopt additional modules.
Why it matters
Specialized findings that stay disconnected are only half the answer
- Security decisions often span exposure, threat, controls, and operational assurance at the same time.
- Specialized tools can produce valuable findings that remain disconnected from one another.
- Leadership needs a combined security context without losing the provenance of the contributing intelligence.
- Federation across purpose-built CNIS™ products.
- Scenario/context orientation rather than a generic dashboard roll-up.
- Preserves supporting context for combined decisions.
- Value increases as the customer adds a second and subsequent CNIS™ module.
Measurement & output
VERDICT — evidence-aware, not falsely certain
This page describes what the output means and how teams read it. What sits behind it — the federation logic, evidence weighting, and calibration — is deliberately not published.
Illustrative readout
Combined Security VERDICT
Low confidenceHigh confidence
Shape only — no real scoring, thresholds, or calibration data shown. Bands pending design sign-off.
A scenario state with its supporting evidence preserved, so a partially corroborated pattern never presents as a confirmed one.
A clear separation between the relationships INFERA™ identified and the conclusions your team draws. Structured for leadership and for the decision layer that follows.
Competitive landscape
Where INFERA™ sits, and what it defends
A capability-level view based on public 2026 market sources. Not a claim of feature parity with every platform listed — a statement of category boundary.
| Market alternative | Category | Typical strength | CNIS™ distinction |
|---|---|---|---|
| Security exposure management platforms | Cross-domain security context | Aggregate exposure, vulnerability, identity and threat context for prioritization. | INFERA™ is positioned as a CNIS™ federation layer across specialized products rather than as a broad third-party exposure platform. |
| Cyber risk quantification platforms | Risk aggregation / decision support | Combine technical and business information to express organizational cyber risk. | INFERA™ focuses on cross-module security context and scenario relationships rather than claiming to replace enterprise cyber-risk quantification. |
| Security analytics / SIEM platforms | Telemetry analytics | Correlate large volumes of security events and operational telemetry. | INFERA™ is not a SIEM; its role is to federate the structured outputs of CNIS™ products. |
| Enterprise risk platforms | Enterprise risk aggregation | Aggregate risk information across business functions. | INFERA™ is security-domain focused and designed around the CNIS™ product family. |
Market comparison is capability-level; reviewed against exposure-management, cyber-risk and security-analytics categories in 2026.
Differentiation strategy
Federate typed outputs. Don't roll them up into an average.
The easy version of this product is a dashboard that shows four scores side by side. INFERA™ is the harder version: it reasons over the relationships between them, and it will report an insufficient scenario rather than manufacture a combined number that nothing supports.
Where INFERA™ competes
- Federation across purpose-built CNIS™ products.
- Scenario/context orientation rather than a generic dashboard roll-up.
- Preserves supporting context for combined decisions.
- Value increases as the customer adds a second and subsequent CNIS™ module.
Where it deliberately doesn't
Do not position this product as a universal replacement for SIEM, enterprise GRC, global threat intelligence, vulnerability management, or broad enterprise risk software.
The strategy is specialization plus composition. INFERA™ is where composition actually pays: each module a customer adds makes the scenario picture more complete, not merely more crowded.
CNIS™ architecture position
Where INFERA™ sits in the pipeline
Input
Evidence / Sources
Approved product-specific evidence across the CNIS™ platform
→
RixNexis™
INFERA™
Domain analysis → VERDICT
→
Output
CNIS™
Structured intelligence for wider security context
Use cases
What security leadership actually does with it
Baseline
Establish an evidence-based baseline for cross-module security intelligence.
Investigate
Follow a scenario back through every module output and evidence record that supports it.
Report
Give the board the organizational story rather than four disconnected departmental scores.
Connect
Hand a corroborated scenario to PRAXIS™ so the intervention decision has context behind it.
Buyer profile
Bought when four green dashboards hide one red story
The buyer already has specialist tools that each report acceptable status. What they are missing is the connection — the exposed service that is only dangerous because a control went silent and a campaign started targeting that technology.
Can the product give us a clearer view of our cross-module security intelligence position?
Will we see the relationship between findings, not just the findings?
When the evidence does not support a scenario, will it say so rather than guess?
Does this get more useful as we add modules, rather than just noisier?
See relationships your findings couldn't show alone
A live demonstration walks through a realistic input, the RixNexis™ workflow, the resulting VERDICT, supporting context, and the decision it supports.