Contradiction handling
Expose inconsistent witness, system, log or telemetry claims before they distort the conclusion.
AxoDen Forensic Intelligence
Evidence graph workflow
Structure incomplete evidence into defensible investigations.
Forensic intelligence
Luminesce designs forensic evidence graph workflows for cyber incidents, technical root-cause analysis and investigations where observations are noisy, partial or contradictory.
What the workflow does
The work is to make investigative reasoning inspectable. Evidence is captured as a graph, constraints are explicit, and gaps are surfaced as findings, not buried as assumptions.
Missing-evidence detection
Identify observations that should exist under the investigation schema but are absent from the corpus.
Replayable reasoning
Keep a record of accepted evidence, rejected evidence and unresolved uncertainty.
Use cases
The strongest fit is a cyber or technical investigation where the buyer already has telemetry, logs, reports or case notes and needs a clearer path from evidence to decision.
- Cyber incident triage and post-incident review.
- SOC escalation review where SIEM/SOAR output needs campaign-level structure.
- Ransomware containment and post-incident evidence review.
- Technical root-cause analysis where logs, telemetry and human reports conflict.
Pilot shape
A forensic pilot is scoped around one investigation question and one bounded evidence corpus the buyer already holds.
Input
A bounded incident corpus, current investigation workflow, relevant telemetry/log sources and one or two investigation questions that matter to the buyer.
Build
Evidence graph schema, deterministic operator stack, gap and contradiction checks, replay ledger and analyst-facing findings pack.
Output
Campaign-level evidence package, pivots, unsupported-claim register, next-investigation recommendations and integration notes.