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FETCH is a cross-platform forensic acquisition platform built for DFIR, incident response, and investigative operations across distributed environments. It enables targeted and full-scope data collection from Linux, macOS, and Windows endpoints, as well as iPhone and Android devices, through a unified collection workflow.
The platform supports both local and remote evidence acquisition, including secure internet-based collections, allowing investigators to capture relevant data without requiring physical access to the device. FETCH also normalizes collected date and time values across sources, helping analysts correlate events more accurately, reduce timeline inconsistencies, and streamline analysis across multi-device investigations.
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AI doesn’t just analyze evidence—it decides how to analyze it. RemiFetch adapts forensic methodology in real time based on detected patterns, automatically applying the right techniques—correlation, artifact extraction, behavioral analysis, and timeline reconstruction—to match the investigation.
By linking signals across systems and evolving its approach as new evidence emerges, AI reveals relationships and attack paths that static workflows cannot. This enables deeper insight, faster investigations, and defensible, evidence-driven conclusions.
Remi turns fragmented raw data into operational intelligence that helps defense and security teams identify, track, and understand hostile activity. By exposing adversary patterns, surfacing indicators of compromise, and correlating events across datasets, it gives analysts clearer visibility into malicious behavior and emerging threats.
Designed for mission-driven environments, Remi helps teams move faster from data to decision by converting overwhelming log volume into intelligence that supports threat detection, attribution, and response. The result is a sharper understanding of adversary tactics, techniques, and actions across the operational landscape.
Remi converts raw data into operational intelligence that answers the critical questions adversaries hope you never can. By transforming fragmented logs and technical artifacts into structured investigative insight, Remi helps teams determine what happened, who was involved, how access was gained, how long malicious activity persisted, and which attack paths were used.
Built for defense, incident response, and high-consequence investigations, Remi cuts through data volume to deliver clear, defensible answers at speed. The result is faster investigative clarity, stronger situational awareness, and a more complete understanding of adversary actions across the environment.
RemiFetch includes a built-in, case-specific GPT assistant that runs locally—allowing investigators to interact directly with their evidence using natural language. Ask questions about timelines, events, users, or systems, and receive context-aware answers grounded in the actual case data.
The assistant understands the structure of the investigation, helping to surface relevant evidence, explain findings, and guide deeper analysis without requiring manual searching or complex queries. Because it operates locally, sensitive data never leaves the environment—ensuring privacy, control, and compliance.
Real-world investigations involve evidence from multiple systems, platforms, accounts, and vendors—often in different formats and locations. RemiFetch aggregates this mixed evidence into a single, normalized dataset, bringing together event logs, user activity, system data, and artifacts into one consistent structure.
By unifying evidence at the source, RemiFetch eliminates fragmentation and prepares data for detection, correlation, and analysis. Investigators no longer need to manually collect, convert, or reconcile data—everything is organized, aligned, and ready to be explored.
These reports together answer the key investigative questions: Where did the money come from? Where did it go? Who was involved? How were accounts connected? What activity indicates fraud, theft, or financial misconduct?
What happened How the incident unfolded Which systems were involved Who accessed what Whether data was stolen, modified, or moved They essentially convert raw logs into a full investigative case narrative.
They allow investigators and regulators to quickly answer: What operational changes occurred Who accessed plant control systems Whether treatment parameters were altered How commands moved through SCADA / OT systems Whether safety or alarm systems were affected
Read more …Aggregated Evidence