A layer that detects, correlates and contextualizes weak signals across public digital sources — for security, intelligence and institutional protection teams. Not another monitoring platform. The infrastructure that listens before the noise.
E-7714 in the last 24h?A post in a public network. Alone, noise. Presage expands that fragment into risk class, actors involved and the set of signals that haven't yet made noise — relinking what's scattered across sources that never spoke to each other.
Each signal passes through multiple analytical layers working in concert — inference, behavior, correlation, media, sources. The composition is what turns fragment into scene.
Hybrid pipeline combining analytical rules, language models and contextual inference — every signal scored, classified and weighted automatically.
Profiles actors continuously, surfacing escalation patterns against a learned baseline.
Relinks events, actors and content across sources — building context, not isolated alerts.
Continuous ingestion across public digital sources, with scalable monitoring and contextual tracking.
OCR and visual classification surface signals hidden in images and unstructured content.
Automatic ranking by criticality, context and correlated patterns.
Effective coverage of the 9 operational classes — an immediate read of the active risk profile.
Threat, reputation, leak — surfaces that look disconnected, except for the shared problem: the signal exists, but is scattered, weak and out of context. Presage solves all three the same way.
Each post passes any moderation. Presage looks at the space between them — lexical drift, temporal window alignment, deviations from the actor's baseline. The veiled signal emerges before the threat declares itself.
Sparse mentions are background noise. The layer cross-references velocity, semantics and source topology — revealing when the noise stopped being organic and started organizing. Before the visibility spike.
A dump appears. The interesting question isn't "what's in it" — it's how long it's been exposed, in which parallel sources, and what else was exposed alongside. The layer relinks the leak to the history it had already been drawing.
State changes of the signal. Presage is the layer where public fragments become signals, context and priority — before any alert happens.
Distributed public sources stop being islands. Everything converges into a single layer of continuous ingestion.
Fragments start being read as signals — lexical, behavioral, visual — classified and scored in real time.
Distributed signals recognize each other — actors, targets, time windows, patterns that only exist when seen together.
The consolidated scene flows to where the operation happens — UI, API or agent via MCP. Priority, not queue.
The same infrastructure, three surfaces designed for different roles — those who investigate, those who integrate, those who orchestrate.
Visual exploration of signals, actors and correlations in real time. Each signal opens the whole scene — not the notification, the scene.
Contextualized signals delivered to pipelines, SIEMs and risk platforms via REST and streaming. You subscribe to the stream, the layer delivers it already correlated.
Agents consume the layer without an adapter — just point to the infrastructure via MCP. The scene is already assembled, ready for autonomous reasoning.
E-7714?Presage is the infrastructure where public fragments become signals, context and priority — before your operation needs the response.