Extract actionable Signals
from noisy, unstructured data.

Every output is an actionable Signal

Each signal is extracted from multiple sources, analyzed, scored, and delivered as a structured object. Outputs include summarized insight, linked sources, confidence scoring, and tracking for momentum and novelty.

Summarized insight
Concise, decision-ready synthesis.
Linked sources
Traceable inputs and evidence.
Confidence scoring
Clear signal quality and uncertainty.
Momentum and novelty
What is changing and what is new.

Example Signal types

Killfeed Lab collects live demos and experiments built on the same signal engine—checkpoint crowd stress, structured news inspection, investment-relevant scans, and more—so you can browse outputs, limits, and methods in one place before extending the model to private workflows.

Killfeed Lab

Explore operational and strategic signal experiments side by side: CrowdPulse TSA checkpoint views, Killfeed Brief-style article intelligence, reliability-banded scans, and other public builds. Lab is where we organize and explain what is live today.

Built on a unified signal model

Every use case runs on the same signal object schema. New domains require new inputs and classifiers, not new systems.

Inputs
Events
Documents
Feeds
Unified Signal Object
source · type · confidence · novelty · momentum · metadata
Decision Surfaces
Operations
Strategic
Etc

Request a proposal

This form is for teams with a real signal extraction use case. Share requirements, constraints, and timeline so we can respond with a scoped next step, not a generic pitch.

What happens next

  1. Intro call
  2. Architecture discussion
  3. Proposal with clear scope and outcomes

We review RFP-style submissions and prioritize engagements with clear scope and buying intent.