The data layer for understanding what's actually changing in tech.
Semantic search, knowledge graph, entity intelligence, and signal detection across 1,249,397 articles spanning 13 years.
50 to 90 tech articles are published every day. Most will be forgotten by tomorrow. The important patterns — an entity's coverage trajectory shifting, two companies appearing together at unusual rates, a major player going conspicuously silent — take months to form and are invisible in any single day's coverage.
TEXXR Pulse turns the daily stream into structured intelligence. Every article is embedded as a vector, entities are extracted, and structured relationships are mapped into a knowledge graph. The result: you can query not just what happened, but what changed, how fast, and whether the change is significant.
Search by meaning, not keywords. Query "chip companies that stopped licensing" and find Arm, Intel, and Samsung.
POST /api/v1/search/semantic
Structured edges from every article: partnerships, acquisitions, launches, controversies. Track how relationships evolve over time.
GET /api/v1/graph/between/Arm/Nvidia
Coverage profiles for thousands of entities. Velocity, acceleration, semantic drift, regime break detection.
GET /api/v1/entity/OpenAI/profile
Z-score spikes, coverage silences, co-occurrence anomalies, edge profile shifts. What today's headlines miss.
GET /api/v1/signals/day/2026-03-25
Track how entities transform over years. The knowledge graph detected Arm's identity break before it was obvious.
37 REST endpoints, JSON responses, interactive docs. Free tier: 1,000 req/month, all endpoints, no credit card.
Triangulation connects articles across years that keyword search would never surface. The CLI makes it fast.
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