Nova Origins
AI-assisted scientific review for exoplanet data, origins-of-life signals, content intelligence, and compounding learning.
Signal posture
candidate, unresolved, follow-up-worthy
Review state
evidence before interpretation
Eight branches, one scientific review platform.
Sprint 2 keeps these branches static and visual. Later sprints can turn them into pages, workflows, and validated product systems.
Brand + Public Experience
A premium public surface for careful science storytelling, product trust, and the Nova Origins identity.
Scientific Data Layer
Future connectors for public archive data, target pages, observation context, and provenance tracking.
Source + Content Intelligence
Source monitoring and content planning that turn reputable leads into reviewable stories with citation discipline.
Community + Review System
A contributor workflow for submissions, structured review, debunk trails, and human approval gates.
AI Review Board
Planned assistant reviewers for provenance, literature context, skeptical QA, and follow-up-worthy anomalies.
Anomaly Intelligence
A future Nova Signal Index for candidate signals, unresolved features, and model-dependent interpretations.
Nova Learning Core
A derived intelligence layer where meaningful actions become evaluated LearningEvents, never unchecked self-training.
Monetization Layer
Later pro products, alerts, API keys, and compute controls that fund better data and stronger review systems.
A compact path from foundation to scale.
The roadmap keeps Nova Origins grounded: visual system first, mock pages next, then validated data and review systems.
Foundation
repo, memory, guardrails
Public Website
visual system, public pages
Data Ingestion
archive connectors
Source Crawler
RSS, arXiv, trend leads
Content MVP
approved articles and scripts
Contributor Platform
submissions and review
AI Review Board
assistive QA agents
Signal Index
candidate signal scoring
Learning Core
events and evaluation
Monetization
pro tiers and controls
Hardening
security and monitoring
Content Scale
distribution readiness
Better review loops create better public intelligence.
The long-term value path is explicit: credible data work creates better content, attracts better contributors, and compounds into stronger review infrastructure.
Serious claims need serious restraint.
Nova Origins is designed around cautious language, source discipline, and human approval before public scientific claims.
Credibility rules
Language posture
Public copy should distinguish evidence, interpretation, speculation, and proposed tests. Preferred terms include candidate signal, unresolved feature, model-dependent interpretation, follow-up-worthy anomaly, public archive data, structured review, debunk trail, and derived intelligence layer.
Join the early review list.
This form is static in Sprint 2. It previews the future contributor and product-interest surface without connecting an email provider.