DAEPOLIS is judgement infrastructure.
This guide describes the system as it is being built in code: decision records, claim ledgers, source hardening, review workflow, forecasts, exports, and calibration. It is intentionally shorter than the methodology page because the product should be inspectable before it is persuasive.
Core Surfaces
The public site should map to the database and workflow objects, not just explain the analysis style.
Durable records containing the question, decision owner, source pack, claims, evidence, forecasts, objections, review status, monitoring triggers, and later outcome.
PDF and Office uploads must produce trusted extraction reports before the text can enter the untrusted-content boundary. Raw private files are not stored.
Existing consultant reports, AI memos, ESG briefs, policy papers, board papers, and investment notes can be decomposed into claims, warrants, implied priors, belief debt, missing counter-evidence, falsifiers, adversarial objections, and questions before reliance.
Companies, countries, buyer markets, sources, claims, contracts, portfolios, regimes, public agencies, vendors, and decision records can be audited as risk-bearing dependencies with separate materiality channels, evidence gaps, monitoring triggers, rhetorical downgrades, and next actions.
The post-login Surface is becoming the live instrument: users should be able to add observations, source snippets, reviewer objections, and monitoring deltas to specific nodes while the system preserves provenance, freshness, review state, and the verification chain.
Atomic claims with support status, evidence links, verification state, disputes, retractions, and resolved forecast outcomes.
Evidence states distinguish provisional, source-assisted, source-grounded, contradicted, and missing-source material.
Candidate claims, evidence, and hardening tasks can be challenged, approved, rejected, or returned for source work.
Predictions carry probability distributions, reference-class context, red-team distribution sidecars, decisive unknowns, resolution criteria, Brier score, and calibration bins.
Trust capsules, append-only Surface events, role-specific record views, and node-level proof chains make the graph inspectable rather than decorative.
Brief PDFs, production packages, audit-trail exports, proof downloads, and enterprise data resources expose the same record spine.
Build Status
DAEPOLIS is launch-stage infrastructure. Some surfaces are live; others are deliberately staged because audit systems become credible by refusing to fake maturity.
Workbench intake, source packs, source-hardening states, claim verification, Brief Forensics, dependency intelligence, full-document ingestion integrity, Surface import/compilation, trust capsules, Surface events, role views, public ledger, prediction distributions, red-team sidecars, reference classes, decisive unknowns, calibration surface, outcome ledger, portfolio ingestion, proof paths, PDF exports, review queue, cohort access framing, and public methodology pages.
UI probability update history, richer node-level public proof chains, stronger automated source verification, more real-data/entity saturation, improved live monitoring surfaces, and CJI production-panel data coverage.
Autonomous lawful source collection, workstation readiness expansion, screen-aware DAEPOLIS context, globe/network workstation, enterprise workflow integrations, and organisation-scoped operating configurations.
Autumn 2026
The cohort tests real institutional decision records with source packs, claims, evidence, review workflow, exports, and ledger accountability. For access, contact daepolisanalysis@outlook.com.
Apply for cohort