Direct energy forecasts on generation capacity, demand, infrastructure events, climate-fund allocation. The founding vertical of Phronesis. Customer class: capital allocators in energy infrastructure, utility and grid operators, energy-sector corporate strategy, climate-aligned funds.
Archetypes
- E1 Generation capacity additions by region and technology, multi-year horizon
- E2 Locational marginal price (LMP) trajectories under capacity scenarios
- E3 Interconnection queue throughput and project-completion probability
- E4 Critical-minerals supply chain availability for energy-storage build
- E5 FERC ruling and state PUC docket outcome probabilities
Co-primary vertical with Energy. Forecasts on AI compute power demand, data center electrification, GPU and HBM production, hyperscaler capex, training run trajectories. Cross-vertical Phronesis Grid-Compute Forecast is the flagship intersection product. Customer class: data center operators, hyperscaler infrastructure, utility forecasting desks needing compute-side demand, semiconductor analysts, AI-infrastructure-focused capital allocators.
Archetypes
- I1 Phronesis Grid-Compute Forecast — cross-vertical AI-compute power demand × grid-capacity intersection (FLAGSHIP)
- I2 GPU + HBM production capacity vs hyperscaler capex demand
- I3 Inference cost trajectory by model class and provider
- I4 Data center build cadence by region and power-availability profile
- C1 AI training run trajectory (cluster size, model scale, time-to-first-token)
Disease incidence, population-health, public-health system forecasts. Operates exclusively under HIPAA Safe Harbor enforcement at the code layer. PHI is architecturally excluded from the inference path. Customer class: payers and providers, public-health agencies, pharmaceutical demand forecasting, clinical-trial site planning.
Archetypes
- H1 US disease incidence per 100k by demographic and region (e.g., Type 2 diabetes; first H-archetype minted)
- H2 Population-health metric trajectories (life expectancy, age-adjusted mortality)
- H3 Health system capacity by service line and region
- H4 Public-health intervention effect estimates
- H5–H8 Additional H-archetypes in pre-launch substrate
Physical-risk forecasts: hurricane and wildfire frequency, sea-level-rise impact zones, extreme-weather probability, asset-level exposure modeling. Customer class: insurance and reinsurance underwriting, commercial real estate diligence, climate-disclosure funds, infrastructure resilience planning.
Regulatory environment forecasts: legislation passage probability, agency rulemaking timing, jurisdictional outcome variability. Cross-cutting regulatory rule set at the architecture level. Customer class: lobbyists and trade groups, corporate government-affairs, regulators themselves, compliance-aware capital allocators.
Supply-chain resilience forecasts: critical-minerals availability, logistics throughput, manufacturing-supply-chain disruption probability, commodity flow scenarios. Customer class: logistics operators, commodity traders, manufacturing supply-chain teams, critical-minerals investment funds.
Space-economy forecasts: launch cadence, IPO probability, orbital-debris density, mission-budget trajectories, commercial-space-station deployment, lunar infrastructure timing, space-based solar power feasibility. The rule set enforces ITAR/EAR, national-security-payload, crewed-mission and insurance-grade actuarial hard lines. Customer class: space-economy capital allocators, commercial-space companies, defense-aerospace investors, regulatory observers.
Archetypes
- C1 SpaceX IPO probability by Q4 2027 (52% canonical p50; first C-archetype minted)
- C2 Commercial launch cadence by provider and orbit class
- C3 Orbital infrastructure deployment cadence
- S1–S6 Additional S-archetypes in pre-launch (orbital debris density, STM, mission-budget, etc.)
Humanoid and autonomous-system deployment cadence forecasts. Universal cross-pollinator vertical: intersects with V#1 (energy infrastructure robotics), V#2 (compute substrate for robotics), V#7 (space robotics). Archetype weighting favors digital-interface forecasts (sensors, actuators, software stack maturation) over full-stack autonomy timing. Customer class: industrial robotics buyers, humanoid-platform investors, automation supply-chain analysts, defense-robotics observers.
Archetypes
- R1 Humanoid robot industry deployment cadence by region and customer-segment (first R-archetype minted)
- R2 Industrial robotics market sizing by sector
- R3 Autonomous vehicle deployment timing by jurisdiction
- R4–R6 Cross-vertical I_V2×V8 + I_V7×V8 archetypes
AGI capability arrival forecasts, alignment-research milestone substrate, AI-safety regulatory cadence per jurisdiction, compute-capability economics, recursive self-improvement substrate-evidence, multi-AI ensemble emergent capabilities. Cross-vertical V#9 × V#2 (capability × grid + compute availability) substrate-aligned. Customer class: frontier AI lab compliance + GC functions, regulated-entity AI deployment teams, AI-investing capital allocators, cross-border AI governance bodies.
Archetypes
- AGI-T AGI capability-class arrival with p10/p50/p90 confidence band
- CAP-D Capability-delta substrate-evidence (benchmark + parameter-scale + training-compute attestation)
- ALIGN-M Alignment-research milestone (paper + lab + reproducibility citation)
- REG-C AI-safety regulatory cadence per specific jurisdiction
- COMP-E Compute-capability economics arithmetic (training-compute × parameter-count × capability × cost)
AI-accelerated materials discovery cadence, physics experimentation cadence per lab and per funding class, battery chemistry breakthroughs, superconductor discovery timelines, advanced manufacturing substrate transitions. Cross-vertical V#10 × V#12 quantum-chemistry-simulation accuracy substrate. Customer class: materials investors, national-lab program managers, advanced manufacturing capital allocators.
Archetypes
- AI-MAT AI-accelerated materials discovery cadence forecast
- PHY-X Physics experimentation cadence (per-lab × per-funding-class)
- BAT-B Battery chemistry breakthrough timeline forecast
- SUP-D Superconductor discovery timeline forecast
- MFG-S Advanced manufacturing substrate transition forecast
Lifespan extension trajectories, biomarker clock validation (Horvath / GrimAge / phenotypic-age / proteomic / metabolomic), geroscience trial outcomes (rapamycin / metformin / senolytic / parabiosis), longevity therapy pipeline progression, cellular rejuvenation substrate (Yamanaka factor reprogramming + epigenetic age reversal). Cross-vertical V#11 × V#3 aging-cascade healthcare substrate. HIPAA-adjacent intake discipline (population-aggregate / de-identified only; PHI never persisted). Customer class: longevity / biotech capital allocators, biopharma demand forecasting.
Archetypes
- LIFE-X Lifespan extension trajectory (population-level + biomarker-anchored sub-populations)
- BIO-C Biomarker clock validation (per-clock validation cadence)
- GERO-T Geroscience trial outcome (per-trial reproducibility substrate)
- LONG-P Longevity therapy pipeline progression (per-mechanism × per-stage)
- CELL-R Cellular rejuvenation substrate (Yamanaka + epigenetic age reversal)
Quantum supremacy / quantum advantage milestones, qubit scaling trajectories per technology (superconducting / trapped-ion / neutral-atom / photonic / topological), post-quantum cryptography migration (NIST PQC FIPS 203/204/205 + jurisdiction migration deadline 2030), quantum chemistry simulation accuracy. Canonical attestation accepts US-and-allied quantum vendors (an allowlist). Cross-vertical V#12 × V#10 quantum-chemistry-simulation + V#12 × V#5 PQC regulatory cadence + V#12 × V#2 PQC × data-center cryptographic migration. Customer class: quantum computing investors, hyperscaler tenants, cross-border crypto-governance bodies, insurance underwriters.
Archetypes
- Q-SUP Quantum supremacy / quantum advantage milestone
- Q-SCALE Qubit scaling trajectory (per-vendor × per-technology)
- PQC-MIG Post-quantum cryptography migration (NIST FIPS 203/204/205 + jurisdiction migration deadline)
- Q-CHEM Quantum chemistry simulation accuracy (cross-product V#12 × V#10 flagship)
- Q-VEND Quantum vendor canonical attestation (US-and-allied allowlist).
Any consequential decision in any domain. The caller brings the proposed action, a frozen resolution rule and a resolution source — a public, dated source the engine can read, or the principal's or the counterparty's attested outcome. Phronesis captures the decision before the outcome, anchors it, resolves it under the rule and scores it; the resolution's evidence class is shown on the record, and only source-resolved outcomes feed calibration. No Phronesis forecast is supplied: the record, not the forecast, is the product. Customer class: any agent or enterprise acting on a mandate — operators of purchasing, booking, procurement or contracting agents.