# Anchored Horizon — capabilities

With Anchored Horizon, game developers and studios turn comparable-game evidence into distribution-first commercial belief—honest uncertainty, time-scoped horizons, scenarios they can challenge, and live updates as signals arrive—through BeliefSession, API, MCP, and A2A. This page catalogs what Iridae enables for forecasting.

## Plan against a distribution

Replaces comps decks and single-number forecasts with posterior predictive belief—bands, targets, hit chance, and evidence strength studios can defend.

### Predictive belief

- Posterior predictive draws (not a point estimate)
- Planning quantiles (p10–p90 and custom bands)
- Hit probability and P(revenue ≥ target)
- Log1p modeling with proper back-transform to currency
- FX normalization and deflation to a planning currency
- Named forecast profiles (12-month, 24-month, as-of, mixture tiers)
- Batch multi-title forecast runs
- BeliefSession question scope: outcome, horizon, and anchor
- Density and CDF views for distribution inspection
- Pins, planning bands, and scenario forks in-session

### Evidence strength

- ESS (Kish) from composite comp weights
- ESS-scaled prior width and power-prior discounting
- Explicit “unreliable when” gates (low ESS, sparse comps, missing embeddings)
- Prior vs features vs groups vs tail explanation
- Comp influence ranking on every forecast
- Lineage artifacts for audit and reproducibility

## Anchor in comparable games

Priors come from titles that are similar in game space—weighted, overridable, and explainable—not from a hand-picked deck.

### Comp retrieval & weighting

- Latent Spark similarity retrieval (asymmetric KL over Gaussian embeddings)
- Top-k comps with query fuzziness and diversity quotas
- Composite weights: similarity × recency × quality
- Regime-aware recency half-life for aging comps
- Multi-signal quality scores (reviews, CCU, rank, profile signals)
- Standalone modes when Latent Spark is not connected
- Comp-set stability index for analyst review

### Analyst control

- Include, exclude, and reweight comps before prior construction
- Explainable prior construction (comps inform priors only—no double-count)
- Feature-conditioned likelihood for the subject title
- Hierarchical hit-mixture model (base vs hit regimes)
- Constrained mixture parameterization to prevent label switching
- Forecast explain: what drove the outlook and how much

## Horizons, trajectories & time

Every forecast is a time-scoped belief—windowed horizons, live signal trajectories, and multi-horizon paths for planning—not a timeless spreadsheet cell.

### Horizon-native forecasting

- Horizon scopes: 12-month, 24-month, and custom month windows
- Anchors: launch, as-of date, and fiscal year end
- Scoped outcome keys per entity, horizon, and anchor
- Multi-horizon path forecasts for strategic pathway planning
- Path-horizon bundles (e.g. 3/6/12/24 or 6/12/24/36 months)
- Temporal training windows and rolling-origin backtests
- Regime-aware aging of comparable-game evidence

### Live trajectories

- Time-stamped signal ingest (wishlist, engagement, revenue)
- Trajectory features: slope, momentum, volatility, wishlist velocity
- Pre-launch and post-launch trajectory modes
- Signal panels that keep features current as the market moves
- Observation scoring against frozen forecast runs over time
- Cohort calibration drift checks across time windows

## Scenarios & inverse planning

Lets studios ask “what if,” solve for the input that hits a plan target, and keep causal honesty when analysts move the knobs.

### Counterfactuals & compare

- Feature-override scenarios that re-forecast under new assumptions
- Ghost forks and side-by-side scenario compare
- Net-revenue waterfalls (platform, publisher, deductions) on draws
- Causal role labeling (intervention, mediator, conditioning, collider)
- Non-blocking causal validation on scenario draws

### Solve for the decision

- Inverse constraint solve (exceedance, median, or quantile targets)
- Wishlist- and pin-style solves (“what must be true for 75% chance of ≥ $X”)
- Scenario inverse APIs for agents and UI
- Planning pins that stay attached as belief updates
- Exportable scenario packs for finance and leadership reviews

## Calibration, surprise & lifecycle

Keeps forecasts decision-grade after they leave the lab—promotion gates, surprise scoring, and governed refit.

### Trust & calibration

- Rolling-origin CRPS, log score, coverage, and PIT diagnostics
- Per-horizon calibration segments
- Candidate → active model promotion with statistical gates
- R-hat / ESS / coverage thresholds before release
- Rollback to prior active models
- Diagnostickit promotion gates for safe operation

### When reality lands

- Score realized outcomes against a frozen forecast_run_id
- Calibration vs structural surprise classification
- No silent prior override when observations arrive
- Post-forecast drift detection
- Auto-refit policy with cooldown and caps
- Sensitivity and upside/downside partition explainers

## Portfolio, OIE & platform

Title-level belief joins portfolio risk and the Iridae loop—or runs stand-alone when peers are not connected.

### Portfolio & peers

- Joint portfolio draws across titles
- Independent or Gaussian-copula correlation assumptions
- VaR-style portfolio risk summaries
- Subtle Beacon experiment-posterior ingest (promotion-gated)
- Patient Cartographer tactic distributions and path-horizon payloads
- Latent Spark comp retrieval and structural-surprise notify
- Fail-soft mesh when peers are unavailable (wider, weaker priors)

### Surfaces & governance

- Headless capability API (AgenticKit-only public surface)
- OpenAPI, MCP, and A2A projections
- BeliefSession for analysts; agents under the same contracts
- Tenant isolation and role-based access (analyst / operator / admin)
- Lineage chain for forecast runs and promotions
- Optional commerce metering and customer-success hooks
- Hosted multi-tenant SaaS

## Site map

- [Home](https://iridae.com/) — Iridae decision infrastructure for game studios

### [Latent Spark — Understand](https://iridae.com/understand/)

Calibrated game belief, comps, and market atlas

- [Overview](https://iridae.com/understand/)
- [Headless + Integrated](https://iridae.com/understand/headless/)
- [Capabilities](https://iridae.com/understand/capabilities/)
- [FAQ](https://iridae.com/understand/faq/)

### [Anchored Horizon — Forecast](https://iridae.com/forecast/)

Comp-based Bayesian commercial forecasting

- [Overview](https://iridae.com/forecast/)
- [Headless + Integrated](https://iridae.com/forecast/headless/)
- **Capabilities** (this page)
- [FAQ](https://iridae.com/forecast/faq/)

### [Patient Cartographer — Plan](https://iridae.com/plan/)

Live strategic pathfinding under uncertainty

- [Overview](https://iridae.com/plan/)
- [Portfolio](https://iridae.com/plan/portfolio/)
- [Capabilities](https://iridae.com/plan/capabilities/)
- [FAQ](https://iridae.com/plan/faq/)

### [Subtle Beacon — Learn](https://iridae.com/learn/)

Continuous Bayesian experimentation

- [Overview](https://iridae.com/learn/)
- [Capabilities](https://iridae.com/learn/capabilities/)
- [FAQ](https://iridae.com/learn/faq/)

### Also

- [Book a Demo](https://iridae.com/demo/)
- [Company](https://iridae.com/company/)
- [Careers](https://iridae.com/company/careers/)
- [Blog](https://iridae.com/blog/)
- [Legal](https://iridae.com/legal/)

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