The a2vm Framework
The a2vm framework is founded on a simple yet powerful thesis: we can codify the expert reasoning of the best human appraisers into a collaborative network of specialized AI models, while simultaneously overcoming human limitations through scale, consistency, and deep data analysis. Our system doesn't seek to replace the appraiser but to amplify their expertise, ensuring every valuation is backed by a fortress of data and a clear, logical narrative. The full whitepaper describes a three-layer architecture that combines multi-modal data ingestion, a Mixture‑of‑Experts valuation core with agentic tool-calls, and compliance-focused governance with human-in-the-loop gates. Below is an executive summary and an example sanitized workfile you can download for review.
Executive summary
- Layer 1 — Appraisal Data Fabric: multi-modal ingestion (photos, MLS, GIS, inspections) normalized into a feature store and universal encoder.
- Layer 2 — Valuation Intelligence: a gating router activates a sparse Mixture‑of‑Experts (comparables, valuation models, condition adjustment, market dynamics, risk/bias checks). Experts can make agentic tool-calls (MLS, regulatory APIs) to fetch evidence in real time.
- Layer 3 — Compliance & HITL: automated QC, explainability experts producing structured, immutable workfiles, and human gates (Comp Selection Gate & Final Validation Gate) for low-confidence or high-value cases.
- Continuous learning: human approvals and overrides feed a Golden Dataset used to periodically retrain and fine-tune experts and routing logic.
View a sanitized sample workfile
We provide a small, sanitized JSON example that demonstrates the structure of the audit-ready workfile and the kind of expert activations, tool-calls, and QC checks captured for each assignment.
Request the full whitepaper (PDF)
For full access to the technical appendix, diagrams, and compliance attestations, request the PDF and we will follow up with a secure download link and optional technical review.
Request full whitepaper & technical review