Force-multipliers and gap-fillers for the TroveSnap pipeline — beyond what's already planned. Each idea is tagged for how it fits the candidate-first, deterministic-first, cost-controlled architecture. Brainstorm, 2026-06-17.
Ideas are arranged along the existing pipeline: external source → candidate → review → canonical → publish → demand → disposition.
Highest leverage against the core pain, the candidate layer, and the competitive wedge.
★ Voice cataloging
Hands-free intake during the walkthrough — the single biggest attack on the 14–19 min/lot pain.
★ Cross-run dedupe
Makes the whole candidate layer trustworthy at scale; links reappearing items instead of cloning.
★ PII / privacy scrubber
Turns a competitor's CCPA weakness into TroveSnap's headline trust feature.
Channel-export adapters are the highest value but gate on Auth + connectors — a phase-2 bet.
Get items in faster and richer, before the form ever appears.
Photographer speaks "oak dresser, 1960s, ask $120"; transcription pre-fills candidate fields paired to the photo. Hands-free.
Walk a room on video; sample frames, detect distinct objects, emit candidates. One pass catalogs a whole room.
A shelf photo becomes N draft items via segmentation; the inverse recommends grouping low-value items into one sellable lot.
Photograph receipts, COAs, appraisal letters → attached as evidence to the item, boosting trust/value and feeding the appraiser.
Reduce review noise and speed throughput without ever bypassing the promotion contract.
Perceptual hash + embeddings detect the same item reappearing (relisted, or duplicated across connectors) and link instead of cloning.
Seller rule: high-confidence, low-value, clearly-identified items auto-promote; uncertain or high-value always hold. A policy over promoteInventoryCandidate(), not a bypass — auditable.
The queue learns each seller's repeated edits (always recategorizes "misc") and pre-fills/reorders accordingly. Enrichment that compounds.
Make guidance trustworthy and self-improving.
Pricing guidance shows the actual sold comps behind the range with recency/condition adjustments, so sellers trust it.
Reconciled sold prices calibrate future guidance per category/region. Guidance → sale → reconciliation → better guidance — the learning flywheel.
Flags likely reproductions in high-value categories to trigger closer appraisal. Risk reduction for client estates.
Turn the Kanban into an operations tool.
Time-in-stage, bottleneck detection ("40 items stuck in Needs Appraisal 3 days"), per-cataloger throughput.
Assign review / appraisal / reshoot work to teammates (device tokens already exist). Multi-user cataloging.
Surface each item's full lineage — photo → run → connector → edits → promotion — already tracked via promoted_record_id. Trust + compliance artifact.
Project the canonical record outward as drafts — never auto-posted.
Per-target export profiles for the feeds estate sellers use — LiveAuctioneers, Proxibid, Invaluable, Auction Flex/HiBid, Wavebid — each with its own template + lot-numbered image bundle, plus sale-results pull-back. See the integration spec.
Per-channel resale listing payloads (eBay item specifics, FB fields, Shopify) from the canonical record — drafts, candidate-style. Makes the reseller promise shippable.
Print price tags / QR item labels (QR → buyer item page + door code) and a printable catalog from the same records. Connects the sale floor to the pipeline.
Make safety a headline feature where incumbents are exposed.
Auto-detect faces, addressed mail, documents with SSNs, people in reflections → flag/blur before anything publishes. Directly targets the EstateSales.net interior-photo / CCPA complaint we found, and reinforces "nothing publishes without approval."
promoteInventoryCandidate().