Quantum Structures
Revenue Optimization · Agentic AI

Stop the leaks.
Win back the revenue you’re owed.

Quantum Structures builds agentic AI systems that protect forward revenue and recover backward revenue for retail, CPG, and financial services enterprises — turning policy fluency, fine‑tuned models, and orchestrated agents into measurable dollars on the P&L.

Talk to us See what we build
1–3%
of revenue typically leaks through unclaimed reimbursements, chargebacks & fee errors
40–60%
of eligible recoveries go unfiled because manual workflows can’t keep pace
14–30 days
earlier we detect threshold breaches that lead to suspensions or compliance failure
100–1000×
cheaper per inference using fine‑tuned NER for high‑volume entity extraction vs. frontier LLMs alone

Two pillars. One revenue engine.

Most enterprises lose money in two directions their dashboards aren’t built to fix — forward, through suspensions, claim denials, and metric collapse; and backward, through unclaimed reimbursements, chargebacks, and counterparty errors. We build agentic systems that defend the first and recover the second on a single data spine.

Pillar 1 · Defense

Compliance & Performance Watchtower

Continuous, predictive monitoring of the metrics, policies, and counterparty rules that gate your revenue. We catch threshold breaches and policy drift weeks early, draft structured corrective actions, and pre-flag at-risk SKUs, listings, accounts, or transactions before enforcement lands.

Predictive metric monitoring Policy-diff knowledge base Auto-drafted plans of action Risk sentinels (IP, sourcing, fraud) Claim & dispute defenders
Pillar 2 · Recovery

Continuous Recovery Engine

Always-on reconciliation across ledgers, fee reports, settlement files, and dispute windows. Our agents identify every dollar your counterparties owe you, assemble the evidence package, and file claims inside narrow windows — at SMB price points, with enterprise rigor.

Reimbursement recovery Chargeback NER & root-cause Cost-basis auditing Return & refund disputes Defect-cost ledger

Built for the verticals where revenue leaks compound.

Different industries, same shape of problem — structured counterparty rules, narrow dispute windows, and high-volume text that legacy ops teams can’t economically read at scale. Our agentic stack is purpose-built for exactly that surface.

Retail & CPG

Marketplace & trade-spend revenue protection

  • Account-health and listing-integrity defense across Amazon, Walmart, Shopify and 1P vendor portals
  • FBA / WFS reimbursement recovery on lost, damaged, mis-returned, and mis-fee‑d inventory
  • Vendor chargeback NER & root-cause classification (ASN, In-Full Delivery, GTIN-14, packaging)
  • Inauthenticity and sourcing-documentation risk sentinels
  • Trade-promotion and deduction recovery for CPG brands across retailer portals
Financial Services

Dispute, claim & revenue-leakage automation

  • Card-network chargeback parsing, evidence assembly, and representment at scale
  • Continuous fee, interchange, and processor-statement reconciliation
  • Insurance claim defense and subrogation recovery workflows
  • Regulatory and compliance policy-diff monitoring with seller / issuer impact analysis
  • Counterparty SLA enforcement and revenue-assurance auditing

How we build: an agentic stack tuned for revenue.

Generic LLM chatbots are uneconomic at the per-transaction volumes revenue operations actually run on. We layer specialized models where precision and cost matter, and reserve frontier reasoning for the moments judgment matters most.

Layer 1

Ingestion spine

Direct connectors to marketplace, ERP, processor, and ledger APIs — one normalized event stream.

Layer 2

Fine‑tuned NER & classifiers

BERT-class models extract entities from chargebacks, disputes, and notifications at 100–1000× LLM economics.

Layer 3

Frontier LLM reasoning

Used surgically — ambiguous-case judgment, evidence-grounded narratives, structured plans of action.

Layer 4

Policy-diff knowledge index

Versioned, dated record of every counterparty policy change, tagged to affected SKUs, accounts, or transactions.

Insider fluency, software economics.

Our team has spent years on the inside of the largest marketplaces and trust & safety organizations — shipping the exact NER architectures, evidence frameworks, and policy systems we now bring to your revenue stack. We pair that fluency with software unit economics so the work scales below the price point a services firm can profitably serve.

  • Two pillars on one data spine. Defense and Recovery share ingestion, models, and policy knowledge — structurally lower cost than stitching point tools together.
  • Outcome-labeled feedback. Every recovered dollar and every prevented enforcement event becomes a label that compounds model quality.
  • Specialized models where they belong. Frontier LLMs for reasoning; fine-tuned NER for high-volume parsing; classical classifiers for routing.
  • Evidence trails by default. Every alert, claim, and action ships with citation and policy basis — audit-ready from day one.
  • Self-funding ROI. A single recovery audit typically pays for the platform; ongoing prevention is upside.

Find out what your business is leaving on the table.

Send us a note — we’ll walk you through a recovery and defense assessment tailored to your stack.

Contact us