The Sea of Green Exchange Model
How verified sales data, inventory performance scoring and on-chain liquidity combine into a credit market for the cannabis supply chain.
Working draft with live models. Every figure in the models is an adjustable example, not a forecast. Features marked planned are not yet built. This is not legal, tax or investment advice, and not an offer of any security or financial product. Tokenized, yield-bearing positions that can be resold need securities review, and the tax treatment needs qualified counsel.
Executive summary
Sea of Green merges verified sales data, inventory performance modeling and on-chain liquidity to build a credit market for the cannabis supply chain.
At its foundation are three analytics models developed by Trees N Clouds Technologies: the Decay Risk Index (DRI), the Share of Decision Influence (SDI) and the Shelf Efficiency Index (SEI). Together they turn retail and ERP data into a measurable view of which inventory converts to cash, which is what a lender needs to price an advance against it.
Industry context
Cannabis retail is one of the most fragmented, liquidity-constrained markets in commerce. Retailers are often short of capital and carrying slow inventory, while most banks and conventional lenders won't serve the industry at all.
Sea of Green prices credit from verified point-of-sale data, so financing follows real performance. The sale of the goods becomes the source of repayment.
How capital and product move
The financier stays a secured creditor. Product moves only through licensed parties, so there are two licensed transfers and no extra sale. Market makers fund positions that pay brands on day 0; retail buying groups pay a discounted price as product sells.
One $100k position
Unit economics of a position
Illustrative exampleThe brand discount creates the margin. The exchange, the market maker and the retailer each take a share. Retailers pay within 30 days, some in 15, and only for products that have sold. Every input is adjustable.
- $115,000
- Product received at list value
- $110,000
- Retailer pays by day 30, for products sold
- $105,000
- Back to the market maker by then
- 6.0%
- Yield per cycle: 5.0% spread plus 1.0% pool fee. About 73% a year if repeated
Where the margin goes
| Party | Gets | Amount | % of position |
|---|---|---|---|
| Brand | Cash on day 0 | $100,000 | 100% |
| Exchange | Exchange spread | $5,000 | 5.0% |
| Market maker | Yield on the position | $5,000 | 5.0% |
| Market maker (LP) | 1% pool fee on trading volume | $1,000 | 1.0% |
| Retailer | Discount off list value | $5,000 | 5.0% |
| Margin created | List value less cash paid | $15,000 | 15.0% |
| Per product | Position size per product | $12,500 | |
| Still outstanding | Capital on products not yet sold | $0 | 0% |
Split and sell a position
Illustrative exampleThe market maker can sell part of a position, with a share of its yield, to short-term lenders. That frees capital and cuts the amount at risk.
- $40,000
- Capital freed by the sale
- $60,000
- Capital still at risk
- $3,600
- Market maker yield per cycle
- $2,400
- Buyer yield per cycle
30 of 50 pieces kept, $2,000 each
Filled pieces are kept. Outlined pieces are sold.
| Capital in | Yield per cycle | Return per cycle | |
|---|---|---|---|
| Market maker | $60,000 | $3,600 | 6.0% |
| Short-term lenders | $40,000 | $2,400 | 6.0% |
At 100% the buyer gets the full pro-rata share of the market maker's yield on the slice. Lower it to keep part of that yield as a fee.
Retailer tax effect
Illustrative exampleThe retailer pays the exchange and market maker spread inside the price. A separately stated fee is not deductible under §280E. A fee embedded in the price is part of cost of goods sold, if it holds up as a real purchase price.
Who 280E reaches
| Party | 280E | Why |
|---|---|---|
| Market maker and SPV | Not reached | Provides capital, no trafficking, ordinary deductions |
| Exchange | Not reached | Platform with no cannabis licences; counsel to confirm |
| Brand, distributor, retailer | Reached | Only COGS is deductible, so the spread sits in COGS |
Retailer after-tax cost of the spread
| Spread stated separately | Embedded in price | |
|---|---|---|
| Cash paid to the brand | $100,000 | $100,000 |
| Exchange and market maker spread | $10,000 | in price |
| Total paid by retailer | $110,000 | $110,000 |
| Deductible as COGS | $100,000 | $110,000 |
| Spread deductible? | No | Yes, as COGS |
| Tax on the spread amount | $2,100 | $0 |
| After-tax cost of the spread | $10,000 | $7,900 |
| Retailer tax saved | – | $2,100 |
Per position, federal only, same financier yield in both cases. This lowers 280E exposure for licensed operators; it does not remove it. It depends on arm's-length pricing and documentation. Counsel and a CPA need to confirm.
Compounding over 24 months
Illustrative exampleEach cycle the market maker and the lenders earn their yield. With reinvesting on, that yield joins the position, so the position grows and so does the volume the exchange, brand and retailer see. Lines show each player's cumulative gain.
- Exchange
- Market maker
- Retail buying group
- Brand
- Short-term lenders
| Player | Puts in | First cycle | 24 months | From compounding |
|---|---|---|---|---|
| Exchange | Spread on all volume | $5,000 | $254,078 | +$134,078 |
| Market maker | Capital kept at risk $60,000 | $3,600 | $182,936 | +$96,536 |
| Retail buying group | Discount and tax saving | $7,100 | $360,791 | +$190,391 |
| Brand | Paid on day 0 | $4,716 | $239,634 | +$126,456 |
| Short-term lenders | Pieces bought $40,000 | $2,400 | $121,957 | +$64,357 |
24 cycles of 30 days. The position grows from $100,000 to $404,893 when reinvested. Gain is earnings only; starting capital isn't counted. Brand and retailer figures rest on the assumptions at right.
Uses the position, split and tax settings above. Exchange, brand and retailer earnings scale with the size of the position.
Pool design: Uniswap v2 and v3, forked for credit
A v3 position picks a price range. A Sea of Green position picks which products and retailers it funds. The position mechanics carry over; the economics are credit.
| Uniswap | Sea of Green |
|---|---|
| 1% fee tier | Pool fee on trading volume, earned by LP positions as a second revenue source |
| Swap fee | Exchange spread and market maker spread paid in the retailer's price |
| v3 price range | Scope of the position: which brands, retailers and tenor it funds |
| v3 position NFT | A market maker's position, wrappable into pieces |
| v2 LP token | Fungible share of a whole pool |
| Impermanent loss | Credit loss if a retailer does not pay |
| Swap | Pay the brand, collect from the retailer, repeat |
Pool pairs and the on-chain claim on the receivable are still open design questions.
The three indices
Decay Risk Index
Quantifies time-based financial risk in inventory.
DRI = w1·TV + w2·DS + w3·DA + w4·MP + w5·RL
- TV
- Time-on-shelf velocity delta: the rate at which sales decay over time
- DS
- Days since stocked
- DA
- Discount activation: pressure to move product through markdowns
- MP
- Margin pressure ratio, (cost − sale price) ÷ cost
- RL
- Reorder likelihood from historic performance
A high DRI signals overstocking or falling sales velocity. A low DRI means efficient turnover and little capital decay.
Share of Decision Influence
Captures a product's influence on buying behavior beyond its own sales.
SDI = (w1·PV + w2·CV + w3·AV + w4·IC) ÷ Σ SDI
- PV
- Product views: menu or in-store exposure
- CV
- Comparison behavior: evaluations against adjacent items
- AV
- Anchor value delta: price deviation from the category average
- IC
- Influence conversion: how often the product triggers additional purchases
SDI surfaces products that steer customer behavior and lift the whole store, even when they aren't sales leaders themselves.
Shelf Efficiency Index
Normalizes influence against decay to show capital efficiency.
SEI = SDI ÷ DRI
- > 1.0
- High-value, low-risk inventory
- ≈ 1.0
- Balanced performers
- < 0.5
- Risk-heavy, low-influence inventory: capital tied up in product that isn't moving
SEI is the score that sets eligibility and pricing for financing.
| Example SKU | SDI | DRI | SEI |
|---|---|---|---|
| Premium cartridge A | 0.92 | 45 | 2.04 |
| High-end tincture | 0.95 | 50 | 1.90 |
| Edible C | 0.68 | 40 | 1.70 |
| Rare SKU X | 0.80 | 90 | 0.89 |
| Flower pack B | 0.30 | 50 | 0.60 |
Inventory quadrants
Plotting SDI against DRI sorts inventory into four groups that drive financing eligibility.
| Quadrant | Type | Risk | Action |
|---|---|---|---|
| High SDI / Low DRI | Shelf heroes | Low | Prioritize for promotion and bundling |
| High SDI / High DRI | Flashy but risky | Medium | Promote selectively, avoid overstocking |
| Low SDI / Low DRI | Stable fillers | Low | Keep minimal stock for niche demand |
| Low SDI / High DRI | Shelf drag | High | Liquidate or return to supplier |
Data integrations
- ERP and distribution
- Nabis, Canix, Distru, Acumatica, LeafLink, LeafTrade
- Point of sale
- Dutchie, Treez, BLAZE, Meadow, WebJoint
- CRM
- HubSpot
The same scores power retailer dashboards, restocking recommendations and the risk controls that decide which receivables a pool may fund.
Planned safeguards
These are design goals. None is live yet, and each will be documented and audited before any pool opens.
- Repayment driven by live POS data
- Reserve buffers held in each pool
- Oracles that publish DRI, SDI and SEI on-chain
- Circuit breakers for systemic risk
- Participant verification and access controls
- Multisig and timelock control of admin functions
Governance
- A risk committee validates changes to the scoring models.
- Independent auditors review every smart contract release.
- Protocol changes follow a published process with time for review before they take effect.
Contact
611 Wilshire Blvd, Suite 900 #1188
Los Angeles, CA 90017
info@treesnclouds.com
Questions about participating? Pre-register and we'll be in touch.