Executive Summary

Everyone in nature-finance — results-based funds, insurers, registries, rating firms, governments, credit buyers — has to prove something about a forest before money moves. Today they prove it with satellite proxy data that sees the top of the canopy but not the carbon, the species, the degradation or the recovery. CeibaQ holds the missing layer: directly-measured Amazon ground truth — built once, and licensed to everyone who needs to underwrite nature.

CeibaQ (the first flagship product of AWAKEN) is the query layer for living ecosystems — a neutral, audit-grade integrity layer that sits upstream of the rent, not a rating agency, exchange or credit shop that depends on it.

The product — ROOT

ROOT is a calibrated reference "Datamode" (digital twin) of Amazon ecosystems: ~1,500–1,600 ecosystem parameters across all 36 SEEA-EA ecosystem services, built from direct measurement — eddy-covariance CO₂/flux, eDNA, bioacoustics and LiDAR — fused with 20 years of Peruvian government data. It is built once per ecosystem subtype on owned ground, then replicated across the basin by sampled drone overflight: measure once, infer many. The result is data that cannot be produced from space and is expensive and slow for anyone else to reproduce.

The model — measure once, bill per use

ROOT is built once at a fixed cost, then the same per-hectare record is billed every time someone uses it — pricing an insurance policy, releasing a results-based fund payout, attesting a credit or bond, filling a government ledger, calibrating a third-party node. The same bytes serve many payers at near-zero marginal cost on every sale after the first — Bloomberg/Verisk-style recurring-data economics on a dataset that improves as it scales.

How it makes money — five streams on one dataset, neutral layer first

The five revenue lines all run on the same ROOT dataset. The neutral data and services come first; own-credit issuance is deliberately ring-fenced behind an independent verification entity so the data layer stays trusted — you cannot be the referee and sell the ticket.

1. Monitoring-as-a-Service — per-hectare subscription + a share of clients' credits, for project developers (outside our own concessions).
2. Jurisdictional licence — per-hectare data licence to states/regions in regressive tiers (~$0.10 / $0.30 / $0.75), paid by donors / MDBs / results-based funds.
3. Data-only subscription — enterprise calibration seats / API ($30–250k), for insurers, registries and researchers — paid independently of any credit clearing.
4. Credit royalty — a ~2% fee on any ROOT-verified credit issued.
5. Own credits (ring-fenced) — carbon + biodiversity credits on the owned concession, issued through independent verifiers; the proof book that calibrates ROOT, not the headline.

The moat

A position that takes years and deep local trust to replicate: an owned ~90,000-ha reference concession; institutional convenios and MoUs across Peru (MINAM, SERNANP, SERFOR, GOREL, CCPIP); 20 years of government data accessed in-kind through a joint office; a science layer (TERI); and direct-measurement integrity. On the market map, CeibaQ sits in the near-empty quadrant — owns the ground · owns the intelligence · regulated instruments, no crypto — where remote-data vendors and origination-only players cannot reach.

Why now (in brief)

The integrity bar is rising exactly where proxy data fails: Verra VM0048 and Article 6.2 are tightening what counts as proof (first VM0048 credits are only now imminent, with ~40% supply haircuts and provisional Peru baselines emerging), while standing-forest / results-based finance (LEAF, TFFF, Article 6.2 offtake) pays for measured outcomes. Since the 2023 trust collapse, the bottleneck is measurement, not baselines — and that is what cannot be faked from space. (Full case: "Problem & Why Now".)

Financial shape (base case; model in Financials)

A J-curve: a fixed, largely non-dilutive investment in ROOT (~$10.7M CAPEX, designed for grant/MDB funding), then high operating leverage as one dataset is sold many ways at 70–85% gross margin on the data and SaaS streams.

• Base case reaches roughly $67M revenue by Year 5, EBITDA positive around Year 4 (~22% margin by Y5), on the approved five-stream model (1.5M owned / 10M serviced hectares).
• Downside — data + services only, slower methodology, no credit stacking — modelled explicitly at ~$20M Year 5, still high-margin: the floor an investor can underwrite.
• Stretch — basin-scale (5M owned / 50M serviced) — materially larger (~$290–330M), shown as gated upside, never as base.

Valued at a deliberately conservative 4× revenue (re-rated down from frothy multiples), the base case implies an exit on the order of ~$270M, with the data/SaaS streams able to earn higher multiples as they grow.

Status & ask (honest)

CeibaQ is pre-product and pre-revenue. In hand: the owned concession, the institutional convenios/MoUs, a submitted Singapore Article 6.2 Notice of Intent, the TERI science layer, and a complete financial and product model. To build: ROOT, on our own concession first. No commercial revenue contracts are signed yet — and the plan is built without assuming them.

We are raising a pre-seed of $600k on a SAFE ($4.5M post-money cap) to build a lean ROOT proof-of-concept, sign the first paying data customers, stand up the conflict-free legal structure, and file grant / Article-6.2 applications — de-risking toward a milestone-gated seed ($5–6M), with the ROOT science capex designed to be carried by non-dilutive grant/MDB capital. Because it enters earliest, the pre-seed is the cheapest equity in the staged plan.