> ## Documentation Index
> Fetch the complete documentation index at: https://docs.seednode.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Technical Architecture

> Data indexing, scoring engine, LLM interpretation, on-chain credentials

## 3.1 Data Indexing Layer

Built on existing infrastructure — Covalent / GoldRush, Moralis, Alchemy, The Graph, Dune Analytics — to fetch address-level public data across chains (balances, transactions, protocol interactions, NFTs, staking and lending records). V1 prioritizes Ethereum, Base, and Solana, the highest-density chains. No custom indexer — keeping early engineering and ops cost minimal.

## 3.2 Scoring Engine: Rules + Lightweight ML

**Transparent weighted rules:** wallet age, transaction breadth and depth, protocol diversity, staking and liquidity history, asset distribution — users can see exactly why they got their score. No black box.

**Lightweight machine learning:** small models (XGBoost / LightGBM) for anomaly detection — catching score farming, sybil attacks, and bot clusters that rule-based scoring alone can be gamed around. Training and inference need no GPU; an ordinary cloud server suffices. This is where "AI" earns its place rather than being a label.

## 3.3 Optional LLM Interpretation Layer

Off-the-shelf large language models via API (not self-hosted, not self-trained) turn scores into plain-language readings — e.g., "You're a long-term active DeFi participant who favors conservative lending and rarely touches speculative tokens." Pay-per-call, low marginal cost, swappable for cheaper open-source models at any time.

## 3.4 On-Chain Credentials & Validators: An Honest Trust Assumption

Rings are issued as soulbound tokens / verifiable credentials, written to the user's address — non-transferable, non-sellable.

In V1, scores are co-signed and anchored by a small set of publicly identified, reputationally accountable signers (initially the team itself, later 1–2 trusted partners). We state the current trust assumption plainly — no pretending to be "fully decentralized" — and expand toward a stake-based validator network on the roadmap. We deliberately do not use an "anyone can run a node" model (see [Appendix A](https://docs.seednode.ai/appendix-a.md)).

## 3.5 Cost Structure (V1 Estimate)

Total V1 operating cost stays in the hundreds of dollars per month — the core hypothesis can be validated without external funding.

| Module | Stack | Cost Level |
| - | - | - |
| On-chain data indexing | Covalent / Moralis / Alchemy / The Graph APIs | Usage-based; free tiers cover the MVP |
| Scoring engine | XGBoost / LightGBM on an ordinary cloud server | Tens to hundreds of USD per month |
| LLM interpretation | Pay-per-call third-party APIs; open-source optional | Usage-based, low marginal cost |
| Credential issuance | Low-gas L2 (Base / Arbitrum) | Cents per issuance |
| Validator signing | Team-held keys in V1 | 0 |


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.