Go Green Chain

App Flow
Components
Landing Page
Loan List Overview
AI Extraction Modal
Loan Dashboard
Evidence Upload Drawer
On-chain Timeline

🌱 Inspiration

If you're going to price sustainability, measure it properly.

ESG-linked loans need KPIs and performance data, but ESG reporting is fragmented, unverifiable, and hard to compare across loans.

⚙️ What it does

AI to understand the loan
AI to evaluate ESG performance
Blockchain to verify and trust the ESG data

🛠️ Features

1. AI-Powered ESG Extraction

GreenLedger reads sustainability-linked loan agreements and automatically extracts the key ESG metrics hiding inside them. Emission targets, renewable requirements, diversity metrics, and margin ratchets are converted from dense PDF clauses into clean, structured KPIs. This eliminates hours of manual reading and ensures consistent interpretation across teams.

2. KPI Dashboard with Real-Time Performance

Each loan receives a living dashboard:
Current KPI values
Target trajectories
Trendlines
AI confidence scores
On-chain verification badges It becomes a single pane of truth shared between lenders, borrowers, auditors, and regulators.

3. Evidence Upload & AI Validation

Borrowers upload ESG evidence, emissions reports, meter data, attestation letters. AI automatically:

Matches files to the correct KPI
Extracts relevant numbers
Flags anomalies or unit mismatches

Assigns a confidence score This shrinks verification workflows from days to minutes.

4. Immutable On-Chain Verification Timeline

Each evidence submission and verification event is hashed and timestamped on a blockchain. This creates:

A tamper-proof audit trail
Clear provenance for regulators
Zero room for greenwashing or backdated changes

The system doesn’t store private data on-chain, only transparent proofs.

5. Smart Contract Margin Simulator

Bankers can model margin adjustments in real time:

KPI met → margin decreases

KPI missed → margin increases

Partial performance → blended outcomes It lets lenders evaluate pricing risk instantly and borrowers understand the financial impact of their climate performance.

6. Portfolio-Level Insights

View all loans together through the lens of:

ESG verification depth
AI-predicted risk of target failure
Performance trends across time It helps institutions quantify ESG exposure across thousands of loans at once.

🎯 Target Users

1. Banks & Lending Institutions

They use GreenLedger to make ESG-linked loans more transparent, faster to monitor, and lower-risk. It reduces operational workload, improves compliance, and strengthens pricing integrity.

2. Corporate Borrowers

Borrowers gain a single, elegant system to:

Upload evidence
Track their ESG progress
Demonstrate credibility
Qualify for margin reductions faster It removes friction between sustainability teams and finance teams.

3. Auditors & Third-Party Verifiers

Auditors need reliable, consistent documentation. GreenLedger provides structured evidence, AI-supported tagging, and a blockchain-backed audit trail.

4. Regulators & Reporting Bodies

They benefit from standardized, comparable, verified ESG metrics rather than disconnected spreadsheets and PDF disclosures.

5. Investors & ESG Analysts

Portfolio insights give them a high-level understanding of performance risk, credibility, and sustainability impact.

🤖 Gemini Integration

We use Gemini 3 as the core intelligence layer of the application. Gemini is central to how the system understands documents, structures ESG data, and assists decision-making.

First, Gemini’s long-context understanding is used to read full loan agreements and sustainability clauses directly from PDFs. Instead of relying on manual review, Gemini extracts ESG-linked targets such as emissions reductions, renewable energy usage, and diversity metrics, and converts them into structured KPIs that power the dashboard.

Second, Gemini’s multimodal reasoning is used when borrowers upload evidence like sustainability reports, spreadsheets, or mixed documents. Gemini analyzes the content, identifies which KPI the evidence belongs to, and flags inconsistencies such as unit mismatches or missing data. This significantly reduces manual verification effort.

Third, Gemini’s reasoning and summarization capabilities are used to generate clear, human-readable insights. The model explains KPI trends, highlights risks of missing targets, and produces simple summaries that bankers, auditors, and non-technical users can easily understand.

Finally, Gemini enables natural-language interaction with the system, allowing users to ask questions like “Are we on track to meet our emissions target?” and receive grounded answers based on the underlying data.