Case Study — YieldSphere

Portfolio Operational Intelligence Platform

Unifying On-Chain Positions, Fund Accounting, and Market Intelligence in One Platform

3 disconnected systems unified into a single operational picture for an institutional DeFi fund

Industry

DeFi Fund / Digital Asset Manager

Timeline

18 weeks

Team

7 engineers

Tech

React + PostgreSQL + dbt

The Challenge

An institutional DeFi fund managing positions across 30+ protocols and 10+ chains, with traditional fund accounting and market-data subscriptions, was running on-chain position tracking, fund accounting, and market intelligence on completely separate systems with no data sharing. The 4-day monthly NAV close involved 3 separate teams reconciling between systems with a 15-20% error rate in initial drafts.

Our Approach

How We Solved It

Data Integration Architecture

Built a unified data integration layer connecting on-chain position indexing (via The Graph), the fund accounting system, and market data feeds — establishing a single operational data store with consistent entity references across all three systems.

Unified Position Accounting Model

Designed a granular accounting model that tracks cost basis, realized/unrealized P&L, and yield accrual at the position and protocol level — replacing the prior practice of portfolio-level aggregation that obscured performance differences between protocols.

Market Intelligence Integration

Connected token price feeds, DEX liquidity data, and protocol TVL data into the operational platform so NAV calculations use current market prices rather than the previous-day batch from a separate system.

Integrated NAV Dashboard

Built a real-time NAV dashboard showing performance per protocol, per chain, and per strategy with full drill-down — eliminating the 4-day close and replacing it with a continuously updated operational NAV.

Engineering Process

How We Built It

dbt Semantic Layer for Cross-System Metrics

dbt semantic models define business metrics (yield accrued, realized P&L, risk-adjusted return) in one place, ensuring consistent definitions across fund accounting, portfolio management, and investor-reporting views.

Event-Driven Cross-System Sync

On-chain events (deposits, withdrawals, reallocations, yield claims) trigger automatic updates to position accounts and NAV, replacing the weekly manual reconciliation that was the primary source of the 15-20% error rate.

Hierarchical Position Architecture

Positions follow the natural portfolio hierarchy (fund → strategy → protocol → pool), enabling drill-down from fund-level NAV to individual pool performance without custom reporting work.

Architecture Decisions

Key Technical Choices

Operational Data Store Over Data Warehouse

An operational data store (ODS) with dbt transformations rather than a pure analytical data warehouse — the ODS serves both operational dashboards (low-latency read) and analytical/investor reporting (batch aggregation).

Market Data as Real-Time, Not Batch

Delayed token price data in NAV calculations caused systematic misvaluation of open positions. Real-time price feeds were non-negotiable for accurate intraday NAV visibility.

Rolling NAV Over Period-Close Only

The platform maintains a continuously updated rolling NAV rather than computing NAV only at period close — a design choice that eliminates the close process while improving portfolio-management decision-making.

Results

What We Delivered

Systems Unified

100%

Data Consistency Across Systems

Same Day

NAV Visibility (was 4 days)

35%

Reduction in Operational Overhead

Solution Blueprint

How It All Fits Together

Integration Layer

On-chain position indexing connector
Fund accounting system sync
Real-time market data feeds

Analytics Layer

dbt semantic performance models
Protocol-level P&L attribution
Cross-chain risk analytics

Operations Layer

Integrated NAV dashboard
Position drill-down
Market intelligence view

Lessons Learned

What We Improved

Entity Resolution Is the Core Technical Challenge

The three systems used different identifiers for the same positions, protocols, and chains. A 3-week entity resolution process to create a unified master data layer was the critical path item for the entire project.

Fund Accounting and Portfolio Management Have Different Granularity Needs

Fund accounting wanted period-end NAV summaries; portfolio management wanted intraday position-level visibility. Building both views on the same underlying data model satisfied both without compromise.

The Market Data Integration Changed Decision Culture

When managers could see current-market NAV impact per protocol in real time, they began making reallocation decisions based on live risk-adjusted return rather than end-of-week reporting. This was the highest-value outcome — and was discovered, not planned.