Real-time computation at
capital markets speed.
QGraph is Euclid's reactive computation engine built on a live dependency graph for real-time pricing, risk and P&L.
The computation engine that replaces batch overnight with real-time always-on.
Traditional risk and pricing systems run in batch — calculating overnight what traders need in real time. QGraph inverts that model with a live dependency graph that recomputes only what changes, the instant it changes.
Every market data tick, position update or parameter change propagates through a directed graph of computation nodes — repricing derivatives, recalculating VaR, updating P&L and aggregating regulatory metrics in sub-millisecond end-to-end latency.
Built for capital markets but applicable to any domain that needs reactive, incremental computation at scale — from real-time logistics optimization to IoT sensor networks.
Reactive computation,
engineered for institutional scale.
Live Dependency Graph
A directed acyclic graph that models every relationship between market data inputs, intermediate calculations and output metrics — with automatic change propagation.
Event-driven Propagation
When a market data tick arrives, only affected nodes recompute. No batch sweeps, no polling — pure reactive propagation through the dependency chain.
Sub-millisecond Latency
Optimized graph traversal and in-memory computation deliver end-to-end recalculation in microseconds — critical for real-time pricing and intraday risk.
Horizontal Scaling
Graph partitioning and distributed execution across compute nodes. Scale linearly by adding capacity — no architectural refactoring required.
FRTB Reporting
Built-in support for Fundamental Review of the Trading Book calculations — SA, IMA and DRC computations with regulatory-grade audit trails.
gRPC / Protobuf APIs
High-performance streaming APIs for integration with trading systems, risk engines, data warehouses and downstream analytics — with schema evolution support.
From market tick to
risk metric.
Model
Define your computation graph — pricing models, risk factors, aggregation hierarchies and output metrics — as nodes and edges in QGraph's declarative DSL.
Connect
Bind live market data feeds, position snapshots and reference data to input nodes. QGraph handles serialization, replay and late-joiner semantics.
Compute
As data arrives, QGraph propagates changes through the dependency graph — recomputing only affected nodes with sub-millisecond end-to-end latency.
Consume
Downstream systems subscribe to output nodes via gRPC streams — receiving real-time P&L, risk metrics, scenario results and regulatory aggregations.
Explore further.
QGraph
How a reactive computation engine replaced overnight batch risk with real-time analytics.
InsightReal-time Risk: Beyond Batch Processing
Why leading institutions are replacing overnight batch with continuous risk computation.
InsightCore Banking Modernization
Why banks are replacing decades-old core systems and how to execute without disruption.
Ready to move from batch
to real-time?
See how QGraph can replace your overnight risk batch with continuous, sub-millisecond computation — on your data, your models, your infrastructure.