Custom Algo Trading Software
We engineer institutional-grade execution engines used by quant desks, prop firms and broker-dealers — built on .NET 8 and Python with FIX, REST and WebSocket connectivity to global venues.
12ms
Median tick-to-order
9
Brokers integrated
99.99%
Engine uptime
Capabilities
What you get
- Strategy framework with tick-level backtesting
- FIX 4.4 + native broker SDK adapters
- Pre-trade and live risk controls (VaR, exposure, kill-switch)
- Smart order routing and slippage-aware execution
Engineering stack
Battle-tested tech
- .NET 8
- Python
- Kafka
- MySQL
- MongoDB
- Redis
High-Frequency Trading · Hot Path
Tick-to-order in single-digit milliseconds
Execution
12ms
Throughput
184k ops/s
Slippage p99
0.7 bps
Uptime
99.997%
Order routing topology
Co-located · Lock-free queues · Span<T> zero-alloc I/O
Greek parameters · live
Δ Delta
0.6421
Directional exposure per tick
Γ Gamma
0.0184
Convexity of delta
Θ Theta
-0.0312
Time-decay per session
ν Vega
0.1207
IV sensitivity bp
ρ Rho
0.0089
Rate sensitivity
λ Lambda
1.482
Leverage elasticity
FIX 4.4 sessions
Persistent, sequenced, encrypted
Strategy versioning
Backtest + paper + live in lockstep
Real-time PnL
Per-strategy and per-instrument
Institutional Framework
Quantitative methodology — precision at scale
Strategy Research & ADRs
Quant-led discovery capturing alpha targets, risk parameters and execution topology. Every logic trade-off is committed as a versioned ADR.
Low-latency trunk delivery
Short-lived branches, mandatory peer review by quant engineers, and progressive rollout via shadow-mode testing.
Tick-by-tick observability
Every strategy ships with real-time PnL dashboards, latency heatmaps, and automated risk kill-switches.
Backtest gates, not assumptions
Slippage budgets, transaction cost analysis (TCA), and walk-forward optimization are gates in CI — strategies must pass to go live.
Technical Specifications
What runs underneath
.NET 8 Hot-Path Engineering — async/await primitives, ReaderWriterLockSlim mutex strategies, lock-free ring buffers, Span<T> zero-allocation I/O, Channels for backpressure-aware pipelines.
Concurrency model
Thread-safe .NET mutex pools, lock-free queues, async I/O
Transport
FIX 4.4, gRPC, WebSocket, REST
Latency target
p99 < 15ms tick-to-order
Compute
Horizontally scaled, stateless containers behind L7 routing
Security & Scalability
Risk & Security posture
Pre-trade risk controls
Hard-coded exposure limits, fat-finger protection, and automated margin checks gate every order before it hits the exchange.
Hardened API security
mTLS between services, KMS-managed API keys, AES-256 encryption at rest, and bank-grade vaulting for broker credentials.
Burst-ready scalability
Backpressure-aware queues and circuit breakers load-tested with k6 to 10× peak market volume before every major release.
Co-located resilience
Active-active across data centers, automated failover, and quarterly chaos drills with documented recovery paths.
Delivery Architecture
How it ships — blueprint to production
A high-performance trading architecture mapped to your broker topology, with every integration touchpoint and a phased execution timeline.
Reference architecture
Client edge → API gateway → services → data plane
Cross-cutting · Observability · Security · CI/CD · IaC
Integration touchpoints
Exchange
Zerodha, Interactive Brokers, Binance
Data plane
MySQL, MongoDB, Redis, S3
Cloud
AWS / Azure landing zone
Observability
OpenTelemetry → Datadog / Grafana
Security
Vault, KMS, WAF, Cloudflare
Delivery
GitHub Actions, ArgoCD, Terraform
Execution timeline
- 01
Week 0–2
Discovery & Backtesting
Senior quant architect captures alpha targets, risk parameters, and strategy ADRs.
- 02
Week 2–6
Foundation & Paper
Landing zone setup, broker integration, and first vertical slice in a paper-trading environment.
- 03
Week 6–12
Iterative Build
Two-week sprints with progressive strategy rollout behind shadow-mode flags.
- 04
Week 12+
Live & Hardening
Load tests at 10× peak, final security audit, runbooks, and live production cutover.
Engineer with us