Version 4.2 • Now with 10x faster GPU acceleration

Apollo RAG

GPU-Accelerated Document Intelligence

Production-ready RAG system with CUDA optimization, adaptive retrieval strategies, and enterprise-grade deployment. Built for speed, scale, and precision.

127ms
P95 Latency
450q/s
Throughput
94.2%
Accuracy

Built for Production Scale

Enterprise-grade capabilities that power mission-critical applications

Hybrid Search

Combines semantic similarity with BM25 keyword matching for optimal recall and precision

Enterprise Security

Role-based access control, comprehensive audit logging, and SOC 2 compliance ready

Real-time Monitoring

Prometheus metrics, Grafana dashboards, and distributed tracing for full observability

Production Deploy

Docker containers, Kubernetes manifests, and auto-scaling configurations included

Quick Start

Get Apollo running in under 5 minutes:

# Clone the repository
git clone https://github.com/zhadyz/tactical-rag-system.git
cd tactical-rag-system
 
# Launch with Docker Compose (includes GPU support)
docker compose up -d
 
# Upload your first document
curl -X POST http://localhost:8000/upload \
  -F "file=@document.pdf" \
  -H "Authorization: Bearer your-api-key"
 
# Ask a question
curl -X POST http://localhost:8000/query \
  -H "Content-Type: application/json" \
  -d '{"query": "What is the main topic?"}'

See the Getting Started guide for detailed instructions.

Engineered for Performance

Enterprise-grade architecture with careful optimization at every layer

1

Client Layer

Desktop App (Tauri) • Web UI (React) • REST API • WebSocket

2

API Gateway (FastAPI)

Authentication • Rate Limiting • Request Validation

3

RAG Engine Core

Query Analysis • Adaptive Retrieval • Response Generation

Vector Store

FAISS/Milvus

GPU Acceleration

CUDA/cuBLAS

Document Pipeline

PDF/DOCX/TXT

Why Apollo

Four core principles that set us apart from traditional RAG frameworks

True GPU Acceleration

Unlike frameworks that claim GPU support but run most operations on CPU, Apollo leverages CUDA for every compute-intensive operation: embeddings, similarity search, re-ranking, and token generation.

Learn about our GPU architecture

Adaptive Retrieval Intelligence

Apollo analyzes query complexity in real-time and automatically adjusts retrieval strategies, chunk sizes, and re-ranking depth to optimize both latency and accuracy. No manual tuning required.

Explore adaptive strategies

Production Observability

Built-in metrics, tracing, and profiling at every layer. Know exactly what's happening in your RAG pipeline with OpenTelemetry integration and custom performance dashboards.

View monitoring features

Enterprise Ready

Multi-tenant architecture, role-based access control, comprehensive audit logging, and compliance features designed for regulated industries and enterprise deployments.

See security features

Performance Comparison

Apollo consistently outperforms popular RAG frameworks in real-world benchmarks

SystemLatency (P95)ThroughputAccuracyGPU Utilization
ApolloBest
127ms450 q/s94.2%88%
LangChain892ms67 q/s89.1%23%
LlamaIndex654ms102 q/s91.3%41%
Haystack543ms134 q/s90.7%35%

Benchmark conditions: 100K document corpus, NVIDIA A100 40GB, concurrent queries, mixed complexity

View detailed benchmark methodology and reproduce results

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Built with NextraMIT License