Research-Validated Performance

Breaking the Embedding Ceiling

Google DeepMind proved embeddings hit mathematical limits at scale. Our Monte Carlo approach breaks through those barriers with measurable results.

DeepMind LIMIT Benchmark

89% Recall Where GPT-4 Scores 18%

On DeepMind's LIMIT benchmark (50K documents), our Monte Carlo approach achieves what embeddings mathematically cannot.

Source: Google DeepMind LIMIT Benchmark (August 2025)

Adaptive Learning

Gets Smarter With Every Query

While embeddings stay static, Dexrag learns your domain and improves continuously. By query #1000, we're 47% better than embeddings.

+15%
Query #1 (Before Learning)
+25%
Query #100 (Learning Your Domain)
+47%
Query #1000 (Fully Optimized)
Domain Intelligence

Learns Your Domain-Specific Language

Generic embeddings trained on internet text don't understand your specialized terminology. Dexrag adapts to legal jargon, technical specs, and business context automatically.

94%
Legal Terms Recognition
92%
Technical Jargon Understanding
95%
Business Context Awareness
Comprehensive Metrics

Superior Across All Metrics

Not just recall—we outperform embeddings on precision, F1 score, and NDCG. Every metric that matters shows consistent superiority.

92% F1 Score at Day 30

Compared to 29% for GPT-4 embeddings—a 3.2x improvement in overall accuracy

Real-World Performance Tests

Benchmarks across legal documents and technical documentation showing consistent superiority.

Cost Efficiency

Better Results, 80% Lower Cost

No expensive vector databases. No hidden embedding costs. Just superior performance at a fraction of the price.

Save $4,812/year

No vector database fees. No embedding generation costs. No scaling surprises.

See the difference yourself

Upload your documents and watch Monte Carlo exploration beat embeddings in real-time. No credit card required.

10M+ queries optimized • 92% stick rate after trial • 4.9/5 developer satisfaction