Retrieval Optimization

Generic models guess. Ours learn. We automate the tuning of dense and sparse embeddings to your specific domain, ensuring that search results map to actual business intent.

Generic Embeddings

General-purpose models confuse distinct concepts without domain-specific fine-tuning.

Precision62%
Isolate PatientIsolate HostRisk IsolationClinical ProtocolNetwork ProtocolPolicy ProtocolViral CultureViral MalwareViral Exclusion
Medical
Insurance
Cyber

K² Optimized

Domain tuning adjusts weights, moving relevant concepts closer and pushing noise away.

Precision94%
Isolate HostNetwork ProtocolViral MalwareIsolate PatientClinical ProtocolViral CultureRisk IsolationPolicy ProtocolViral Exclusion
Medical
Insurance
Cyber

Synthetic Contrastive Alignment

We solve the cold-start problem by generating synthetic training triplets from your raw documents. Our pipeline mines hard negatives using embedding similarity to align models before a single user query is fired.

  • Zero manual labeling required
  • Automated negative mining
  • Tuned in under 15 minutes
Input
Raw PDFs / HTML
Processing
Synthetic Triplets
Output
Aligned Weights