Proprietary Models &
Private LLM Clusters
We build retrieval-augmented generation pipelines (RAG), orchestrate private fine-tuning schedules, and deploy secured inference endpoints within isolated networks.
Tabular & Predictive ML
We structure custom classification, recommendation, and fraud detection trees. Hostable directly on standard virtual CPUs to avoid expensive runtime parameters.
High-Velocity Classification
Ideal for scoring risk matrices, verifying credit limits, predicting user drop-offs, and optimizing logistics routes in sub-5ms latency ranges.
Private Context Indexing
Extract and index unstructured data points from massive PDF vaults and email logs. Ensures zero data leaks to public APIs.
Language & Text Systems
Custom fine-tuning of open models (Llama 3, Mistral) on company datasets, linked to private vector DBs (Qdrant, pgvector) for hallucination-free generation.
Computer Vision Models
Object classification, spatial tracking, and visual compliance checkers trained to run efficiently on small edge devices or centralized GPU servers.
Cargo & Video Classification
Analyze warehouse security streams, catalog product condition parameters, and index cargo tracking coordinates automatically.
Inference Pipeline
Dataset Prep & Anonymization
We run data cleaning scripts to extract personal identifiers from database logs, preparing safe parameters for neural weights training.
Similarity Embeddings Generation
Proprietary documents are chunked and converted into vector keys, then loaded into pgvector database endpoints.
Model Weight Customization
We orchestrate supervised fine-tuning loops on open models, tracking validation metrics to prevent overfitting.
Quantization & API Launch
Model weights compile into compact configurations, running on budget cloud containers with secure HTTP endpoints.
Model Capabilities Matrix
Continuous Model Lifecycle
Data Ingestion
Raw events land in private secure storage buckets.
Training Loop
Custom model weights adapt to the normalized datasets.
Inference Gateway
Live production queries hit active container clusters.
Monitoring & Drift
Confidence metrics trigger automatic retraining loops.
Model Inference Sandbox
Select an input payload and trigger the simulated classification engine.