Core AI Competencies
RAG Pipelines
We design semantic indexing engines using vector storage. We integrate pgvector, Pinecone, and Qdrant to search millions of document embeddings in milliseconds with hybrid search logic.
Agentic Workflows
Custom AI agents capable of tool usage, dynamic planning, and multi-step reasoning. We leverage LangChain and LlamaIndex to automate enterprise support, ETL pipeline ingestion, and code generation.
Model Fine-Tuning
Adapter-based training (LoRA/QLoRA) to specialize models on your codebase, proprietary schemas, or brand copy. Optimized for high concurrency using vLLM inference runtimes.
Industrial System Topology
We architect self-contained, enterprise AI infrastructure designed for sub-100ms response cycles. Our pipelines are built from the ground up to support highly concurrent semantic search queries, secure enterprise databases, and robust multi-agent orchestration.
- LoRA / QLoRA adapter training interfaces
- Sub-100ms vector semantic searches across multi-gigabyte files
- Closed Virtual Private Cloud (VPC) subnets for compliance
- Direct vLLM server scaling running on GPU nodes
Frequently Addressed Protocols
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