AI-02Service Line

AI Engineering

Enterprise-grade intelligence systems and model integration.

Overview

Enterprise-grade AI design and implementation. We focus on fine-tuning models, building secure retrieval-augmented generation (RAG) pipelines, embedding structures, and optimizing inference workloads at enterprise scale.

Engineering Benefits

Context-Aware RAG Pipelines

Ingest multi-format enterprise documentation into secure vector databases with advanced hybrid search and reranking.

Custom LLM Fine-Tuning

Adapt open-weights models (Llama 3, Mistral) to business domains using PEFT/LoRA techniques for specialized logic.

Inference Latency Optimization

Scale compute resources with custom execution layers, GPU scheduling, caching, and model quantization.

Technology Profile

PyTorchvLLMHugging FaceLangChainLlamaIndexPgvector

System Pipeline

Architected for isolated data context, high-throughput model inference, and structured telemetry.

RAG & LLM Execution Pipeline
[1]Data Ingestion → Chunking & Metadata Enrichment
[2]Embedding Generator → Secure Batch Vector Injection
[3]Hybrid Vector Search + Reranking (Cross-Encoder)
[4]Context Prompt Compiler → Guardrails Evaluation
[5]Inference Orchestration Engine (vLLM)
[6]Telemetry & Audit Logging (Traces, Tokens, Latency)
STATUS: COMPILEDIllustrative high-availability architecture

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Get in touch directly with our technology team to discuss custom integrations, scale capacity, model planning, and architecture objectives.

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