Enterprise AI Engineering & LLM Solutions

Enterprise AI & Generative AI Development Services

DecillionX architects proprietary, zero-data-leakage Artificial Intelligence platforms. We engineer autonomous agentic workflows, fine-tune domain-specific foundation models, build enterprise RAG vector engines, and deploy high-throughput neural inference systems built for business impact.

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99.2%

Context Recall Accuracy

< 250ms

Inference Response Latency

100%

Proprietary IP & Zero Data Leakage

2 - 3 Weeks

Functional POC Delivery

Full-Stack AI Stack

Next-Generation AI Engineering Capabilities

From foundation model fine-tuning to autonomous multi-agent swarms, our deep learning architects build end-to-end solutions that automate complex enterprise operations.

Autonomous Agentic Workflows

Multi-agent systems using CrewAI, LangGraph, and AutoGen that collaborate, execute multi-step research, call APIs, automate reconciliation, and handle complex enterprise workflows autonomously.

  • Dynamic Task Planning & Tool Invocation
  • Human-in-the-Loop Approval Routing
  • Fault-Tolerant State Machine Persistence

Enterprise RAG & Vector Pipelines

Production-grade Retrieval-Augmented Generation that connects LLMs to your private data lakes, relational databases, Confluence, ERPs, and document archives with semantic accuracy.

  • Hybrid BM25 & Dense Vector Search
  • Cohere & BGE Cross-Encoder Reranking
  • Pinecone, Milvus, Qdrant & pgvector Integration

LLM Fine-Tuning & Quantization

Adapt foundation open-weights models to your proprietary vocabulary, compliance standards, and internal domain using LoRA, QLoRA, and Direct Preference Optimization (DPO).

  • Llama 3, Mistral, DeepSeek & Gemma Adaptation
  • 4-bit / 8-bit AWQ & GPTQ Quantization
  • 4x to 8x GPU Infrastructure Cost Reductions

Computer Vision & Video Intelligence

Industrial real-time computer vision models for automated quality inspection, OCR document parsing, defect detection, and edge camera analytics running on TensorRT.

  • Real-time YOLOv10 Object Detection
  • Vision-Language Models (VLM) for Diagnostics
  • Embedded NVIDIA Jetson & Industrial Edge Deployment

Predictive Analytics & Forecasting

High-precision statistical and neural forecasting algorithms that analyze customer churn, demand volatility, financial risk scoring, and predictive equipment maintenance.

  • Time-Series Neural Forecasting (PatchTST, N-BEATS)
  • Real-Time Fraud & Anomaly Scoring
  • Automated Feature Store Architecture

LLM Security & Guardrail Engineering

Hardened guardrail layers and red-teaming pipelines that prevent prompt injection attacks, sensitive PII leakage, jailbreaks, and hallucinations in production environments.

  • NeMo Guardrails & Llama Guard Integration
  • OWASP Top 10 for LLMs Vulnerability Shield
  • Continuous Model Drift & Latency Telemetry
Technology Matrix

Enterprise AI & Deep Learning Stack

Foundation Models

Llama 3, Mistral 7B/8x22B, DeepSeek V2, Gemma, Claude 3.5, OpenAI GPT-4o, Cohere Command-R+

Agent & Orchestration

LangChain, LangGraph, CrewAI, LlamaIndex, AutoGen, Semantic Kernel, Haystack

Vector Databases

Milvus, Pinecone, Qdrant, Weaviate, pgvector, Chroma, Elasticsearch Vector Engine

Inference & Serving

vLLM, TensorRT-LLM, Triton Inference Server, Ollama, Ray Serve, Hugging Face TGI

AI Engineering FAQ

Frequently Asked Questions: Enterprise AI

Essential technical insights on data confidentiality, sovereign deployments, accuracy evaluation, and production SLAs.

How does DecillionX ensure enterprise data privacy with LLM deployments?
DecillionX implements zero-data-leakage architecture. Client training data and corporate documents are processed within dedicated, isolated virtual private clouds (VPC) or sovereign on-premise hardware. Data is never shared with public model providers, and all vector databases are encrypted with AES-256 keys managed by the client.
Can DecillionX deploy open-source models on private on-premise or sovereign cloud infrastructure?
Yes. We specialize in quantizing and deploying state-of-the-art open models (Llama 3, Mistral, DeepSeek, Gemma) using vLLM, TensorRT-LLM, and Ollama directly on private AWS, Azure, Google Cloud, or bare-metal Kubernetes GPU clusters with complete data sovereignty.
How does DecillionX benchmark and evaluate Generative AI accuracy and hallucination reduction?
We deploy automated continuous evaluation frameworks using RAGAS, TruLens, and G-Eval to quantify context recall, precision, and faithfulness. Hallucination guardrails and semantic validation filters intercept and verify responses before they reach end users.
What is the typical timeframe to deliver an enterprise AI proof-of-concept (POC)?
Our AI squads deliver an interactive, benchmarked functional proof-of-concept (POC) connected to your enterprise data within 2 to 3 weeks, followed by iterative enterprise hardening and production deployment.

Ready to Transform Your Enterprise with Proprietary AI?

Collaborate directly with our principal AI architects and deep learning researchers. We analyze your workflows, evaluate data pipelines, and architect custom AI systems tailored to your enterprise goals.

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