NeuroSoft ENTERPRISE PRACTICE — GENERATIVE AI

Governed Generative AI Architectures for Mission-Critical Enterprise Workflows

Design, fine-tune, integrate, and deploy private RAG pipelines, domain-specific LLM copilots, and multi-agent reasoning systems with zero data bleed and SOC 2 Type II compliance.

99.9%
Retrieval Context Precision
<3.5ms
Vector Query Latency
Zero
Data Bleed Guardrails
SOC 2 II
Compliance Certified
PART 01 — PROPRIETARY MODEL ARCHITECTURE

Gen AI Models Design & Fine-Tuning

Purpose-built neural architectures, parameter-efficient fine-tuning (PEFT), and domain-adapted LLM reasoning systems engineered for enterprise data assets.

MODEL FINE-TUNING PIPELINE
1. Base Model Selection (Llama 3 / Mistral) 70B Parameters
2. Parameter-Efficient LoRA Adapter Inject Domain Specific
3. 4-bit AWQ / GPTQ Quantization 60% VRAM Reduction ✓

Domain-Adapted Language Models

Adapt open-weights foundation models on your internal technical manuals, legal contracts, and financial ledgers without risking public data exposure.

Custom Tokenizer & Vocabulary Optimization

Extend BPE tokenizers with industry-specific terminology to reduce token fragmentation and lower inference costs by up to 35%.

Multi-Modal Architecture Design

Integrate vision transformers (ViT) and audio encoders into unified multi-modal reasoning models for complex document and stream analysis.

PART 02 — ENTERPRISE CONNECTIVITY & RAG

Gen AI Integrations & RAG Pipelines

Embedding generative intelligence directly into enterprise ERP, CRM, databases, and multi-vector search repositories.

<3.5ms

Hybrid Dense/Sparse Vector RAG

Connect vector stores (Milvus, Qdrant, pgvector) with BM25 sparse keyword search and Cohere reranking for 99.9% context retrieval precision.

ERP & Database API Connectors

Out-of-the-box data pipelines connecting generative copilots directly to SAP, Salesforce, Microsoft Graph, Snowflake, and Postgres.

GraphRAG Knowledge Synthesis

Combine vector search with Neo4j enterprise knowledge graphs to synthesize multi-hop relationships across complex corporate documentation.

PART 03 — GOVERNANCE & SAFETY GUARDRAILS

Gen AI Audit & Maintenance

Continuous model evaluation, automated PII sanitization, toxicity filtering, and immutable compliance logging.

Real-Time NeMo Safety Guardrails

Intercept prompt injection attacks, mask sensitive customer PII, and block unsafe output generation before responses reach end users.

Automated Hallucination Scorecards

Evaluate output faithfulness against retrieved ground-truth documents with real-time NLI (Natural Language Inference) scoring engines.

SOC 2 & GDPR Audit Trail Logging

Cryptographically log every prompt, context payload, model response, and safety score for complete regulatory transparency.

PART 04 — HIGH-SCALE PRODUCTION RUNTIMES

Gen AI Model Deployment & Scaling

Deploying generative AI workloads into private cloud environments with auto-scaling inference endpoints and zero data leak guarantees.

VPC

Private Cloud Hosting

Host generative models exclusively within your AWS, Azure, or GCP Virtual Private Cloud (VPC) boundaries.

vLLM

High-Throughput Serving

Utilize PagedAttention and vLLM execution engines to maximize token throughput and minimize latency spikes.

Auto

Serverless GPU Scaling

Dynamic GPU pod auto-scaling based on token demand with automated zero-cost idle shutdown rules.

SCALE GENERATIVE AI WITH CONFIDENCE

Consult with NeuroSoft AI Practice Leads

Schedule a technical consultation to design private RAG pipelines, fine-tune LLMs, or audit Generative AI safety guardrails.

Schedule AI Architecture Briefing →