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Use Cases

Private Agent Systems for Your Industry

Discover how enterprises across industries deploy private AI agents - zero data leakage, full control.

Legal Document Review

Law firms and compliance teams use private agents to redline contracts, extract clauses, and summarize case law - zero data leaves the network.

  • Confidentiality guaranteed
  • 90% faster reviews
  • Automatic clause extraction

Manufacturing Quality Control

Factory floor agents analyzing sensor data, predicting defects, and generating maintenance schedules - air-gapped deployment.

  • Predictive maintenance
  • Real-time defect detection
  • 40% downtime reduction

Financial Risk Analysis

Banks running private LLMs on transaction data for fraud detection, regulatory reporting, and portfolio risk scoring.

  • Real-time fraud detection
  • Regulatory compliance
  • Automated reporting

Healthcare Data Processing

Hospitals using private agents for patient record summarization, ICD coding, and clinical trial matching - HIPAA/GDPR compliant.

  • GDPR & HIPAA compliant
  • Automatic ICD coding
  • 80% less manual work

Internal Knowledge Base

Engineering teams deploying private RAG agents over proprietary codebases, Confluence, and Jira - on-prem vector DB.

  • Company-wide searchable knowledge
  • Code context in seconds
  • No SaaS dependency

Supply Chain Optimization

Logistics companies using agents for demand forecasting, route optimization, and supplier risk assessment.

  • 30% cost savings
  • Automated route planning
  • Supplier risk scoring

Deploy in Minutes

One command. Your model. Your infrastructure. No data leaves your network.

nxp-deploy - Private Agent Systems
Architecture

How Private AI Gets Deployed

Click on nodes to reveal infrastructure and data flow details.

Comparison

Private AI vs. Cloud APIs

See why enterprises switch to private deployments for mission-critical AI workloads.

FeatureCloud APIsNexPatch Private AI
Data SovereigntyData leaves your network100% in your VPC/on-prem
Cost at ScaleToken-based, scales linearlyFixed cost, predictable
Latency50-200ms (network-dependent)<10ms (local network)
CustomizationLimited / no fine-tuningFull fine-tuning, RAG, custom agents
ComplianceShared responsibilityGDPR, EU AI Act, SOC 2 compliant
Vendor Lock-inAPI-dependentOpen-source models, portable
ReliabilityProvider outages possibleSelf-hosted, 99.9% SLA
Performance

Benchmark Results

Real-world performance metrics from production deployments on dedicated GPU infrastructure vs. cloud API alternatives.

Inference Latency

NexPatch Private AI12ms
OpenAI API45ms
Azure OpenAI38ms
AWS Bedrock52ms

Throughput (req/s)

NexPatch (A100)850/s
NexPatch (RTX 4090)420/s
Cloud API (rate limited)60/s

Cost per 1M Tokens

NexPatch Private AI0.8
GPT-4 API10
Claude API8
Gemini API3.5

Benchmarks measured on production workloads. Results may vary depending on model size, hardware configuration, and data complexity.

Developer Experience

Build with Our APIs

Clean, well-documented APIs and SDKs in your language of choice. Deploy agents, run pipelines, and query models programmatically.

  • Full REST & gRPC API with OpenAPI specs
  • Python SDK with async support
  • TypeScript SDK for full-stack apps
  • Webhook integrations for CI/CD pipelines
  • Token-based auth with fine-grained scopes
deploy_agent.py
from nexpatch import PrivateAI

client = PrivateAI(api_key="nxp_...")

agent = client.agents.create(
    name="contract-reviewer",
    model="llama-3.1-70b",
    target="vpc",
    gpus=4,
    tools=["document_search", "summarize"]
)

result = await agent.run(
    "Review this NDA for non-compete clauses",
    documents=["contract.pdf"]
)
print(result.summary)

See Private Agent Systems in action

Book a 30-minute live demo with our engineering team