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AI Engineering & Security

End-to-End Elite AI Engineering

From Vibe Coding to enterprise deployment. We build cloud orchestration, sovereign local inference, and agent governance for companies demanding excellence.

360°
Cloud & On-Prem
Agnostic
0%
Data Exfiltration
Private RAG
Full
Compliance
GDPR/LGPD
Cloud AI
On-Prem
Edge
Hybrid

The Vulnerabilities of Unregulated AI

Artificial Intelligence without engineering is a liability, not an asset.

sysadmin@ai-gateway:~
$ ./scan_ai_infrastructure --mode deep_audit
Initializing vulnerability and governance scan... Done.
[CRITICAL]PII Leakage in Prompts

Sensitive data sent to public APIs without prior sanitization, control, or masking.

[CRITICAL]Agent Hallucination

Inaccurate or dangerous responses generated by decontextualized models without structured RAG.

[CRITICAL]Uncontrolled Shadow AI

Decentralized use of dozens of AI SaaS tools off the radar and out of security control.

[CRITICAL]Vendor Lock-in & Costs

Architectures tightly coupled to a specific provider (OpenAI), hindering migration and inflating costs.

$ Execution required: Deploy Enterprise AI Blueprint..._

Enterprise AI Ecosystem

Agnostic and Scalable Solutions

Managed Cloud AI

Architecture and deployment over enterprise cloud services (NVIDIA AI Enterprise, AWS Bedrock, GCP Vertex, Azure OpenAI) with centralized orchestration.

SYSTEM_ACTIVE100% HEALTH

Sovereign Inference (On-Prem)

Deployment of open models (Llama 3, DeepSeek R2, Qwen 3, Mixtral, Kimi, Minimax) via NVIDIA NIM in GPU-optimized containers — many with no upfront license cost.

Secure RAG & Hybrid

Enterprise RAG pipeline with NVIDIA RAG Blueprint: vector indexing, NIM reranking, and advanced extraction from PDFs/tables/charts.

AI Security Governance

NeMo Guardrails for Content Safety, Topic Control, and Jailbreak Detection, plus offensive Red Teaming with NVIDIA Garak.

SYSTEM_ACTIVE100% HEALTH

Real-World Applications

How our clients transform operations with elite AI Engineering.

Private Legal Analysis

Extraction and summarization of confidential contracts via local RAG without data traveling to the cloud.

Security Operations

Log triage agents that analyze SIEM alerts and suggest mitigations, running isolated on the perimeter.

Autonomous Support

Intelligent ticket routing based on unified knowledge bases from Zendesk/Jira.

Assisted Software Engineering

Internal assistant connected to private company repositories (Git) for secure onboarding and pair programming.

AI-Powered CVE Analysis

NVIDIA Morpheus + NIM for automated container vulnerability analysis, reducing CVE triage from days to seconds.

Sovereign GPU Inference

LLM deployment via NVIDIA NIM on H100/A100 GPUs on-premise with TensorRT-LLM, ensuring minimal latency and full data sovereignty.

Why Does AI Engineering Matter?

The difference between experimental projects and production-ready systems.

Ungoverned AI (SaaS/Shadow AI)
Enterprise AI (Tech86)
Data Privacy
Variable (training risk)
Guaranteed by AWS/Azure contract or Local inference
System Exposure
APIs directly exposed to employees
Orchestration via protected local gateways
Dependency (Lock-in)
Total reliance on one vendor (e.g., OpenAI)
Agnostic. Easy switching Azure/Bedrock/NIM Local
Cost Visibility
Unpredictable, decentralized monthly billing
Centralized inference quota control
Hallucination Rate
High (lacks company context)
Low (anchored by clean RAG pipelines)
Compliance (GDPR)
Hard to map data flows and DPIA
By-Design architecture ready for audits
GPU-Accelerated Inference
No optimization (generic CPU or API)
NVIDIA NIM + TensorRT-LLM with signed containers and SBOM

AI Adoption Roadmap

Tactical methodology without wasting time in infinite PoCs.

Phase 01

Discovery & Threat Modeling

Data identification, leakage risk mapping, and strategic definition of the ideal deployment (Cloud vs Local).

Phase 02

AI Pipeline & RAG Design

Robust construction of invisible data engineering (ETL ingestion, vectorization, and targeted embeddings).

Phase 03

Orchestration & Integration

Implementing Control Planes, LLM Gateways, and monitoring response stability via LLMs-Judges.

Phase 04

Hardening & Red Teaming

Offensive bombardment (Jailbreaking, RBAC Exploitation) simulating real attacks against AI in staging.

Corporate AI requires Engineering, not just an API.

Stop sending your strategic data to black boxes. Integrate intelligence into your processes safely with resilient architecture.

Accelerate AI Projects

The 360° Artificial Intelligence Stack

We master the entire AI ecosystem: from managed SaaS Providers to dense on-premise infrastructure.

Foundational Models

NVIDIA NemotronLlama 3.3 (Meta)DeepSeek R2 / V3.2Qwen 3 (Alibaba)Mistral Large 3Gemini 3.1 ProClaude 4.6 (Opus/Sonnet)MinimaxKimi (Moonshot)OpenAI GPT-5.2

Cloud AI Platforms

NVIDIA AI EnterpriseAWS BedrockGoogle Vertex AIDatabricks Mosaic AIAzure OpenAI

Frameworks & Agents

LangChain & LangGraphSemantic KernelSmolAgentsPydanticAILlamaIndexCrewAIAutoGenNVIDIA NeMo

Inference Infra

NVIDIA NIMvLLMSGLangTensorRT-LLMLMDeployOllamaTGI

Vector DBs & Search

OpenSearchMilvusPineconeQdrantWeaviatepgvectorNVIDIA cuVS

MLOps & Governance

NeMo GuardrailsNVIDIA MorpheusNVIDIA GarakLangSmithArize PhoenixDSPyGuardrails AIMLflowPromptfoo
NVIDIA Partner

NVIDIA NIM Platform

GPU-optimized inference microservices that accelerate enterprise AI deployment from weeks to minutes.

NIM Inference Engine

Pre-built, GPU-optimized containers with industry-standard APIs. Deploy state-of-the-art models (Nemotron, Llama, DeepSeek, Qwen, Mixtral, Kimi, Minimax) on any NVIDIA-accelerated infrastructure — many with no upfront cost.

NeMo Guardrails

Programmable safety microservices: Content Safety (35k+ samples), Topic Control to prevent conversational drift, and Jailbreak Detection trained on 17k+ known exploits.

RAG Blueprint

Enterprise reference pipeline for Retrieval-Augmented Generation with NIM: inference, reranking, PDF/table/chart extraction, and multimodal embeddings.

Morpheus Cyber AI

AI-powered cybersecurity framework for CVE analysis at scale, real-time anomaly detection, and container protection with SBOM and cryptographic signing.

AI Engineering FAQ

Strategic questions and answers about implementation.

Cloud AI (via NVIDIA AI Enterprise, AWS Bedrock, Google Vertex, or Azure OpenAI) uses managed models with heavy corporate SLAs and does NOT train on your data. Local AI runs open models (Llama, DeepSeek, Qwen, Mixtral, etc.) on proprietary servers via NVIDIA NIM for cases where data cannot leave the perimeter, or to drastically reduce token costs at high volumes.

Myth. Today's open-weight models (like Llama 3 70B, DeepSeek R2, Qwen 3 72B, and Mixtral 8x22B) often surpass first-generation paid models in corporate benchmarks, while being highly optimized for fast inference via NVIDIA NIM (Edge/On-Prem) — many available with no upfront license cost.

An architecture that connects LLM intelligence to your structured (and unstructured, like PDFs) data, ensuring responses with truthful corporate context and citing documentary sources.

More than magic texts, it's testable software development. We create deterministic system templates governed via CI/CD to prevent AI response regression.

Unplanned projects scale token costs absurdly fast. We analyze the utility of each use case against compute consumption to determine if it requires a giant cloud model or a focused small local one.

Prompt Injection aims to induce adversarial actions bypassing main directives. We employ LLM Firewalls, I/O sanitizers, and semantic verification to shield your agents.

NVIDIA NIM (NVIDIA Inference Microservices) are pre-built, GPU-optimized containers that transform AI model deployment from weeks to minutes. They offer industry-standard APIs, auditable SBOM, cryptographic container signing, and support for cloud, on-premise, or air-gapped deployments with full security and compliance.

NVIDIA NeMo Guardrails are specialized NIM microservices trained on extensive datasets (35k+ Content Safety samples, 17k+ known jailbreaks). Unlike generic solutions, they offer Topic Control, Jailbreak Detection, and Content Safety as GPU-optimized services, natively integrated with Nemotron models and with minimal inference latency.

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