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DATA SKY NETBUILDING THE FUTURE OF AI
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OUR ENGINEERING CAPABILITIES

Technology built for the agentic era.

From experimental assistants to production-ready autonomous workflows, we design systems that balance intelligence, reliability, security, and human control. These are engineering capabilities and solution areas, not claims of completed customer projects.

/01

AI Agent Engineering

Intelligent workflows with clear boundaries. From multi-agent orchestration to production-ready autonomous systems.

MULTI-AGENT SYSTEMSRAGTOOL ORCHESTRATION
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/02

MCP Infrastructure & Security

Connect agents to enterprise tools without compromising control. Secure integrations, scoped access, and complete visibility.

MCP GATEWAYSLEAST PRIVILEGETOOL SECURITY
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/03

DevSecOps & Supply Chain

Security throughout the delivery lifecycle. Hardened pipelines, trusted artifacts, and policy-driven automation.

SECURE CI/CDSBOMPOLICY AS CODE
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/04

Cloud-Native Engineering

Resilient platforms engineered for scale. Kubernetes, hybrid cloud, and infrastructure built to perform under pressure.

KUBERNETESGITOPSOBSERVABILITY
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/05

Private AI & GPU Infrastructure

Your models. Your infrastructure. Your control. Private inference environments designed around sensitive data.

PRIVATE INFERENCEGPUDATA ISOLATION
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/06

Cybersecurity Engineering

Defense in depth for an evolving attack surface. Identity, trust boundaries, and security-conscious architecture.

ZERO TRUSTTHREAT MODELINGIAM
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01 · ENGINEERING CAPABILITY

AI Agent Engineering

  • Agent architecture and lifecycle management
  • Retrieval-augmented generation and private models
  • Human-in-the-loop workflows and controlled tool execution
  • Agent observability, safety, and reliability evaluation
ILLUSTRATIVE USE CASE

An engineering assistant retrieves approved documentation and proposes code changes for human review.

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02 · ENGINEERING CAPABILITY

MCP Infrastructure & Security

  • MCP client, server, and gateway architecture
  • Token validation, audience restrictions, and scoped authorization
  • Tool inventory, allowlisting, and third-party risk assessment
  • Secrets isolation, auditability, and runtime visibility
ILLUSTRATIVE USE CASE

An agent searches an internal repository through a gateway enforcing read-only, resource-specific permissions.

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03 · ENGINEERING CAPABILITY

DevSecOps & Supply Chain

  • SAST, DAST, SCA, and secrets detection
  • SBOM generation and dependency integrity
  • Container image and infrastructure-as-code scanning
  • Vulnerability management and secure repository controls
ILLUSTRATIVE USE CASE

A delivery pipeline checks source, dependencies, and signed artifacts before a reviewed production release.

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04 · ENGINEERING CAPABILITY

Cloud-Native Engineering

  • Kubernetes, private cloud, and hybrid environments
  • Infrastructure as Code and GitOps
  • Secure networking, high availability, and observability
  • Disaster recovery and resilient distributed systems
ILLUSTRATIVE USE CASE

A platform team operates segmented Kubernetes workloads with monitored deployment changes and recovery procedures.

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05 · ENGINEERING CAPABILITY

Private AI & GPU Infrastructure

  • Self-hosted language models and GPU inference
  • AI serving architecture and inference optimization
  • On-premises deployment and secure model access
  • Data isolation and local AI agent environments
ILLUSTRATIVE USE CASE

A private inference service keeps approved retrieval sources and model access within defined infrastructure boundaries.

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06 · ENGINEERING CAPABILITY

Cybersecurity Engineering

  • Identity and access management and network segmentation
  • Container, Kubernetes, and API security
  • Infrastructure hardening and security observability
  • Threat modeling, incident readiness, and risk-based remediation
ILLUSTRATIVE USE CASE

A security team reviews identities, segments workloads, and prioritizes remediation based on realistic impact.

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ONE CONNECTED ENGINEERING DISCIPLINE

Intelligence without losing control.

Agent architecture, delivery pipelines, identity, and infrastructure belong in the same engineering conversation. Each request should cross explicit, observable trust boundaries.

AGENT → TOOL TRUST ARCHITECTURE● VERIFIED
AI AGENT
MCP GATEWAY
IDENTITY · POLICY · APPROVAL
REPOSITORIES
INFRASTRUCTURE
DATA SOURCES
✓ SCOPED ACCESS   /   ✓ AUDIT RECORDED   /   FICTIONAL ENVIRONMENT
OUR ENGINEERING APPROACH

From architecture to operational confidence.

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Understand requirements, assets, existing infrastructure, business constraints, and risks.

YOUR NEXT CHAPTER

Let’s engineer what’s next.

Complex challenges. Clear architecture. A conversation is a good place to start.

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