Enterprise AI Engineered, Governed & Secured.
We build production AI systems inside your private cloud tenant, and we secure them with NIST AI RMF, ISO 42001, and adversarial guardrails.
Our Consulting Practices
Two specialized practices spanning end-to-end applied AI engineering and comprehensive risk governance.
Practice 1: Applied Enterprise AI Development
Outcome
Engineers stop searching across fragmented PDFs and outdated revisions.
Engineering Knowledge Platforms (RAG)
We convert technical standards, design manuals, and SOPs into accurate, revision-aware RAG tools. Real-time citations, confidence metrics, and cross-standard mapping included.
Best fit
Engineering, energy, and construction firms with deep technical documentation libraries.
Outcome
Your AI agents securely query internal APIs, databases, and BIM models.
Custom MCP Servers & Tooling
We build Model Context Protocol (MCP) integrations connecting frontier LLMs to your engineering databases, Revit/CAD models, and QA systems with strict role-based controls.
Best fit
Teams adopting Cursor, Claude Code, or Copilot who need agentic access to private engineering systems.
Outcome
Enterprise AI running entirely within your cloud perimeter. Never shared.
In-Tenant Cloud Deployment
We deploy full-stack AI architectures into your Azure subscription using Entra ID, Private Endpoints, Key Vault, and Azure AI Search. You retain 100% IP and data ownership.
Best fit
Organizations with strict data sovereignty, GDPR, or client NDA requirements.
Practice 2: AI Security, Governance & GRC
Outcome
Turn complex AI regulatory mandates into actionable, auditable engineering controls.
AI Governance Frameworks (NIST / ISO / EU)
We design tailored governance operating models crosswalked across NIST AI RMF, ISO/IEC 42001, and the EU AI Act. Includes intake gates, risk tiering, and board-level reporting.
Best fit
Enterprises preparing for AI compliance audits or managing high-risk automated decision systems.
Outcome
Uncover model vulnerabilities, prompt injections, and data leaks before production.
Adversarial Red Teaming & Guardrails
Hands-on adversarial testing aligned to the OWASP GenAI Top 10 and MITRE ATLAS. We build runtime guardrails, input/output inspection gates, and AST-level code validators.
Best fit
Teams deploying LLM applications, citizen developers, or agentic systems with access to critical APIs.
Outcome
Know exactly how third-party AI vendors handle, store, and train on your data.
Third-Party AI Vendor Risk Assessments
Comprehensive vendor due diligence using the CSA AI-CAIQ and NIST AI RMF. We provide scored risk reports, contract clause recommendations, and shadow AI discovery audits.
Best fit
Risk officers, legal counsels, and IT leaders evaluating generative AI SaaS solutions.
How it works
No drawn-out discovery. No 12-week onboarding. Three steps, one working prototype.
Discovery call
30 minutes. We map out exactly where your knowledge is stuck and what one good AI tool would unblock.
Pilot scope
One focused use case. A working prototype, not a roadmap deck. No 6-month contracts.
Ship to your tenant
Everything deploys into your Azure. You own the code, the data, and the infrastructure from day one.
Want to model costs or validate your AI maturity before booking? Run the TCO calculator or explore the free tools hub.
Consulting
Not looking for a vendor.
Looking for an engineer who gets it.
Applied AI Engineering led by Erblin Marku. AI Security & GRC delivered with our specialist partner practice. Book a 30-minute discovery call and let's map out your roadmap.
Book a Discovery Call →