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Engineers stop searching across fragmented PDFs and outdated revisions.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.
In-Tenant Azure Architecture Explorer
Explore how Adlor Labs deploys directly inside your enterprise Azure subscription. No multi-tenant clouds, zero shared data, and 100% customer-owned IP.
Governed AI Microservices
Hosts Adlor Gate (Port 8001) and Adlor RAG API (Port 8000) inside an isolated Container Apps environment. Internal ingress only—no public IP addresses exposed.
infra/azure/main.bicepIn-Tenant Azure vs. Commercial SaaS TCO Calculator
Engineering Team Size
Engineers using AI for standards, BIM & code
Monthly AI Queries / User
Standards lookups, AST code checks, P&ID parsing
Engineering Standards & Manuals
Ingested PDFs, API codes, ASME manuals, Revit specs
Equivalent to £80,730 in 3-year TCO savings with 100% data sovereignty.
Executive AI Infrastructure Business Case & TCO Report
Source: Adlor Labs Financial Model (https://adlor-lab-platform.vercel.app/resources/tco-calculator)
The Labs — demystified
Each lab is a real, working tool. Here's what it actually does and how to use it.
adlor-knowledge
LiveWhat it does
Your firm's brain. Search standards, procedures, and revisions with AI. Ask a question. Get the clause, source, and confidence score.
How to use it
- 1Connect your documents (PDF, Word, SharePoint).
- 2Ask in plain English.
adlor-gate
Open SourceWhat it does
Guardrails for AI code. Checks naming conventions. Bans bad patterns. Scans for secrets. Runs inside Claude and Cursor.
How to use it
- 1Drop the YAML policy into your repo.
- 2Point your MCP client at the server.
Revit Standards QA
LiveWhat it does
Connect Revit models to your standards. Run an audit. Flag elements that fail HSE, API 610, or OSHA rules. Review and sign off.
How to use it
- 1Load a BIM model.
- 2Pick a ruleset and audit.
project-doc-intel
BetaWhat it does
P&ID document intelligence. Extracts tags and equipment lists. Validates them against API 610 and HSE standards. Finds the gaps.
How to use it
- 1Upload a P&ID drawing.
- 2Extract entities and run standard validation.
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.
Consulting
Not looking for a vendor.
Looking for an engineer who gets it.
We have extensive experience in engineering delivery, cloud systems architecture, and AI risk governance. Book a 30-minute discovery call and let's map out your roadmap.
Book a Discovery Call →