Skip to content
DATA ELYSIUM
AZURE AI ENGINEERING · CALGARY, CANADA

Agentic AI, from prototype to production on Azure.

We design, ship, and harden enterprise AI systems — RAG, multi-agent workflows, observability, and security to Azure standards.

Built on frontier-lab evaluation & RLHF experience.

trajectory analysis · illustrativeLIVE
tool-call accuracy96.4%
groundedness (RAG)98.1%
flagged trajectories12 · in review
FRONTIER-LAB EXPERIENCE
2+ yrs
RLHF & agent evaluation at scale
IN PRODUCTION
18,000+
users on systems we built & operate
MICROSOFT CERTIFIED
Azure AI
Engineer · security & architecture practice
SERVICES

Two ways we engage.

Whether you're shipping agents into an enterprise or building the data that trains them, the work is held to the same evaluation bar.

01DELIVERY

Enterprise Agentic AI on Azure

From a working prototype in weeks to a hardened production system — on your Azure tenant, to your compliance bar.

  • 01Rapid prototyping · feasibility sprints, working system in weeks
  • 02RAG on Azure · AI Search, AI Foundry
  • 03Multi-agent workflows · LangGraph, Agent Framework
  • 04Observability · tracing, evaluation telemetry, cost control
  • 05Security & privacy · Entra ID, Azure best practice
  • 06Productionizing · Azure DevOps CI/CD, go-live
Azure OpenAIAI SearchAI FoundryEntra IDApp InsightsAzure DevOps
Discuss a build
02EVALUATION

Agent Evaluation, Datasets & RLHF

The discipline we practiced inside frontier-model labs, applied to your agents and models.

  • 01Benchmark datasets · design & creation for agent tasks
  • 02Human data for agents · high-quality trajectories, preferences, rubrics
  • 03Trajectory analysis · failure taxonomies, root-cause
  • 04Eval pipelines · SxS, factuality, safety, regression gates
  • 05RLHF / RLAIF · alignment loops, reward data
  • 06LLM-as-judge · design & calibration against human labels
RLHFTrajectoriesBenchmarksLLM-as-judgeSxS
Talk about eval data
METHOD

Evaluation-gated delivery.

STEP 1

Prototype

A working system on your data in weeks, not quarters.

STEP 2

Evaluate

Benchmarks and trajectory analysis prove it works before it ships.

STEP 3

Productionize

Azure DevOps, security review, observability — then go-live.

WORK

Systems we build and operate.

Affortable AI

LIVE · 18K+ USERS

Pay-as-you-go AI platform: frontier models, image tools, and APIs. Built, operated, and scaled by us in production.

affortable.ai

Case study

IN PROGRESS

Enterprise RAG on Azure — coming soon.

Case study

IN PROGRESS

Agent benchmark dataset — coming soon.

ABOUT

Engineering-led, evaluation-obsessed.

Data Elysium is a Calgary-based AI engineering firm founded by Md Alamin — a software engineer who spent two years evaluating and aligning frontier models before building agentic systems for enterprises. Every engagement is led hands-on by the founder.

CREDENTIALS

  • Microsoft Certified: Azure AI Engineer
  • Generative AI Specialist (RLHF & code generation), Scale AI · 2023–2025
  • Software Engineer, Samsung R&D — Chromium web engine, 50+ upstream contributions
  • MSc Software Engineering, University of Calgary
  • Published researcher — 7 papers, 400+ citations
  • Azure security & solution-architecture practice
CONTACT

Start with a conversation.

Tell us what you're trying to build — or what you need evaluated. We reply within one business day.