We publish what we can verify.
Benchmarks, integration studies and methodology notes from Arvanord's engineering practice — with the same rule every time: stated methodology, careful language, no figures we cannot stand behind.
Where systems engineering meets AI reliability.
Arvanord is an engineering company, and our research follows the same constraint as our products: it has to survive production. That means the questions we spend time on are the ones that decide whether an AI system can be trusted with real work — not the ones that make the most interesting demos.
Four threads run through current engineering work: evaluation methods for systems whose correctness is hard to score; document intelligence in pipelines where errors propagate quietly; programmatic integration with professional design environments such as Revit, AutoCAD and Bluebeam; and reliability design for agents that operate with permissions and consequences.
This work is published pragmatically. Where a benchmark or study is complete enough to be useful, it appears here with its methodology — including the parts that limit how far it can be generalised.
- Evaluation methods for multi-step systems
- Document intelligence with validation and exception design
- CAD/BIM and engineering-document integration
- Agent reliability: guardrails, fallbacks, approvals
- Knowledge system governance and drift detection
- Human-in-the-loop workflow design
Methodology is a claim about how we work.
If a benchmark number matters to your decision, we will walk you through its exact methodology — including its limits. That conversation is usually the fastest way to judge whether we are the right engineers for your problem.