AI engineering in practice.
Real engineering. Measurable outcomes.
We publish case studies only once the client relationship, metrics and architecture can be described accurately. Until then, this page documents the structure we use and the internal and anonymised work we can discuss.
Every case study answers the same five questions.
Challenge
What operational problem existed?
System
What did Argbit engineer?
Architecture
How did it work?
Outcome
What measurable result occurred?
Engineering notes
What difficult technical problems were solved?
Internal and anonymised engineering.
No client logos, quotes or performance figures appear on this site until they are genuine and approved.
An orchestration runtime with typed tool contracts, per-run budgets and traces, built to support client engagements.
A CI-executed evaluation suite measuring task completion, escalation precision, latency distribution and cost per task.
A reference implementation for document intake, extraction and exception routing across multiple systems of record.
Want the technical detail rather than a case study?
We can walk through architectures, evaluation results and engineering decisions in a conversation, within the limits of client confidentiality.