We build AI into systems that already have owners, permissions and consequences — where an output has to be explainable months later, and a person has to answer for it.
The model is the small part. The work is the data boundaries, the evaluation, the escalation path when confidence is low, the access controls, the versioning, the monitoring, and the way back when something goes wrong.
We are an engineering team rather than an AI advisory. We build the system and it goes into production.
Miros is AI product discovery for e-commerce: it reads shopper intent from behaviour rather than keywords. Our work is the matching and the orchestration of the different AI models behind it — which model runs when, on what, and what happens to the result.
Orchestration is where most production AI actually lives. One model rarely does the whole job, and the seams between them are where quality is won or lost.
Extract and compare document data, identify potential fraud signals, and route low-confidence or exceptional cases to a human reviewer. The routing matters as much as the extraction — a system that quietly guesses is worse than one that asks.
Answers grounded in approved policies, procedures and data, with cited sources, existing access controls and appropriate activity logging. An assistant that can reach what its user cannot is not a feature.
We use AI where it removes manual reading and sorting, and leave the decision with the person who has to sign for it. Escalation paths are designed in from the start, not bolted on after somebody complains.
Around that: versioned models and prompts, evaluation datasets, approvals, monitoring, and durable records of inputs, retrieved sources and outputs.
Most banks have seen an AI demo. The harder part is putting AI into production where material outputs must remain traceable, reviewable and defensible long after launch.
We bring the engineering discipline developed through identity, signature and payment systems, where reliability and auditability are design requirements rather than later additions.
AML alert triage is a common starting point: prioritise alerts and reduce analyst workload while preserving the supporting evidence and rationale, with decisions to suppress, escalate or close following bank-approved rules and remaining available for review.