Two practices, one standard. Product engineering for mobile, web and platform — and multimodal AI that connects what happened with why it happened. Every project below has a full case study.
Showing all 15 projects
Applications taken from early concept through to production software that a business runs on daily.
One connected system for a warehouse that ran on paper.
A mobile-first ERP for warehouse and e-waste operations that replaced a decade of spreadsheets, paper travellers and radio calls with a single connected system that works on the floor..
Market data, sentiment and research in one investment workspace.
An AI investment-intelligence platform that pulls market data, news sentiment and analyst research into a single workspace, so an investment team can go from a question to a defensible answer without leaving the screen..
Where candidates move, and where they stall.
A recruitment analytics platform that turns an applicant tracking system's raw event log into a picture of where a hiring funnel actually leaks, with the bottleneck named rather than left to be inferred..
Clinical translation where a wrong word has consequences.
A translation platform built specifically for clinical settings, where general-purpose translation is not safe enough and a verified medical dictionary sits between the model and the patient..
Encrypted mail with a wallet as the only identity.
An end-to-end encrypted email client where a wallet signature replaces the account entirely: no password, no recovery email, and no server that can read a message even if it wanted to..
Systems that correlate video, telemetry, documents and history to turn raw signal into answers you can check — each one carrying the evidence that produced it.
From defect detection to defect causality.
A multimodal system that correlates line video, machine telemetry, batch records and operator actions to explain why a defect happened, not merely that it did..
Not alarm detection. Failure hypothesis reduction.
A correlation engine that turns an alarm storm into a short ranked list of probable root causes by reasoning over network topology and fault propagation rather than alarm counts..
From a single inspection to longitudinal asset integrity.
A vision system that detects and localises pipeline deterioration, then tracks each defect across inspection cycles so maintenance is prioritised by progression rather than by appearance..
From deviation to evidence, with the audit trail intact.
A deviation investigation assistant that assembles batch records, equipment telemetry, inspection imagery, SOPs and historical deviations into an evidence-linked case file a quality unit can defend to a regulator..
From incident detection to incident prevention.
A vision system that models how people, vehicles and machinery move through a shared space, scoring emerging risk from trajectories and near misses instead of waiting for an incident to detect..
From document summary to document-to-document verification.
A verification engine that reads contracts, policies, procedures and regulatory text together and reports where they contradict each other, where evidence is missing and where an obligation has no controlling procedure..
From inspection image to defensible damage evidence.
An automated container and cargo inspection system that captures condition at entry and exit, classifies damage consistently, and produces an evidence package that stands up in a claim..
From box counting to continuous reconciliation.
A vision system that watches warehouse activity and continuously compares what is physically on the shelf against what the WMS believes, so discrepancies surface within hours instead of at the next stock count..
From road condition to maintenance priority.
A survey system that converts vehicle-mounted road imagery into per-segment condition scores, deterioration trends and a maintenance programme ranked by cost of deferral rather than by complaint volume..
From image finding to evidence-linked insight.
A clinician-facing decision support system that combines medical imaging, patient history and retrieved literature into findings a radiologist reviews, with the model positioned as a second reader rather than a decision maker..
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The patterns repeat: operational data, visual evidence, documents and history, correlated into answers. Tell us what you run and we will tell you what we would build.
