Customers
Anonymised by design. Every name and identifier is withheld; outcomes are reproduced from working-session evidence.
Each engagement is anonymised per our disclosure policy.
Embedded AI R&D function across the UK–HK–GBA corridor.
A Series-A-stage UK biotech developing a lead antibody asset.
What we do
Embedded AI Ab-engineering function — sequence mining → cryo-EM-informed → AI-designed shortlist; wet-lab validation feeds the model.
Outcome
Antibody-optimisation rounds compressed from ~3 months to ~3 weeks per round, sustained across multiple campaigns.
A HK-based pharma R&D partner working on novel-modality therapeutics (cyclic peptides / constrained binders).
What we do
Closed-loop platform deployment — generative design + multi-stage scoring + wet-lab feedback.
Outcome
Active multi-phase paid engagement; first commercial deployment of the closed loop on a novel modality.
A HK enterprise-AI infrastructure partner entering the biomedical vertical.
What we do
Joint platform-on-platform deployment template — abYcloud's agentic decision layer over the partner's on-premise GPU + IoT substrate.
Outcome
Joint pilot scope agreed, four parallel tracks defined.
“What used to be a three-month optimisation round, our team is now turning around in roughly three weeks. That speed has changed how we plan our wet lab — we're no longer batching everything to the next quarter.”
Patient-data-grounded therapeutic shortlists, automated for clinical-research teams.
A clinical-research collaboration at a major HK university hospital (ESMO-designated cancer centre).
What we do
Agentic-SaaS pipeline that turns patient RNA-seq into a therapeutic-options shortlist for clinical-research staff.
Outcome
End-to-end RNA-seq-to-shortlist compressed from ~4–6 weeks (manual) to hours-to-1 week (automated).
“If we can automate the whole RNA-seq workflow so it finishes in hours, or at most a week, that's genuinely a step-change for our research. It frees us to focus on the scientific question rather than the technical scaffolding.”
