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Relation Tech Stack

Biotech drug discovery platform integrating single-cell analysis, genomics, and ML

Biotechnology Research London 51–200 employees Founded 2019 Privately Held

Relation pairs wet-lab biology (single-cell and multi-omics measurements from patient tissue) with machine learning and clinical data to identify and validate drug targets. The tech stack is modern infrastructure (Kubernetes, Terraform, ArgoCD) with heavy adoption of NVIDIA — pointing toward GPU-accelerated computational biology. Hiring velocity is accelerating across data (6 open roles) and research (5), while the active project list reveals they're scaling both ML pipelines and a hybrid on-prem/cloud environment, suggesting infrastructure constraints are limiting discovery speed.

Tech Stack 11 technologies

Core StackKubernetes GitHub Actions ArgoCD Terraform Linux Slack Windows macOS Google Workspace Microsoft 365

AdoptingNVIDIA

What Relation Is Building

◆Challenges

Target identification and validation
Scaling technology and discovery teams
Optimizing hybrid on-prem/cloud environment
Expanding computational talent
Assessing external opportunities
Expanding into chinese biotech market
Identifying partnership opportunities
Monitoring market shifts
Scaling ml systems
Handling large datasets and complex models

▲Active Projects

Multi-omics data integration for drug target discovery
Target identification and validation
Hybrid on-prem/cloud environment optimisation
Osteoporosis programme
Gsk fibrosis collaboration
Training and inference pipelines
Dcf and forecast modeling for portfolio assessment
Competitive intelligence market landscaping
Search and evaluation of assets and potential partnerships
Ml system development and deployment

Hiring Activity

Accelerating20 roles · 10 in 30d

Department

Data

6

Research

5

Sales

3

Engineering

2

Ops

2

Communications

1

Support

1

Seniority

Mid

8

Senior

6

Director

2

Principal

2

Junior

1

Lead

1

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About Relation

Relation is a London-based biotech founded in 2019, developing medicines from patient-derived tissue using high-resolution biology and machine learning. The company operates an end-to-end model: extracting single-cell and multi-omics data directly from patient samples, running functional assays, applying ML to identify disease mechanisms, and advancing selected targets into drug development. Active programs include an osteoporosis therapy and a fibrosis collaboration with GSK. The 51–200-person team spans research, data science, engineering, and commercial functions, with recent hiring concentrated in data and research roles.

HeadquartersLondon

Company Size51–200 employees

Founded2019

Hiring MarketsUnited Kingdom

Frequently Asked Questions

What is Relation's tech stack?

Kubernetes, Terraform, ArgoCD, GitHub Actions for infrastructure; Google Workspace and Microsoft 365 for collaboration. NVIDIA adoption signals GPU infrastructure for computational workloads. No legacy data warehouse stack detected.

What is Relation working on?

Multi-omics data integration for drug discovery, target validation, ML training/inference pipelines, and hybrid cloud/on-prem infrastructure optimization. Active programs: osteoporosis development and GSK fibrosis collaboration.