A
Aignostics Tech Stack
AI diagnostics platform for pathology and precision medicine drug development
Aignostics builds AI models for pathology analysis in drug discovery and clinical trials, with a technically mature stack spanning Python, C++, CUDA, and Kubernetes. The engineering-heavy org (21 of 27 hires) is scaling distributed training infrastructure and data pipelines for medical images, while active pain points around data infrastructure, model transparency, and ISO 13485 compliance reveal the operational friction of moving AI diagnostics into regulated clinical use.
Tech Stack 15 technologies
Core StackPython Java Rust GitLab AWS Kubernetes React Next.js C/C++ CUDA Argo Workflows GCP Cloud Run IAM VPC
AdoptingKubernetes
What Aignostics Is Building
◆Challenges
- Lack of transparent model development
- Large scale medical image data infrastructure
- High quality data access
- Maintaining iso 13485 certification
- Scaling data intensive services
- Secure cloud foundation
- Protect sensitive healthcare data
- Optimizing cloud costs
- Lack of high-quality data
- System observability
▲Active Projects
- Build data infrastructure services
- Scale data intensive services
- Distributed training infrastructure for digital pathology
- Ai platform architecture
- Platform security implementation initiatives
- Public api & integrations
- Change management process implementation
- Capa system development
- Kubernetes cluster architecture
- Model training and inference frameworks for pathology
Hiring Activity
Minimal25 roles · 1 in 30d
Department
Seniority
Notable leadership hires: Machine Learning Team Lead
Company intelligence
