Corti Tech Stack

Enterprise AI models for clinical decision support via API

Software Development Brooklyn, New York 51–200 employees Founded 2016 Privately Held

Corti builds healthcare-specific AI models (PyTorch, TensorFlow) deployed on multi-cloud infrastructure (Azure, AWS, GCP) with heavy focus on model serving (NVIDIA Triton, vLLM, FastAPI) and observability (Grafana, Loki, Tempo). Engineering-dominant hiring (16 of 25 roles) skews senior, and active projects span speech recognition, ML feature development, and Kubernetes multi-tenancy — indicating a company scaling inference workloads and wrestling with clinical-grade reliability at concurrent throughput.

Tech Stack 26 technologies

Core StackPython PyTorch TensorFlow Go Kubernetes Loki Grafana Docker AWS MLflow Kubeflow GitHub Actions ArgoCD FastAPI Apache Kafka Tempo Mimir Azure GCP DVC Drata vLLM NVIDIA Triton Inference Server

AdoptingGitOps Replit Model Context Protocol

What Corti Is Building

◆Challenges

Medical knowledge growth outpacing human capacity
Removing friction in technical onboarding
Clinicians overwhelmed
Lack of access to quality healthcare
Maintaining audit readiness
Accelerating technical activation
Increasing access to medical expertise
Scaling infrastructure for high concurrency
Maintaining multi-tenant cluster reliability
Reducing api integration issues

▲Active Projects

Technical onboarding
Maintain corti security governance model
Prototype new ml-based product feature
Adapt cutting-edge research to healthcare domain
Api platform integration
Customer journey optimization
Speech recognition and text generation backend
Automation improvements
Automation tools for dev ops
Multi-tenant kubernetes setup

Hiring Activity

Steady25 roles · 10 in 30d

Department

Engineering

Security

Sales

Marketing

Product

Support

Seniority

Senior

Mid

Staff

Lead

Intern

Company intelligence

Find more companies like Corti by tech stack, pain points and active projects

Get started free

About Corti

Corti develops enterprise-grade AI models for healthcare delivery, distributed as managed API services. The product targets clinical workflows where decision support and automation reduce clinician cognitive load. The company operates across the United States, Denmark, and the United Kingdom. Core technical challenges center on scaling inference infrastructure for high concurrency, maintaining audit readiness in regulated environments, and reducing friction in customer API integration. Active work on speech recognition and text generation pipelines suggests expansion into multimodal clinical data.

HeadquartersBrooklyn, New York

Company Size51–200 employees

Founded2016

Hiring MarketsUnited States, Denmark, United Kingdom

Frequently Asked Questions

What tech stack does Corti use?

Python, PyTorch, TensorFlow, Go, Kubernetes, NVIDIA Triton, vLLM, FastAPI, Apache Kafka, with observability via Grafana, Loki, Tempo. Hosting spans Azure, AWS, and GCP. MLflow and Kubeflow manage model lifecycle.

What is Corti working on?

Speech recognition and text generation backends, multi-tenant Kubernetes infrastructure, new ML-based product features, API platform integration, and technical onboarding automation to reduce customer implementation friction.