VideaHealth Tech Stack

AI dental assistant platform for DSOs and practices

Software Development Boston, Massachusetts 51–200 employees Founded 2018 Privately Held

VideaHealth deploys deep learning models (PyTorch, TensorFlow, Keras) for dental condition detection into AWS/Azure/GCP production, now adopting GPT for custom agent workflows. The stack reveals a company investing heavily in ML infrastructure—model versioning, monitoring tools, and data lake expansion appear across active projects—while simultaneously building sales and go-to-market automation to scale pilot deployments to GA. Senior hiring dominance (21 of 36 open roles) suggests they're backfilling leadership and IC depth in engineering as they shift from research prototype to regulated medical device at scale.

Tech Stack 46 technologies

Core StackAWS Node.js Python TypeScript HubSpot Salesforce React Jest JavaScript Zendesk Jira Slack Confluence PyTorch TensorFlow GitHub Java C# Azure GCP SQL PartnerStack Crossbeam LinkedIn Sales Navigator JavaScript/TypeScript Puppeteer REST API JSON Web Token Google Workspace Keras+15 more

AdoptingGPT

What VideaHealth Is Building

◆Challenges

Patchwork of disconnected tools
Extending existing data lake capabilities
Scaling top-of-funnel growth systems
Compliance with global medical device regulations
Deploying versioned machine learning models at scale
Automating high-velocity workflows
Scaling engineering efforts
Ensuring reliable, scalable systems
Expanding partner ecosystem
Scaling pilot to ga

▲Active Projects

Deploy versioned machine learning models at scale
Advance platform deployment automation
Extend existing data lake capabilities
Model monitoring tools
Deep learning pipeline for dental condition detection
Post-market surveillance inputs and trending
Build custom gpt agents
Platform replacing patchwork of disconnected tools
Capa initiation and effectiveness
Develop roi calculators

Hiring Activity

Decelerating35 roles · 6 in 30d

Department

Engineering

Sales

Support

Marketing

Healthcare

Product

Quality

Seniority

Senior

Mid

Director

Manager

Lead

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About VideaHealth

VideaHealth builds an AI-powered dental assistant platform for dental service organizations and independent practices. The product layers machine learning (dental condition detection, patient engagement) on top of a cloud infrastructure spanning AWS, Azure, and GCP, integrated with practice management workflows via HubSpot and Salesforce. Founded in 2018 and rooted in research from Harvard and MIT, the company operates across two locations—Boston headquarters and New York office—and serves the nation's largest DSO networks. Current operational priorities center on deploying versioned ML models reliably, extending data lake capabilities to support model improvements, automating platform deployments, and scaling regulatory compliance (post-market surveillance, CAPA initiation) as a medical device vendor.

HeadquartersBoston, Massachusetts

Company Size51–200 employees

Founded2018

Hiring MarketsUnited States, United Kingdom

Frequently Asked Questions

What AI technologies does VideaHealth use?

VideaHealth uses PyTorch, TensorFlow, and Keras for deep learning pipelines. The platform is now adopting GPT for custom agent workflows. Models deploy across AWS, Azure, and GCP with active work on versioning, monitoring, and scaling infrastructure.

What are VideaHealth's biggest operational challenges?

Key challenges include deploying versioned ML models at scale, extending data lake capabilities, scaling engineering efforts, compliance with medical device regulations (post-market surveillance, CAPA), and automating high-velocity workflows to move pilots to GA.