LandingAI

Computer-vision and document-AI platform (LandingLens, Agentic Document Extraction) applicable to pharma visual inspection and document processing.

LandingAI, founded in 2017 by Andrew Ng and headquartered in Palo Alto, California, provides LandingLens for building computer-vision inspection models and Agentic Document Extraction for turning complex documents into structured data. It documents SOC 2 Type II, HIPAA, and GDPR compliance on its own security pages. It is a cross-industry AI platform rather than pharma-specific software, so validate GxP fit, validation support, and pharma references for regulated manufacturing use during evaluation.

Headquarters
Palo Alto, United States
Founded
2017
Compliance
SOC 2 Type II, HIPAA, GDPR
Deployment options
cloud
Website
https://landing.ai
LinkedIn
https://www.linkedin.com/company/landingai

Categories

AI Use Cases

  • Manufacturing Quality Control

Vendor Scorecard

71% — Complete coverage. Coverage score — how completely Atlas documents LandingAI across 7 buyer-evaluation areas. Reflects available Atlas data, not solution quality.

Compliance & Validation — Documented

SOC 2 Type II, HIPAA, GDPR

Deployment & Hosting — Documented

cloud

Pricing Transparency — Not documented by Atlas

Ask the vendor: What is your pricing model, and what drives total cost of ownership?

Implementation & Onboarding — Not documented by Atlas

Ask the vendor: What is a realistic implementation timeline, and what onboarding support is included?

Organization & Role Fit — Documented

Biotech Startup, Mid-Size Biotech, Large Pharma, IT / Digital, Data Engineer / Architect

Solution Scope — Documented

Natural Language Processing

Company Viability — Documented

Series B, $57.0M raised, Founded 2017

Always ask the vendor

Not captured in Atlas data — confirm directly. Excluded from the score above.

Data Rights & IP

Who owns model outputs? Is our proprietary data used to train models others can access, and where does our data reside?

Model Credibility & Explainability

Can you share validation studies or benchmarks, explain how the model reaches its conclusions, and describe how bias and drift are monitored?

Questions to Ask This Vendor

  • What pharma manufacturing references exist for LandingLens?
  • How would the platform fit a GxP-validated inspection process?
  • Can models run on-line/edge for production inspection speeds?
  • What data residency options exist for document extraction?