Provides a platform for building, deploying, and scaling computer vision models tailored to specific industry tasks, such as object detection and optical character recognition. By integrating with tools like Snowflake, it enables organizations to perform visual AI tasks directly on their data without moving it, reducing deployment time by 80% and supporting over 1 billion annual image inferences with 99.99% uptime.
Funding
$57M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
PSFounders
Product
Problem
Many organizations struggle to efficiently build, deploy, and scale computer vision models tailored to their specific industry needs, often facing challenges related to data management, model performance, and integration with existing data infrastructure. This process can be time-consuming and require specialized expertise, hindering the adoption of visual AI across various sectors.
Solution
LandingAI provides a comprehensive visual AI platform designed to streamline the development and deployment of custom computer vision models. The platform offers tools for data labeling, model training, and deployment, enabling users to build high-performance models with minimal data. LandingLens on Snowflake allows organizations to perform visual AI tasks directly within their Snowflake environment, ensuring data governance and security. VisionAgent offers a pilot program for developers to explore visual AI capabilities, including model selection, code generation, and flexible deployment options.
Target Audience
The primary target audience includes organizations in industries such as automotive, electronics, food & beverage, medical devices, life sciences, agriculture, manufacturing, infrastructure, pharma, and semiconductor, as well as developers seeking to integrate visual AI into their applications.
Features
- End-to-end platform for labeling, training, and deploying custom vision models
- Integration with Snowflake for performing visual AI tasks directly on existing data
- Agentic Vision APIs for document extraction and object detection
- Accelerated MLOps for streamlined cycles and reduced time-to-value
- Enhanced model efficiency for superior performance with minimal data
- Simplified visual AI tooling to reduce engineering overhead
- Democratized AI implementation to boost innovation across the organization
- Label Assist tool for suggesting new labels and improvements to existing labels
- SQL-powered inference for running models on images using SQL commands