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Description
DataChain serves as a bridge between unstructured data found in cloud storage and AI models alongside APIs, facilitating immediate data insights by utilizing foundational models and API interactions to swiftly analyze unstructured files stored in various locations. Its Python-centric framework significantly enhances development speed, enabling a tenfold increase in productivity by eliminating SQL data silos and facilitating seamless data manipulation in Python. Furthermore, DataChain prioritizes dataset versioning, ensuring traceability and complete reproducibility for every dataset, which fosters effective collaboration among team members while maintaining data integrity. The platform empowers users to conduct analyses right where their data resides, keeping raw data intact in storage solutions like S3, GCP, Azure, or local environments, while metadata can be stored in less efficient data warehouses. DataChain provides versatile tools and integrations that are agnostic to cloud environments for both data storage and computation. Additionally, users can efficiently query their unstructured multi-modal data, implement smart AI filters to refine datasets for training, and capture snapshots of their unstructured data along with the code used for data selection and any associated metadata. This capability enhances user control over data management, making it an invaluable asset for data-intensive projects.
Description
Tensorlake serves as a cutting-edge AI data cloud that efficiently converts unstructured data into formats suitable for AI applications. It adeptly transforms various content types, including documents, images, and presentations, into structured JSON or markdown segments that facilitate easy retrieval and analysis by large language models. The document ingestion APIs are capable of handling a wide range of file types, from handwritten notes to PDFs and intricate spreadsheets, while executing post-processing tasks such as chunking and preserving the original reading order and layout. With its serverless workflows, Tensorlake provides rapid end-to-end data processing, empowering users to create and implement fully managed Workflow APIs in Python that can scale down to zero when not in use and seamlessly scale up during data processing tasks. Additionally, it is designed to process millions of documents simultaneously, ensuring that context and interrelations among different data formats are preserved, while also offering robust, role-based access control to enhance team collaboration. This flexibility and efficiency make Tensorlake an invaluable tool for organizations looking to streamline their AI data preparation processes.
API Access
Has API
API Access
Has API
Integrations
Python
Claude
Codestral
Codestral Mamba
GPT-4o
Gemini
Gemini 1.5 Flash
Gemini Advanced
Gemini Pro
Google Cloud BigQuery
Integrations
Python
Claude
Codestral
Codestral Mamba
GPT-4o
Gemini
Gemini 1.5 Flash
Gemini Advanced
Gemini Pro
Google Cloud BigQuery
Pricing Details
Free
Free Trial
Free Version
Pricing Details
$0.01 per page
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
iterative.ai
Founded
2018
Country
United States
Website
datachain.ai/
Vendor Details
Company Name
Tensorlake
Website
www.tensorlake.ai/
Product Features
Product Features
Data Extraction
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction