Compare Taiki vs. Unsiloed

Taiki presents a versatile API that automates the process of extracting tax documents and associated data from a variety of payroll and financial service providers. With this innovative solution, users can eliminate the need for manual document uploads by securely linking to numerous financial platforms, thus simplifying the retrieval of essential tax information. The API is capable of handling an extensive array of documents, such as 1040s, W-2s, 1099s, and bank statements, among others. Users benefit from built-in document processing, allowing them to request and obtain only the specific data fields they need, which significantly enhances efficiency in data collection. Taiki's integration features cover a wide range of financial institutions and services, including notable names like ADP, Bank of America, PayPal, and TurboTax, providing users with a comprehensive solution to meet their varied requirements. The platform also offers adaptable pricing structures, including options for pay-as-you-go and annual subscriptions based on user count, catering to both individual and corporate clients alike. Additionally, the implementation process is designed to be quick and user-friendly, ensuring a seamless experience from the outset.

Unsiloed AI is an enterprise document intelligence platform built to transform unstructured documents into structured, LLM-ready data. The platform processes PDFs, images, spreadsheets, scans, and multimodal files, then outputs clean JSON, Markdown, or structured fields for AI agents, LLM applications, vector databases, and data warehouses. Its core capabilities include parsing, extraction, and document splitting, allowing teams to use each function independently or chain them into a full production pipeline. Unsiloed’s parser converts complex documents into Markdown while preserving structure across text, tables, charts, figures, forms, handwriting, signatures, and visual hierarchy. Its extraction engine pulls schema-specific fields into JSON and uses domain awareness to understand documents such as invoices, contracts, financial reports, healthcare records, and regulatory filings. Its splitting tools can separate mixed files into individual documents or break long documents into retrievable chunks while preserving parent-child relationships and surrounding context. The platform is powered by proprietary dual-stream vision models that combine a data stream for tokens and entities with a layout stream for bounding boxes, alignment, indentation, and visual structure. Unsiloed is designed to solve the problem of fragile OCR and DIY pipelines that break when document layouts change. For enterprise AI teams, Unsiloed provides a more reliable document layer for turning high-value unstructured data into assets that can be searched, reasoned over, and used in production AI systems.