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DataLinks is a platform that turns scattered data into structured knowledge that both humans and AI can actually use. Instead of forcing you to clean, reshape, merge, or premodel your data before you can start asking questions, DataLinks learns from your data as it is, builds structure where it is missing, and then gives you a simple way to explore and query it with clarity and confidence. This makes DataLinks a semantic knowledge platform. Your spreadsheets, CSVs, exports, PDFs, and structured systems become part of one unified knowledge network that humans can query over and AI can reason over without hallucinating or guessing. DataLinks follows three stages that work together as one workflow. DataLinks Ontology Diagram Ingest
The platform takes in your data from spreadsheets, databases, APIs, uploads, or files. During ingestion, DataLinks uses its cleanup and normalization layer to apply structure and meaning. Learn more about Ingestion and Cleaning. Interconnect
As soon as data is inside the platform, DataLinks automatically finds relationships between values across datasets. These relationships are stored as links. Together, these links form a knowledge map that reflects how your business entities relate in the real world. Learn more about Interconnection (Knowledge Maps). Inquire
Once your data is clean and connected, you can ask questions using natural language or by writing queries. DataLinks uses a lightweight language model to generate accurate structured queries based on the shape and relationships inside your data. The important detail is that the model is not inventing answers. It is using your data as truth. Learn more about Querying and Insights. DataLinks does not ask you to solve structure before you get value. It builds it with you. Most BI (business intelligence) systems require months of schema design before you can start asking questions. Most AI systems simply cannot reason over enterprise-scale data. DataLinks solves both issues by building a semantic layer based on actual data rather than hand-built modeling. Key differences between DataLinks and traditional solutions include:
  • It does not require you to predefine a schema
  • It discovers relationships instead of asking you to hard-code them
  • It uses an LLM as a reasoning layer, not as a source of truth
  • It prevents hallucination by forcing all model reasoning to reference real data
  • It works with messy real-world data rather than idealized warehouse data

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Vision

DataLinks is building a future in which knowledge is not locked inside specialized tools, departments or people. Data should not require SQL fluency or a data engineering team before you can ask a business question. The vision is a world where every employee is able to ask questions of the truth without worrying about where the truth lives. DataLinks exists to give organizations a semantic layer that makes enterprise data understandable by both humans and AI, so insight no longer depends on technical bottlenecks, modeling cycles, or dashboard backlogs. The goal is simple: turn organizational knowledge into something every person, and every AI agent, can use.

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Looking for platform access?

DataLinks is currently available to select partners and early users. To request access or join the waitlist, sign up for the waitlist.