DXYFER

DXYFER is an agentic AI platform with three modules: Ask Data for plain English database queries, Auto Dash for interactive dashboards, and Ask Docs for document Q&A. It targets business decision makers who want traceable insights without SQL or analyst support.

DXYFER (pronounced de.cipher) is a web based augmented intelligence platform built around three agentic modules that sit in front of an organisation's data and document estate. The first, Ask Data, lets a user type a question in ordinary language and receive analysis and visual output drawn directly from a connected database, with no SQL authoring on the user's side. The second, Auto Dash, turns those answers into interactive dashboards that surface trends for monitoring and governance. The third, Ask Docs, extends the same question and answer pattern to document repositories rather than structured tables. The product is aimed at decision makers rather than analysts: executives, operations leads and finance or commercial teams who need fast answers but do not want to queue work through a data team or learn a query language. The homepage makes the point explicitly, framing adoption as requiring no training and no infrastructure liability. Answers come with referencing so a figure can be traced back to its source, which matters for anyone presenting numbers in a board pack or audit context. In practice the platform works as a layer above existing systems. DXYFER states that it connects to information repositories, ERP platforms and cloud based systems, and its AI/ML architecture is described as handling large and varied data volumes. Security is positioned as a design principle rather than an add on: governance rules, access controls and auditability are built in, and the vendor offers a supporting FAQ covering data protection. Where DXYFER competes is the crowded natural language analytics space, alongside text to SQL assistants and BI tools that have bolted on a chat interface. Its differentiator is the decision to bundle structured data queries and document queries in one secure agentic layer, which suits organisations that want a single front door to both. Buyers who need published per seat rates, a public integration list or transparent onboarding documentation will not find them on the homepage, so a sales conversation is required before committing.