Emly.Labs

The chatbot builder answers from documents you supply, using retrieval augmented generation to pull the matching passage before it writes a reply. Emly Labs markets the setup as hallucination free, and the mechanism is the usual one: a model that only speaks from retrieved text has less room to invent. You get an embeddable widget, brand controls for colors and layout, and a conversation analytics view. The analytics matter more than they sound, since they show which questions your knowledge base still fails to cover.

AutoML preprocesses the data, tries candidate algorithms, tunes parameters, and scores the results without you writing code. It covers classical methods such as gradient boosting alongside deep learning frameworks. Deep learning is reserved for the $399 plan and up. Model interpretability tools show which inputs moved a prediction, which is the part a compliance reviewer will ask about. Reports can be downloaded as PDF or shared inside the workspace.

DataLab treats data preparation as a grid of steps rather than a script. You join tables, fill or drop missing values, derive columns, and enrich records, then save the whole sequence as a reusable pipeline. Emly Labs claims the engine handles billions of rows, and the practical benefit shows up on repeat work: next month's file runs through the same pipeline in one click. An insights engine flags columns worth a second look before you train anything.

Models trained only on internal history tend to learn the past too well. The X-Data catalogue adds third-party datasets such as weather, footfall, or economic indicators, and the platform documents how each one was collected. This is the feature that separates a demand forecast that tracks reality from one that tracks last year's spreadsheet. Third-party integration is listed as a Professional plan capability.

Vizard builds charts from your model output and your raw tables, with automated chart selection and filtering. The point isn't prettier slides. A maintenance model that flags an asset is only useful if a supervisor can see the flagged asset, the sensor readings behind it, and the trend line in one view. Dashboards are included from the Essential plan upward.

Hub is the layer that keeps a project from dying in a notebook. It holds versioned workflows, team roles, data access policies, compute instance controls, and the path from model to microservice. Deployment options run from a hosted environment to your own virtual cloud or on-premises hardware on Enterprise. Control APIs let other systems trigger a model run without a person clicking anything.