Retrieval-Augmented Generation
AI & Retrieval
Grounded answers over a document set, where retrieval quality is the real bottleneck.
Retrieval-augmented generation: retrieving relevant documents and giving them to a language model as context, so an answer is grounded in a source rather than in recall.
How we use it
How the platform answers over a client corpus. Retrieval is treated as the bottleneck it usually is: a fluent answer over the wrong documents is the failure mode nobody notices.
8
systems
Case studies using this
Product-Safety Diagnostics for a Medical Group
An AI system that reads twenty thousand product records, extracts their ingredients, and tells a clinician whether a given product is safe for a given patient.
Cosmetics Safety and Labelling Compliance
A document pipeline that turns safety data sheets into structured, regulation-aware records. Including the labelling rules a human reviewer would otherwise apply by hand.
ForkTex Intelligence, One API for AI Capability
A capability-first AI platform: consumers ask for extraction, retrieval or transcription and never name a provider, so the provider can change without a rewrite.