Technical Knowledge Assistant (RAG)
Ask a question about your own field in Persian, Arabic, English or Spanish and get an answer with the report and page it came from.
Understands log images, maps and cross-sections alongside text, so you can ask a question about a figure rather than only about a paragraph.
A large share of subsurface knowledge lives in figures: log displays, structure maps, seismic sections, core photographs. Text-only retrieval is blind to all of it, and the figure caption is rarely enough.
Vision-language models index figures alongside text, with domain-specific handling for log tracks, map annotations and section displays. Answers reference the specific figure and region, and the system is deliberately conservative about reading values off a plotted curve.
Reading precise numeric values off a plotted curve is unreliable and we do not present it as a feature — the model locates and describes figures rather than digitising them. Scan quality is the binding constraint: a low-resolution scan of a log display is unreadable to the model for the same reason it is unreadable to a person.
Every capability page states a real limitation. If a vendor cannot tell you where their product stops, you are not being told the truth about where it starts.
Ask a question about your own field in Persian, Arabic, English or Spanish and get an answer with the report and page it came from.
Picks faults and horizons across a full seismic volume in hours, leaving the interpreter to judge rather than to click.
Measures porosity, grain size and fracture density from core photographs and CT scans instead of from a description written twenty years ago.
A model further trained on petroleum engineering text, so it uses the field’s vocabulary correctly in Persian and Arabic as well as English.