Forecasting, scoring, recommendations, vision and speech — models trained on your own operational data and deployed into the tools you already use. Scoped honestly, tested on real data before launch, monitored after.
Sales, demand, stock, staffing — from your own history. Reordering stops being a guess.
Lead scoring, churn risk, fraud flags — every case ranked automatically; your team reviews the top of the list.
Products, content, next actions — from real behavior, wired into your store or app.
Photos to listings, voice notes to structured data, invoices to records — the pipelines running on Rabta and Poshak today.
In production: Dastak's 'needs help' scoring model, Poshak's image generation pipeline, speech-to-text and vision on Rabta listings.
What can your data actually predict? We test before we quote.
Model built and measured against your real history. You see the accuracy number.
Into your stack via API; drift monitored; retrained when it matters.
A data audit and feasibility test comes first, quoted flat. Model build and deployment quoted after — fixed price, in writing.
Fixed scope, fixed price, quoted in writing after a 20-minute call. Operate layer (monitoring, retraining, extending) is optional and monthly.
Forecasting model on your sales history.
Scoring — review the top, not the pile.
Recommendation model, built and run for you.
The feasibility test answers that — sometimes with a no.
One call. A written scope, a fixed price, a date. Yours to keep either way.