Tendering AI
Studies uploaded BOQs, specifications, and drawings to classify scope, map material and service categories, identify potential suppliers, and produce a tendering report designed for review by commercial teams.
Quotah Intelligence Layer
Three AI engines for contracting commerce.
Tendering AI, procurement AI, and supplier AI work together to interpret documents, recommend suppliers, structure decisions, and prepare cleaner commercial data.
Procurement AI
Supports requirement study, quotation comparison, supplier conversation context, approval preparation, and purchase order decisioning so procurement stays controlled after the tendering report.
Supplier AI
Classifies supplier products, organizes stock and catalog information, improves response readiness, and makes suppliers easier to evaluate for contractor requirements.
AI Philosophy
Quotah AI is built for preparation, not blind automation.
Construction decisions carry cost, schedule, and quality risk. Quotah AI is built to prepare intelligence, not make silent decisions.
It reads, classifies, compares, and organizes. Tendering and procurement teams still keep final control.
The more structured the contractor and supplier data becomes, the stronger matching, reporting, and procurement preparation become over time.
Human-led intelligence
The AI creates acceleration, structure, and clarity. The contractor and supplier teams remain the final authority on commercial decisions, approvals, and commitments.
AI Motion System
Three engines moving through one commercial path.
The AI Suite is easier to understand as a moving system: documents enter, supplier intelligence connects, procurement logic continues, and the final output becomes reviewable.
Tendering AIReads project packages.
Supplier AIOrganizes supply data.
Procurement AIStudies responses.
InterpretBOQ, specs, drawings, and quantities.
ConnectSupplier categories, stock, and capability.
PrepareReports, comparisons, and next actions.
Designed for human approval.
Quotah AI accelerates preparation, comparison, and organization while keeping final commercial decisions inside the contractor and supplier teams.
A
Explainable Reports
Recommendations are organized into practical report sections that teams can review and challenge.
B
Operational Memory
Commercial context from tendering can continue into procurement instead of being lost between departments.
C
Market Fit
The AI layer is shaped around contracting requirements inside Saudi Arabia, not generic marketplace shopping.
What each AI engine understands.
The intelligence layer is separated by job, so each engine can focus on the kind of decision it is meant to support.
Scope interpretation
Tendering AI looks at BOQ lines, specification language, drawing context, quantities, and scope relationships to understand what the contractor is actually trying to buy or subcontract.
Commercial comparison
Procurement AI helps structure differences between supplier responses, including pricing context, missing items, lead time concerns, alternative options, and decision notes.
Supplier classification
Supplier AI organizes product data, category names, stock indicators, and supplier capabilities into a cleaner commercial profile that can be matched with project requirements.
Report generation
The AI output is shaped as a business report: readable, reviewable, and useful for tendering teams, procurement teams, project managers, and executives who need the logic behind a recommendation.