Check supplier certificates and licences
Check supplier certificates and licences with SpiderNet: a practical, on-prem approach built for Azerbaijani teams.
AI-Driven Supplier Intelligence and SOW Matching
SpiderNet is a sophisticated AI supplier intelligence and SOW matching platform designed specifically for procurement teams to optimize the pre-sourcing phase. By operating at the critical stage before suppliers are invited to a sourcing event, the platform transforms how organizations identify and qualify vendors. It ingests a diverse array of documentation—including PDFs, DOCX, XLSX, scanned files, and free text—supporting Azerbaijani, Russian, English, or mixed-language inputs. The system meticulously extracts structured requirements, mapping them by type, importance, and taxonomy, while providing precise citations to the original document, section, and page to ensure complete transparency. At its core, SpiderNet maintains 'Golden Records' for suppliers, aggregating identity, capabilities, qualifications, and performance signals. Unlike traditional databases, the platform employs a rigorous five-layer matching process—combining mandatory filters, taxonomy matching, semantic retrieval, LLM evidence assessment, and weighted scoring—to produce a highly accurate shortlist. By treating AI-inferred data as unverified and requiring human confirmation for exclusion rules, SpiderNet eliminates the risk of silent exclusions and ensures that procurement decisions are based on evidence-backed intelligence rather than algorithmic assumptions.
Strategic Advantages for Procurement Compliance
Eliminate silent exclusions by surfacing information gaps as actionable data points rather than automatic rejections.
Guarantee ranking neutrality through an architectural constraint that prevents supplier-side monetization from influencing qualification or scoring.
Accelerate the qualification cycle by automating the extraction of mandatory and optional criteria from complex SOWs.
Maintain superior data integrity by tagging every material attribute with source, date, and verification status, ensuring AI-inferred data is never treated as verified fact.
Expand the candidate pool via agentic discovery that scans public registries, accreditation records, and company websites.
Support global and local operations with native processing of Azerbaijani, Russian, and English language documentation.
Core Verification Capabilities
Multi-Format Ingestion
Process PDF, DOCX, XLSX, scanned documents, and free text to extract structured requirements with citations to specific pages and sections.
Supplier Golden Records
Centralized storage for identity, qualifications, certifications, experience, and risk indicators for every supplier.
Agentic Discovery
Automatically widen the candidate pool by searching approved directories, public registries, and company websites.
Five-Layer Matching
A rigorous evaluation process combining mandatory filters, taxonomy matching, semantic retrieval, LLM evidence assessment, and weighted scoring.
Evidence-Based Shortlisting
A comprehensive matrix showing requirement-by-requirement evidence, gaps, contradictions, and risk flags.
The Verification Workflow
Frequently Asked Questions
How does the system handle missing information in supplier certificates?
Unknown information is surfaced as a gap rather than resulting in a silent exclusion, allowing procurement teams to identify missing data and request it from the vendor.
Is AI-generated data treated as a verified fact?
No. Every material attribute carries a confidence level and verification status; AI-inferred data is explicitly marked as unverified until a human confirms it.
How is data privacy and tenant isolation managed?
SpiderNet is a multi-tenant SaaS architecture where buyer contracts, pricing, and scoring configurations remain strictly private to each specific tenant.
Are adverse findings or risk flags automatically published?
No. To ensure fairness and accuracy, all risk and adverse findings require human review and verification before they are published.
How does the platform ensure that the ranking of suppliers is unbiased?
Ranking neutrality is an architectural constraint; the system is designed so that supplier-side monetization never affects qualification, matching, ranking, or shortlist composition.
Ready to secure your procurement pipeline?
Contact Allmaz to implement SpiderNet's AI supplier intelligence for your team.
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