Trusted data layer AGYL positions itself as a universal records reconciliation layer that reads across multiple systems to deliver a single version of truth. Sales opportunities exist in organizations with complex data landscapes and data quality challenges who need a centralized governance layer to enable consistent AI and automation outputs.

Production-scale relevance With 2.1M fields reconciled across 11 systems and 500K products held current daily, AGYL demonstrates real-world, high-volume capability. Target mid-market to enterprise buyers facing scale and data freshness issues can be approached as potential customers for data reliability and operational efficiency.

First-pass resolvability A 96% first-pass resolvability rate indicates strong reliability and speed in delivering trusted records. This can be pitched to AI/ML teams seeking faster, trustworthy data feeds to improve model outputs and reduce downstream errors.

Cross-system integration AGYL reads from any system that holds a record, suggesting broad integration potential with existing tech stacks. Sales can prioritize organizations with diverse data sources and a need to unify records across ERPs, CRMs, product catalogs, and financial systems.

Growth outside core NLP Despite small team size, the company demonstrates growth through a critical data governance layer rather than just model advances. This opens opportunities with organizations pursuing AI governance, compliance, and operational efficiency rather than pure model-centric AI, including sectors like finance, manufacturing, and e-commerce.