Next-Gen Data Mapping
Starts Here
And we’re building it from the ground up.
Our Goal
We want to develop better systems for metadata standards-based data exchanges. By expanding AI-native capabilities, we can advance industry-grade digital transformation for businesses world-wide.
Where We Stand Out
Explainability
Every mapping and transformation is fully explainable and auditable. You can see which rules were used, what context was applied, and why each result was produced—no black boxes. This makes validation faster, governance easier, changes safer, and builds trust with both internal teams and external partners.
Standards-Based
AIR treats metadata as a core asset, using shared standards to power automation. Mappings are built on clear, reusable definitions instead of custom scripts, so integrations stay consistent and easier to manage. This helps large ecosystems align while still allowing flexibility for your specific needs.
Reusable
AIR is designed for reuse, so you don’t have to rebuild mappings for every interface or partner. Shared building blocks can be applied again and again with reliable results. When requirements change, you update once and the change flows everywhere—cutting maintenance effort, lowering costs, and keeping mappings consistent over time.
AI-Native
AIR has AI built into every step of the data mapping lifecycle—not added on later. It works with schemas, rules, and metadata to suggest mappings, catch issues, reuse past work, and clearly explain results. This helps you onboard faster and greatly reduces ongoing effort as your data ecosystem grows and changes.
ABOUT US
Led by Nenad Ivezic, AIR is backed by 20+ years of industry experience.
OUR PARTNERS
And There's More to Come
Whether you’re curious about features, partnering, or investing, we’re here to answer any questions you may have.