Today: a category-defining gap
Procurement has more market data than ever before. Bloomberg, Refinitiv, ICIS, S&P, in-house desks, supplier intelligence, alternative data — the signals exist.
Procurement makes more decisions than ever before. Fixings, hedges, supplier switches, escalation clauses — they happen weekly, sometimes daily, on commodities that move the P&L by tens of millions.
And yet between the two — between the market signal and the procurement decision — there is no layer. No system that quantifies the trade-off. No record that survives the analyst leaving. No mechanism to learn from the decisions that worked and the ones that didn't. The work is done in spreadsheets, the rationale lives in inboxes, and the institutional memory walks out the door every time someone changes job.
Why now: AI moves at the speed procurement actually moves
Procurement decisions cycle weekly to monthly. Forecasting at that cadence, across hundreds of commodities, is a problem only AI can solve at the scale and speed the work demands.
The same is true for the reasoning around the decision: simulating thirty alternatives, ranking them by quantified impact, surfacing the dissent, drafting the rationale — these are not analyst tasks anymore. They are model tasks, executed in seconds, audited in minutes.
The window is narrow. The teams that build the muscle to operate this way in 2026 will be the ones operating with quantified margin instead of post-hoc explanations in 2030.
Forecasting was never the bottleneck. The bottleneck was structuring the decision around it.
Our take: not a tool, infrastructure
INAYA is not a forecasting product, a BI add-on or a procurement suite. INAYA is the layer underneath the procurement workflow — the place where forecasts, cost models, decisions and the conversation around them live as a single, auditable substrate.
We build for procurement teams that have stopped treating volatility as a thing to react to and started treating it as a thing to structure. We build for finance teams that want forward visibility on COGS, not month-end surprises. We build for risk teams that need quantified, defensible exposure management.
This is decision infrastructure. Once it's there, working without it feels like working without a CRM.
Where we're going: 2026 → 2030
In 2026 we are deploying with the first cohort of procurement and finance teams across food, manufacturing and chemicals — proving the platform on the commodities where volatility hurts most.
By 2028 every fixing decision in our customer base will carry a model-anchored, audit-grade record. The committee conversation moves from 'why did you commit?' to 'how did the alternative paths price?'.
By 2030 decision intelligence is standard infrastructure for any commodity-exposed organization. We intend to be the layer that gets there first — and the layer the rest of the workflow gets built on top of.
The companies that win the next decade of margin will be the ones that operate with quantified foresight by default.
We're a small team, building serious infrastructure, in Italy, for the rest of the world. If this is the work you've been waiting for procurement to get — let's talk.