INAYA - AI Procurement Intelligence for Commodity Teams

TL;DR

TL;DR: INAYA is a B2B AI platform that gives commodity-exposed procurement teams 24-month price forecasts, BOM-linked cost models, and an immutable audit trail for every fixing decision.

Source and Accuracy Notes

⚠️ This section is MANDATORY. All links must be verified from actual source, not guessed.

• Project page: inaya.ai ← visited and verified
• HN launch thread: news.ycombinator.com/item?id=45888386 ← 3 pts, Show HN
• License: Proprietary SaaS (no open-source license applicable)
• Source last checked: 2026-07-02

What Is INAYA?

INAYA is an AI-powered procurement intelligence platform built for commodity-exposed teams in manufacturing, CPG, and industrials. The founding team is based in Italy and launched the product in 2024.

The platform sits between a company’s ERP/Procurement system and the commodity markets, giving procurement leads, finance teams, and CFOs a shared view of forward exposure — and a defensible record of every major buying decision.

The core thesis on the site: procurement teams have market data, and they have decisions, but the layer connecting the two — the ability to know what a decision will cost before you make it, and prove why you made it afterward — is missing.

Four integrated capabilities make up the platform:

Market Foresight delivers bull/base/bear commodity scenarios on a 24-month horizon, updated continuously. Each forecast carries a probability weighting and cites the macro drivers behind the call. The claim is over 90% directional accuracy on 1–24 month horizons.

Product Composer lets teams build live cost models by linking every BOM line to a commodity index or supplier quote. FX adjustment is built in, and the model recalculates forward unit cost automatically when a commodity price moves.

Decision Governance is an immutable audit trail attached to every fixing decision. Each record captures the scenario alternatives considered, the model version used, who approved it, and the market conditions at decision time — producing a PDF summary committee-ready on request.

Lisa is the conversational interface: a chat layer inside Teams, Slack, and Email where procurement staff can ask commodity exposure questions in plain language and get answers backed by the same forecasting models powering the platform.

Setup Workflow

INAYA is a fully hosted SaaS product. There is no self-hosted deployment option and no developer install required to get started.

Step 1: Request Access

Visit inaya.ai and click “Get started” to book a 30-minute working session with the founding team, or request a 30-day full-feature trial directly.

The trial requires no IT integration and no contract. Setup time to a first defended decision is quoted at seven days.

Step 2: Connect Your Data Sources

During onboarding, INAYA connects to your existing procurement and ERP data. The specific connector list was not enumerated on the public site, but the platform supports integration with Procore and QuickBooks based on the feature schema.

Key data inputs include:

• Open purchase orders and supplier contracts (exposure quantification)
• Commodity indices referenced in supplier agreements (LME 3M aluminum, ICIS PP, HRC US steel, etc.)
• FX rates for internationally sourced materials

Step 3: Define Your Commodity Exposure

Set up your commodity universe — the specific indices and SKUs your business is exposed to. INAYA supports modeling across the most widely referenced commodity benchmarks including metals (aluminum, steel), polymers (polypropylene), energy (EUR-IT kWh), and freight (DAT-EU km).

Step 4: Run Your First Forecast

Once configured, Market Foresight generates a 24-month bull/base/bear scenario fan for each commodity in your universe. Each scenario includes:

• Price path trajectory
• Probability weighting (base case typically p=0.74 in example outputs)
• Macro narrative explaining the key drivers

You can query any commodity in plain language via Lisa (in Teams or Slack) and get a scenario-backed answer in seconds.

Deeper Analysis

The Decision Gap INAYA Is Solving

The site cites Gartner/AFP 2024 data: uncontrolled commodity exposure on a $200M annual spend can represent approximately EUR 4M per year in unhedged cost risk. Deloitte/Hackett 2024–25 data suggests manual data work across procurement and finance costs approximately EUR 160K per year per company. The Hackett Group 2024 places analyst time waste at 3,200+ hours per year per company.

These are third-party benchmarks cited by the INAYA site — not independently verified here.

Competitive Landscape

INAYA occupies a niche between commodity trading risk platforms (like OpenRisk or CommodityXL) and general procurement suites (Coupa, SAP Ariba). The differentiated bet is the combination of forecasting + BOM cost modeling + decision audit in a single product aimed at mid-market industrial teams rather than enterprise trading desks.

The main comparison points for similar tools covered on runany.dev:

• Klavis AI — AI commodity intelligence for CPG/CPG (broader, more analytics-focused)
• Digger — open-source infrastructure cost management (more DevOps/infrastructure angle)
• Simplex — browser automation for developers (different domain entirely)

Target Users

Based on the site and product schema, the primary personas are:

1. Procurement Leads managing supplier contracts and commodity exposure directly
2. CFOs and Finance Controllers needing a defensible record of major fixing decisions for board and auditor review
3. Supply Chain Teams responsible for BOM cost projection and margin forecasting

Pricing

INAYA offers a free plan with core features. Paid tiers are available via “Contact Sales” — no public pricing page was found on the site as of July 2026.

Practical Evaluation Checklist

If you are evaluating INAYA for your procurement team, here is a practical checklist based on the published feature schema:

• [ ] Do your commodity costs represent more than 15–20% of COGS? (INAYA’s ROI case is strongest here)
• [ ] Are you currently running commodity exposure analysis in spreadsheets?
• [ ] Do you have an upcoming auditor or board review where commodity hedging decisions need to be justified?
• [ ] Do your procurement and finance teams use Teams or Slack daily?
• [ ] Is your team comfortable with a fully hosted SaaS product (no on-prem option)?
• [ ] Do your key supplier contracts reference LME, ICIS, or other indexed commodity benchmarks?

If you answered yes to three or more of the above, INAYA is likely worth a 30-minute demo call.

Security Notes

INAYA handles sensitive procurement data including supplier pricing, commodity exposure positions, and internal cost structures. As a B2B SaaS product processing potentially material non-public financial information, appropriate vendor due diligence is recommended before committing to a trial, including:

• SOC 2 Type II certification status (not published on the site)
• EU data residency confirmation (listed as a feature on the site)
• Data processing agreement availability for GDPR compliance
• Incident response and breach notification procedures

The site does not currently publish a security page, trust center, or dedicated DPA. Reach out to [email protected] to request this documentation before trial.

FAQ

Q: Does INAYA integrate with my existing ERP? A: INAYA is a standalone SaaS platform that connects to your data sources during onboarding. The site mentions Procore and QuickBooks integrations. For specific ERP system support, contact the INAYA team directly to confirm compatibility.

Q: Can INayana forecast custom or niche commodity indices, not just LME/ICIS benchmarks? A: The published feature schema shows support for the most widely referenced commodity indices. For niche or bespoke benchmarks, direct inquiry with the team is the best path.

Q: Is there an on-premises deployment option? A: No — INAYA is fully hosted. The site notes “EU data residency” as a feature, suggesting data stays within European infrastructure.

Q: How is Lisa different from a general AI chatbot? A: Lisa is backed by the same ensemble forecasting models powering the platform, not a general-purpose LLM. Every answer cites the model version, probability weighting, and data source — giving answers that are traceable to a specific forecast, not hallucinated.

Q: What happens to my data if I cancel? A: This was not enumerated on the public site. Review the data retention terms in your data processing agreement before committing sensitive procurement data.

Conclusion

INAYA targets a specific, high-cost problem that most industrial procurement teams manage with spreadsheets and institutional knowledge. The combination of 24-month scenario forecasting, BOM-linked cost modeling, and an immutable decision audit trail is genuinely differentiated from what most companies have today.

The product is early (founded 2024, active development as of 2026) and the pricing model is opaque — you need to talk to sales. But the 30-day free trial with no contract and no IT integration required is a low-friction way to validate whether the product fits your actual workflow.

If your team is currently burning time reconciling commodity exposure in Excel before every board meeting, INAYA is worth 30 minutes of your time.

→ Book a demo at inaya.ai