Supplier Intelligence
See which suppliers need attention before issues become production problems.
Illustrative scenario · modeled targets, not deployed resultsA composite Tier-1 eVTOL airframer moving from flight-test prototypes into FAA type certification and early rate production, with a defense-adjacent variant under DCMA oversight.
~140 active suppliers · AS9100 and NADCAP required across critical tiers, many on ITAR-controlled programs · certification, delivery, and pricing history scattered across ERP, spreadsheets, supplier portals, and email.
In prototype mode, a single late part was an engineering inconvenience. Rate production changes the math: the same late part is now a line-down event with a schedule and certification cost attached. The supplier base tripled in eighteen months, but the way supplier risk is understood did not — it still lives in a procurement lead's head, a delivery spreadsheet, and a folder of certification PDFs. The result is a reactive posture: trouble is learned at receiving, when the only options left are expensive — expedite, re-source under pressure, or slip the build.
Which suppliers do we act on, and how — before they cause a problem?
What this engagement is designed to move — modeled targets for an operator of this profile, not measured results.
From first look to running loop.
Your supplier base, scored in 2–3 weeks. No integration required.
Send a supplier list — names, part categories, and whatever delivery and certification records are at hand. Nothing is connected. Deep-SKAI scores that base against proprietary aerospace & defense benchmark data — certification status (AS9100, NADCAP, ITAR registration), on-time-delivery history, and award-pricing context built since 2017 — and returns every supplier ranked by risk, the 10–15 that need attention now with the reason each surfaced, and the modeled schedule and cost at risk.
One decision, running live in your environment. 4–6 weeks.
Connect the systems behind a single decision — which suppliers to act on each week, and how. Deep-SKAI encodes your policy and compliance constraints and runs the governed loop live: ranked supplier actions, the modeled consequence of each, a human-in-the-loop approval, and a recorded audit trail defensible to DCMA and internal quality.
The decision becomes a governed operating habit. Ongoing.
The pilot decision becomes permanent — the loop runs continuously above your existing systems, no rip-and-replace. Scores refresh against live signals, every action is a decision of record, and expected-vs-actual feeds back so the scoring sharpens each cycle. The loop expands to adjacent decisions as it earns trust.
Illustrative scenario. The composite operator is fictional, created to show how an engagement is structured; it does not depict a specific NexStratus customer, and the KPIs shown are modeled targets, not measured results from a deployment. Deep-SKAI is patent-pending.