Procevia gives automotive supply chain teams visibility from Tier 1 through Tier 3 — connecting supplier surveys, capacity validation, demand shifts and decision support in one platform.
Survey suppliers below your direct base, not just Tier 1.
Simulation, dashboards and AI analysis, shipped today.
Connect a database read-only , no integration project.
Procevia connects collection, AI review, validation and decision support , so the team always knows the next move.
Collect supplier inputs.
Flag missing or blocked replies.
Compare demand and supply.
Surface risk and next steps.
Capacity risk rarely announces itself at your direct supplier. It builds two and three tiers down, in plants you have no signal from until production halts.
Revenue the semiconductor shortage cost automakers in 2021 , roughly 9.5m vehicles never built.
AlixPartners, 202195% of companies have visibility into direct suppliers. Below that it collapses , and it has fallen since 2022.
McKinsey Supply Chain Pulse, 2025What a decade of supply chain disruption costs the average company, cumulatively.
McKinseyThe cost of one disruption lasting 30 days or less. Longer outages run far higher.
McKinseyTier 2 and Tier 3 constraints stay invisible until they stop the line.
Survey Tier 2 and Tier 3 directly, roll their declared capacity up the chain.
Replies get re-keyed into spreadsheets, losing days and introducing errors.
Replies are parsed on arrival and matched to the right part number automatically.
By the time the review lands, the demand it was built on has already moved.
Re-run demand against live declared capacity whenever the forecast changes.
Tooling and line-rate spend is approved without a clear capacity payback.
Every investment case is charted against the capacity it actually unlocks.
Four pillars work together so plans, suppliers and decisions stay connected.
See supply, demand and risk at a glance.
Send surveys and track responses.
Flag gaps and draft next actions.
Inherit demand down the chain, roll declared capacity up from sub-suppliers.
Collect, analyze, follow up, decide. Each stage hands off cleanly into the next.
Create the request.
Send it to suppliers.
Collect and normalize replies.
Read the answers.
Flag blocked cases.
Track actions and reminders.
Compare demand and supply.
Show the next move.
Target: faster survey to response.
Target: follow-up moves quicker.
Target: teams decide sooner.
Procevia treats the CID conversation as a first-class workflow from the moment you draft a survey to the reply landing back in the tracker.
Step 01Build a structured CID request from your master data. Procevia pre-fills part numbers, volumes and contact emails so nothing is retyped.
Step 02Send one batch to dozens of suppliers from your own mailbox. CC, schedule and test mode are built in , every send is logged against the part code.
Step 03Replies land back in the CID Tracker read, parsed and matched to the right thread. AI flags missing fields, low confidence and KO answers automatically.
Fourteen screens are already built and running. This is what your team gets on day one, not what's promised for next year.
No integration project, no middleware, no engineer on standby. Point Procevia at your database, map the columns once, and stop exporting a spreadsheet before every planning cycle.
Sync is one click today. Scheduled sync, Google Cloud connectors and a native SAP connector are on the roadmap , everything else on this page is already live.
Need data out instead of in? A read-only API lets your own ERP or BI pull your organisation's parts, demand, capacity and CID data on its own schedule , no spreadsheet, no manual export.
Host, database and a read-only user. Test the connection before you save it , nothing is stored until it succeeds.
Match your own column names to Procevia's fields. The mapping is saved and reused on every later sync.
Pull fresh capacity and demand straight from your database instead of exporting a spreadsheet each cycle.
Procevia removes the busywork so teams focus on signal and action.
Drop spreadsheet reviews.
See supplier status in one place.
AI highlights the next step.
Automate chasing and reminders.
Modelled targets , not yet measured against a customer deployment.
Target: less spreadsheet work.
Every surveyed PN in one view.
Target: shorter response paths.
Target: automated reminders.
Procevia is built for the way automotive supply chains actually move , multi-tier, multi-PN, multi-plant. The same flow scales from a 4-PN survey to a 5-year capacity plan.
Coordinate hundreds of part-number CIDs across plants. Cut survey-to-decision cycles when an OEM volume shift hits a large integrator account.
Track capacity commitments from sub-suppliers feeding Tier 1s. Spot the bottleneck before it hits the line , pressed parts, harnesses, injection-molded components.
Watch single-source risk on raw inputs. AI correlates Tier-3 lead-times with Tier-1 KO answers so escalations happen weeks earlier, not after a stop-ship.
Replace the 40-tab demand-vs-capacity spreadsheet. Run multi-year mix scenarios across Tier 1/2/3 with one shared signal , quote support, RFQ prep and re-sourcing.
Compare capacity, demand, mix and forecast.
The platform surfaces gaps, risks and investment needs early.
Where supply trails demand.
What needs funding.
Which suppliers need attention.
What may block production.
What needs escalation.
Demand is ahead of supply.
Action is needed.
Top suppliers stand out.
Procevia was born from hands-on experience with demand, supplier capacity and operations in the automotive supply chain — combining supply chain, data and technology expertise.
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Control and Automation Engineer with 4+ years of experience across data, analytics and supply chain, working with Stellantis and DHL Supply Chain. Specializes in building data, automation and intelligence solutions that turn complex operations into faster, more efficient decisions.
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Data and BI professional with experience on the DHL/Stellantis operation, working across demand analysis, production mix, volume and operational capacity. Specializes in turning operational data into visibility that identifies bottlenecks and supports supply chain decisions.
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