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AI Use Cases

synvert Accel­er­at­ors

Indus­tri­als


Cloud Data & AI for Industry – Effi­ciency, Qual­ity & Innovation


Intel­li­gent man­u­fac­tur­ing processes


Industrials automotive Manufacturing Processes


Cloud data & AI are fun­da­ment­ally chan­ging indus­trial oper­a­tions by optim­iz­ing pro­duc­tion, redu­cing costs and auto­mat­ing qual­ity assur­ance. Com­pan­ies bene­fit from pre­dict­ive main­ten­ance, more effi­cient man­u­fac­tur­ing pro­cesses and intel­li­gent sup­ply chains.

Arti­fi­cial intel­li­gence ana­lyzes sensor data in real time to detect fail­ures early and pro­act­ively man­age main­ten­ance. Machine learn­ing improves pro­duc­tion plan­ning by optim­iz­ing demand fore­casts and effi­ciently alloc­at­ing resources. Com­puter vis­ion enables auto­mated qual­ity con­trol, while data-driven pro­cess optim­iz­a­tion min­im­izes error rates. Shop floor ana­lyt­ics help to mon­itor machine uptime and mater­ial flows in real time, identify bot­tle­necks and make pro­duc­tion pro­cesses more effi­cient. Pro­cess min­ing uncov­ers inef­fi­cien­cies and sup­ports con­tinu­ous pro­cess improvement.

With over 30 years of exper­i­ence and more than 3.000 suc­cess­ful pro­jects, synvert is the ideal part­ner for com­pan­ies that want to drive their digital trans­form­a­tion with cloud data & AI.


Our cus­tom­ers in industrials



Use Cases



Self-Ser­vice Data Mesh


Pion­eer­ing self-ser­vice Data Mesh plat­form imple­ment­a­tion – Using Cloudera Data Plat­form on AWS at a global com­mer­cial vehicle manufacturer.



Cloud Plat­form


Built a cloud data plat­form from scratch in Azure for a lead­ing global man­u­fac­turer of con­sumer goods, includ­ing an auto­mated fore­cast­ing tool to improve their man­u­fac­tur­ing timelines and drive profit margins.



NLP in Reporting


Nat­ural Lan­guage Pro­cessing in Auto­mot­ive Report­ing. An inges­tion mech­an­ism includ­ing OCR digit­iz­a­tion, arte­fact removal and text cleans­ing was cre­ated and has since been fed well over a mil­lion reports. As a final step in the NLP pipeline, topic mod­el­ling was used to tag the doc­u­ments accord­ing to their content.



Neural Car Classification


Auto­matic clas­si­fic­a­tion of cars by their model – A deep con­vo­lu­tional neural net­work was trained to identify car types. It can identify roughly 200 dif­fer­ent types of cars with near-human level accuracy.



Man­u­fac­tur­ing DWH


Devel­op­ment of new and improved ETL pro­cesses of the pro­duc­tion data ware­house (pDWH) for eval­u­at­ing pro­duc­tion para­met­ers, quant­ity runs and depend­ent KPI val­ues for a man­u­fac­turer of elec­tronic components.



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