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Prennoy99/README.md

Prennoy Babu

Automotive and industrial AI systems, built and shipped as working software rather than notebooks — fault diagnosis, predictive maintenance, anomaly detection, and control.

Every project below verifies its own results, and publishes the ones that aren't flattering. DocuBot's eval harness was rewritten mid-project after file-level scoring was found to hide a total retrieval failure; pdm-lite states plainly that its 100% test accuracy is expected on a clean benchmark and the pipeline is the actual achievement; rag-enterprise-assistant reports a RAGAS faithfulness score of 0.675 rather than a rounder, better-looking number. A hiring engineer can't fake-check a demo, but they can check a claim — so the claims here are measured, not asserted.

Live

  • DocuBot — German-language RAG agent over automotive/technical documents
  • pdm-lite — bearing-fault predictive-maintenance API (Swagger UI)

Both are free-tier deployments and cold-start slowly on the first request — that's normal, not broken.

Projects

Project What it does Stack Proof
DocuBot German-language RAG agent over automotive/technical documents FastAPI · ChromaDB · ONNX int8 · Groq · LangChain Live demo · image cut 934→251 MB, cold start 17.5→5.0s · 68 tests, CI green
pdm-lite Predictive-maintenance API classifying bearing faults from raw vibration signals 1D-CNN · ONNX Runtime · FastAPI · Docker Live demo · CWRU dataset, 923 held-out windows · CI → GHCR
patch-cae-anomaly-detection Patch-based autoencoder for unsupervised industrial defect detection — Master's thesis, Audi AG Production Lab PyTorch · computer vision ROC-AUC 0.9745 / 0.9962 vs. DFR baseline 0.801 / 0.940 and PatchCore 0.753 / 0.660 (MVTec avg 0.9787)
rag-enterprise-assistant Document Q&A with hybrid search and grounded citations FastAPI · pgvector · React/TypeScript · RAGAS RAGAS: faithfulness 0.675, relevancy 0.875, context precision 0.933, recall 1.000
fleetpulse Real-time vehicle telemetry pipeline Kafka · Spark Structured Streaming · PostgreSQL · Grafana CI green · dead-letter path proven by deliberately corrupting 2% of events
chartersense Natural-language analytics over shipping data via a versioned semantic layer FastAPI · PostgreSQL · LLM-to-SQL LLM's SQL answer diffed against independently computed ground truth · read-only DB role

Auf Deutsch

Ich entwickle KI-Systeme für die Automobil- und Fertigungsindustrie – von der Fehlerdiagnose über prädiktive Wartung bis zur Anomalieerkennung. Dabei ist mir wichtig, dass jedes System seine eigenen Ergebnisse überprüft, statt sie nur zu behaupten: DocuBot etwa ist ein deutschsprachiger RAG-Agent für technische Dokumente mit einem eigens entwickelten Auswertungsverfahren und einer echten Live-Demo. Ich freue mich über den Austausch mit Teams im DACH-Raum, auf Deutsch oder Englisch.

Contact

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  1. DocuBot DocuBot Public

    German-language RAG agent over automotive/technical documents — FastAPI, ChromaDB, ONNX int8, real eval harness.

    Python

  2. patch-cae-anomaly-detection patch-cae-anomaly-detection Public

    Master's thesis, Audi AG Production Lab — patch-based convolutional autoencoder for unsupervised industrial defect detection.

    Python

  3. pdm-lite pdm-lite Public

    Predictive-maintenance API classifying bearing faults from raw vibration signals — 1D-CNN, ONNX Runtime, FastAPI, live demo.

    Python

  4. rag-enterprise-assistant rag-enterprise-assistant Public

    Document Q&A with hybrid search, streaming answers and grounded citations — FastAPI, pgvector, React/TypeScript, RAGAS eval.

    Python

  5. fleetpulse fleetpulse Public

    Real-time vehicle telemetry pipeline — Kafka, Spark Structured Streaming, PostgreSQL, Grafana, with a proven dead-letter path.

    Python

  6. chartersense chartersense Public

    Natural-language analytics over shipping data — versioned semantic layer, LLM SQL checked against independent ground truth.

    Python