LAL A.I. – Decision Support
Text mining, n‑grams, vector search and enterprise context injection for decision support.
- • Up to 40% faster decision cycles
- • +15% decision accuracy (with feedback loop)
- • +25% user adoption (simplified UX)
Text mining, n‑grams, vector search and enterprise context injection for decision support.
LAL A.I. ingests ERP/DB/REST data, builds n-gram and embedding representations, injects live context into prompts via RAG, and produces clear, auditable decision texts.
User feedback is fed back into the system; versioned templates provide measurable, iterative improvements.
Key terms/patterns from free text; TF-IDF / PMI signal scoring.
Sentence/record embeddings; similarity via cosine/dot.
Auto-inject ERP/DB context into prompts.
Versioned templates with A/B comparisons.
Preprocess → inference → validation → publish.
User rating/explanation → quality metric → continuous tuning.
Field masking, audit logs, role-based access.
SAP (OData/BAPI), Wolfram ERP, REST, SQL; scheduled/event-driven.
Cloud (OpenAI etc.) + local models; hot key switching.
Stream data from SAP/Wolfram ERP/DB/REST.
Clean, build n-grams & embeddings, map to ontology.
RAG + context injection to generate decisions/text.
Feedback, metrics and versioning to iterate.
Connects to SAP (OData/BAPI/IDoc), Wolfram ERP, REST, SQL (MSSQL/PostgreSQL/MySQL), queues (Kafka/RabbitMQ) and file shares.
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