Why It Matters
Most enterprise data—emails, documents, support logs, images—is unstructured. Generative AI unlocks this data to:
Accelerate Decision-Making
Summarize, classify, and extract key insights.
Automate Knowledge Work
Power search, reporting, and analysis without manual effort.
Boost Innovation
Create new value streams by enabling AI-based knowledge discovery.
Reduce Risk
Uncover hidden issues in contracts, tickets, or logs.
The Levi9 Approach – Contextual, Responsible GenAI for Enterprises
We design GenAI pipelines that are safe, contextual, and business-ready. Our strength lies in combining data engineering, retrieval-augmented generation (RAG), and real enterprise constraints to deliver high-trust outcomes.
Steps We Take Together
Whether it’s chat-based access to knowledge, price prediction models, or intelligent search interfaces—Levi9 delivers.
01
Use Case Design
Identify high-value unstructured data sources and business opportunities.
02
Data Readiness & Structuring
Clean, transform, and embed your data for GenAI consumption. Ensure privacy and governance.
03
Model & Pipeline Development
Use LLMs (Azure OpenAI, Google Vertex, etc.) with RAG, prompt engineering, and fine-tuning as needed.
04
Deployment & Feedback Loop
Launch interfaces—search, summaries, chat, or recommendations—and iterate based on real usage.
WHAT YOU GAIN: KEY OUTCOMES & DELIVERABLES
AI-Ready Data Architecture – Structured, governed, and embedded for safe AI use.
Custom GenAI Interfaces – Use-case specific apps (e.g., internal Q&A, price forecasts, HR coaching).
Transparent Outputs – Logs, citations, and audit tools to validate responses.
Accelerated Time-to-Insight – Cut hours of manual effort into seconds.
Real-World Proven Methods – From internal HR tools to commercial visual AI search for clients like PVH.
