Private LLM Deployment for Multi-National Bank
Client Partner: Apex Trust Holdings · Build Timeline: 4 Months
Project Tech Stack
Allocated Engineering Pod
- NLP Specialistsx2
- Security Architectsx1
- UI Engineersx2
"Crocus Robotics built a secure AI system that our compliance team approved. It has significantly changed how our analyst groups digest regulatory shifts."
Marcus Sterling
Chief Technology Officer, Apex Trust
1. Context & Business Goal
The Core Challenge: Apex Trust employees spent hours summarizing 500+ page regulatory PDF reports manually, but were restricted from using public AI APIs due to security rules.
The Agreed Objective: Deploy a high-speed, secure, private LLM inside Apex's on-premise cloud infrastructure to automate document summaries and semantic queries.
2. Technical Research & Discovery
Audited internal bank documents to compile safe search datasets, checking data structures to verify security controls. Prior to writing any code, our team compiled reference data frameworks and mapped API endpoints to identify speed limits.
3. System Architecture Design
Layout Scheme: Split-screen interface with document upload/viewer on the left, and a chat interface showing source citations on the right.
Database Infrastructure Setup: Llama-3 70B running inside a secure VPC using Kubernetes, utilizing a Milvus vector grid to search PDF text chunks.
4. Production Implementation Lifecycle
Infrastructure Isolation
Setup secure VPC configurations with local database replications.
Vector Pipeline Setup
Built PDF parser engines to slice, index, and load bank documents into Milvus database.
Security Alignment Auditing
Tested prompts with security filters to block data leakage across user access levels.
5. Validated Business Outcomes
- ✓Reduced regulatory summary workflows from 6 hours to less than 5 minutes.
- ✓Successfully indexed and queried over 12 million corporate pages.
- ✓Fully compliant with banking security audit standards without cloud calls.