01 PROBLEM STATEMENT

Your Branch Staff are Searching for Answers While Customers Wait

A leading private sector bank with 400+ branches found that its front-line staff tellers, relationship managers, branch operations officers were spending hours every week searching for answers to policy questions, product guidelines, and internal SOPs. Documents were scattered across SharePoint, file shares, email attachments, and PDF archives.

When a customer asked about eligibility for a new loan scheme or the process for a foreign remittance, staff either kept the customer waiting while they searched internal systems, or gave incorrect information from memory. Training for new hires took weeks because there was no quick way to learn the hundreds of policies, products, and procedures that govern daily branch work.

02 current challenges

What the Bank was Struggling With

03 SOLUTION OVERVIEW

STAR’s Approach – AINE Branch Operations Assistant

STAR Systems deployed the AINE Branch Operations Assistant is a Gemini-powered Q&A; system over the bank’s entire corpus of internal SOPs, product guidelines, and policy documents. The corpus is ingested from SharePoint or file share in a one-time sync, with incremental updates handled automatically. Staff authenticate via Azure AD or LDAP, ask questions in plain language, and receive cited answers instantly. Usage analytics track which policies and SOPs have content gaps, and the content team updates the corpus monthly. No model retraining required. the RAG architecture auto-picks up new documents from SharePoint. STAR manages the vector index refresh and monitors response quality fortnightly.

04 WORKFLOW PROCESS

Step-By-Step: How Branch Staff Get Answers Instantly

Step 1 – Corpus Integration: SOPs, product guidelines, and policy documents ingested from SharePoint or file share in one time sync plus incremental updates.

Step 2 – Staff Authentication: Branch staff authenticate via Azure AD or LDAP. Role based access controls which documents are searchable.

Step 3 – Plain-Language Query: Staff ask questions in plain language no keyword search syntax required. Gemini understands the intent.

Step 4 – RAG Retrieval: Relevant policy sections and SOP paragraphs retrieved from the vector index and ranked by relevance to the query.

Step 5 – Cited Answer: Gemini generates a plain language answer with citations to the source documents. Staff see the exact section referenced.

Step 6 – Usage Analytics: Query logs tracked for content gap identification. Content team updates corpus monthly based on unanswered questions.

05 KEY FEATURES

What the Assistant Does

Gemini-Powered Natural Language Q&A:

Staff ask questions in plain language – no keyword search syntax. Gemini understands intent and retrieves the right policy section automatically.

Azure AD or LDAP Authentication:

Staff authenticate via existing bank credentials. Role-based access controls which documents are searchable based on branch and job function.

Auto-Sync from SharePoint or File Share:

Document corpus ingested from SharePoint or file share in one-time sync. Incremental updates are handled automatically no manual re-indexing.

Usage Analytics for Content Gaps:

Query logs reveal which policies have unclear or missing content. Content team updates corpus monthly based on unanswered or low-confidence queries.

Cited Answers with Source Documents:

Every answer cites the exact SOP, product guideline, or policy document section it came from. Staff can verify the answer at the source.

Zero Model Retraining Overhead:

RAG architecture means no model retraining when corpus is updated. STAR manages vector index refresh and response quality monitoring fortnightly.

06 BUSINESS OUTCOMES

What Changes After Go Live

07 REAL-WORLD SCENARIO

A Day in the Life – Before and After

08 ROI AND VALUE JUSTIFICATION

Why this Numbers Work

09 NEXT STEPS