Transaction Activity Agent
Summarizes buy, sell, and dividend transactions from trade confirmations into client activity reports.
EXPLORE WHAT'S POSSIBLE WITH AI
The Operating Blueprint for AI-Native Retail Banking
Discover 200+ AI use cases, spanning 4 functions, engineered for real enterprise scale.
Use our operating blueprint of apps and agents to map your path to becoming AI-Native.
Why this matters now
The Pilot Trap
95% of AI projects never make it to production. Enterprises are stuck in endless POCs with no clear path to scale.
Average time from pilot to production:
6-18 months
What's Changed
AI agents are now production-ready. The question isn't "if" but "where to start" and "how fast can we scale.
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LLMs reliable for enterprise workflows.
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Integration patterns now standardized.
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ROI proven across industries.
The Blueprint Advantage
Skip the experimentation. Deploy production-proven agents with documented ROI from day one.
Average time to production:
4-6 weeks
What you'll discover
200+
Production Agents
4
Departments Covered
50+
Process Areas
Sample apps and agents
Refund Processing Agent
Generates refund instructions for disputed transactions with amounts, account credits, and customer notifications.
40% Reduction in Refund Documentation Time
Fee Waiver Agent
Documents fee waiver requests, approval decisions, and adjustments from customer service exceptions.
30% Reduction in Waiver Documentation Time
LC Application Agent
Extracts letter of credit details, including beneficiary, amount, terms, and shipping documents from client applications.
45% Reduction in LC Application Processing Time
How to use
Why this exists:
Every enterprise AI conversation ends the same way: What’s working—and where do we start?
This blueprint provides a tangible path to prioritize your AI transformation.
How to use it?
- Pick a domain: Finance, HR, Supply Chain, Sales, IT, etc.
- Find a process: Each domain is broken into functional areas
- Check the ROI: Business ROI of becoming AI-Native
- Add the agent or app to your plan: Every agent has documentation behind it
What each use case gives you:
- Agent: Name and function
- Description: Inputs, logic, outputs, integrations
- ROI: For transforming that process with AI