Real Talks, Real Use Cases: Our Meetup with the AWS User Group Bogotá

November 25, 2025

The First Line Software team shares insights and updates with each other on a nearly daily basis, but we know that we don’t exist in a vacuum. That’s why we share our experiences with our local communities all around the world at our Meetup Nights

Our most recent Meetup Night was held in Bogota, Colombia, where our team partnered with AWS User Group Bogota for an evening of insights, skill sharing, and connection.

Our teammates Angelica Echeverria and Juan Sebastian Pera presented their expertise at the meetup, sharing insights about our own use cases and how organizations can prepare for successful AI adoption. 

We know it’s always better to hear presentations in their original form, straight from the speakers themselves. But we gathered some key takeaways from our teammates’ talks, so you can see what we’ve been up to (and why our Meetup Nights are so great!). 

This Isn’t Just Another AI Demo: Real Use Cases That Actually Delivered Value

Angelica Echeverria, Product Manager

Case 1: Jaime

Some context for our readers: Jaime is the AI assistant who supports the First Line Software team on our global website, firstlinesoftware.com (if you follow the link, you’ll find Jaime in purple, in the bottom right corner). Since its initial launch, Jaime has been receiving regular updates and new features from our team. This presentation describes why we created Jaime, and the journey we’ve had together since its inception. 

Initial Problem:
Jaime 1.0 could answer basic questions, but users needed something more: continuity, personalization, and real context. People needed a system that could understand intent, follow the user’s journey, and offer a more natural interaction.

Goal:
Transform a reactive chatbot into a proactive digital assistant that guides visitors using contextual intelligence.

Solution:
• Development of Jaime 2.0
• Modular, multilingual architecture with voice capabilities
• Smart suggestions such as “summarize this page” or “see similar cases”

Results:
• More natural and personalized interactions
• Increased time spent on the site
• Ready for future advanced search and multichannel features

Case 2: Automation of Compliance and Regulatory Processes in Banking

Problem:
A bank had to process thousands of documents in multiple languages under strict regulations, without being allowed to use cloud services. Manual workflows were slow, expensive, and prone to errors.

Goal:
Automate document review and regulatory compliance with AI, while maintaining full security and confidentiality.

Solution:
• Implementation of RegulationAI with OCR (Optical Character Recognition) and multilingual analysis
• Data extraction for loans, conditions, and regulatory requirements
• On-premise processing on the bank’s servers to meet regulatory requirements

Results:
• 70% reduction in review time
• Higher accuracy and lower costs
• Scalable, secure platform adaptable to new regulations

Takeaways from our experience

What the client values most in product development:

  • The development team is more efficient when they have clarity and access to information about the problem.
  • AI is often a means, not an end.

Conclusion
Artificial intelligence is not just technological innovation; it’s a tool to improve processes, decisions, and experiences. Our team has seen firsthand that when AI is applied with purpose, it transforms operations and creates significant value.

From Demo to Reality: How to Prepare Your Operation for AI Success

Juan Sebastian Pira Diaz, Service Operations Engineer

[quick intro of his talk]

The AI Mirage
It looks amazing in the demo…
…but in production, it becomes slow, expensive, or simply doesn’t work as expected.

Why AI Fails in Production
It’s not the technology…

  • Chaotic processes
  • Dirty or incomplete data

…it’s the foundation:

  • Disconnected tools
  • Wrong metrics

Sound familiar?
Maybe you’ve experienced…

  • Manual rework due to incorrect data
  • Searching for a client’s information across three different systems
  • Reports nobody trusts or understands
  • A technology project that didn’t deliver the expected results

The Cloud is a Toolbox
But tools don’t build the house.
The blueprint and foundation do.

Value isn’t in which tool you use—it’s in how you use it.

1. Know Your Business Inside & Out

Real Value is Hidden in Your Operation
Don’t automate a process you don’t understand.

  • Map the customer journey: Where do they struggle? Where do they wait?
  • Talk to your front line—they have the answers.

2. AI Doesn’t Thrive in Chaos

Structured and Clear Processes
Your goal: consistency

  • Standardize case classification
  • Define clear workflows
  • Build a robust, useful knowledge base (KB)

3. Smart Integration

APIs and CRM—AI alone is useless!
Your CRM is the brain of your operation

  • Connect tools like Zendesk with your CRM
  • 360° customer view: Who are they? What have they purchased? What issues have they had?
  • Clean your data—garbage in, AI garbage out

4. Stop Measuring Only “Closed Cases”

Refine Reporting and Change the Mindset

New metrics to track:

  • FCR: Did we solve the problem on the first contact?
  • CSAT: Is the customer satisfied?
  • CES: How much effort did it take for the customer?

Prepare your reports today—so when AI arrives, you can measure its real value.

Conclusion: Your Checklist to Be Ready

  1. Audit Your Processes
    Map your 5 most common workflows.

  2. Clean and Integrate Your CRM
    Are your customer data reliable and accessible from your support platform?

  3. Strengthen Your Knowledge Base
    Is it up-to-date and easy to use?

  4. Define Your Success Metrics
    How do you measure “good work” beyond speed?

"AI implementation is not a technology project. It’s a business project supported by technology." – Google Gemini

Want to join the next Meetup Night near you? Keep an eye out for upcoming events and we’ll see you there!

Let’s talk!

Have any questions? Fill out the form and our team will be in touch!