JO

01 — AI in production↑ Back to the map

From prototype to production.

LLM-based systems built end to end — architecture, integration, evaluation and monitoring — with a focus on latency, reliability and business metrics.

  • CredicorpArtificial Intelligence Program
  • Advanced Data Scientist, Cognitive AI
  • 2024 — present

Collections conversational agent

A conversational agent deployed in production on WhatsApp. A cognitive architecture built on LLMs, connected to the channel through the messaging provider Jelou, with an end-to-end flow and handoff to human advisors.

System
  1. 01CustomerWhatsApp
  2. 02MessagingJelou
  3. 03AgentMicrosoft Agent Framework · Azure OpenAI
  4. 04ContextMulti-step retrieval
  5. 05Responseor handoff to a human advisor
−80%latency per interaction
Before~1.5 min
After~18 s
Optimisation of a multi-step flow with context retrieval, maintaining effectiveness and improving how natural the responses feel.
  • Microsoft Agent Framework
  • Azure OpenAI
  • WhatsApp
  • Jelou
  • LLMs
02 — Agents↑ Back to the map

Agents that do real work.

Conversational and automation agents operating on real processes, beyond the prototype.

2 projects

  1. 01

    Credicorp · 2024 — present

    Collections conversational agent

    A conversational agent deployed in production on WhatsApp. A cognitive architecture built on LLMs, connected to the channel through the messaging provider Jelou, with an end-to-end flow and handoff to human advisors.

    • Microsoft Agent Framework
    • Azure OpenAI
    • WhatsApp
    • Jelou
    • LLMs
  2. 02

    Independent project · 2023 — present

    Commercial communications agent

    An AI agent that automatically generates commercial communications in HTML, automating a marketing process that used to be manual.

    • LangChain
    • OpenAI API
    • HTML
    System
    1. 01BeforeManual marketing process
    2. 02AgentLangChain · OpenAI API
    3. 03OutputCommercial communication in HTML

Language turned into decisions.

Natural language and speech processing applied to conversations, interactions and documents.

  1. Credicorp

    Speech analytics

    A tool deployed on the collections phone channel: automatic classification of non-payment reasons, analysis of advisors’ soft skills and speech recommendations.

  2. Credicorp

    Sentiment analysis

    Sentiment analysis of customer interactions to prioritise experience improvements in collections.

  3. Credicorp

    Legal documentation

    Automated processing of legal documentation for collateral recovery workflows.

04 — Research↑ Back to the map

Published research.

Research on generative AI applied to learning, built on systems of my own.

  1. First author

    GenAI-Powered Feedback for Video-Based Learning

    AIAI 2026 — 15th Workshop on Mining Humanistic Data (MHDW)

    Springer · 2026

    • Conference
    • Organisation
    • Publisher

    Citation

    Ordóñez Olazábal, J. S., et al. (2026). GenAI-Powered Feedback for Video-Based Learning. AIAI 2026 — 15th Workshop on Mining Humanistic Data (MHDW). Springer.

The project behind the paper

GenAI feedback for teachers

A full-stack application that gives teachers feedback on video courses, built from data capture to user interface. It is the foundation of my AIAI 2026 publication.

System
  1. 01InputVideo courses
  2. 02DataBigQuery
  3. 03Generative AIVertex AI
  4. 04InterfaceAngular · Flask
  • Angular
  • Flask
  • BigQuery
  • Vertex AI
05 — Product + business↑ Back to the map

AI with business context.

Over seven years in digital banking (BCP / Credicorp): product, strategy and analytics before AI.

Career

  1. 2024 — present

    Advanced Data Scientist, Cognitive AI

    Artificial Intelligence Program · Credicorp

    See the full case
    • Collections conversational agent in production on WhatsApp.
    • Speech analytics, sentiment analysis and automated legal document processing.
  2. 2022 — 2023

    Business Specialist Proficient / Deputy Manager

    Digital Customers Squad · BCP

    • Led the roadmap for the digital banking activation journey.
    • Built the business case to reverse the policy banning links in commercial communications — revenue projections, cybersecurity risk analysis and communication strategy — presented up to General Management.
    • Led the digital communications front and its stakeholder committee.
  3. 2020 — 2022

    Business Specialist Senior

    Digital Customers Squad · BCP

    • Coordinated the Next Best Digital Action model with technical teams.
    • Designed customer-level Cost-to-Serve logic.
    • Led the business case and relocation plan for more than 40 remote employees, preserving salary equivalence.
  4. 2019 — 2020

    Business Specialist Advanced

    Affluent Relationship Squad · BCP

    −38%operational calls, through a differentiated call-centre service initiative

    +37%sales effectiveness on prioritised customers, by improving the lead-prioritisation model

  5. 2017 — 2019

    Pricing Analyst

    Strategic Planning · BCP

    • Supported the RARORAC simulator for wholesale banking.
    • Led a pricing strategy project for financing products.

Education

  1. 2023 — 2025

    Master’s in Edge Computing

    Universidad de Buenos Aires

    AI specialisation: deep learning, computer vision and NLP; IoT and application development.

  2. 2014 — 2018

    BSc Business & Management

    University of London

    Upper second-class honours.

  3. 2013 — 2018

    Bachelor’s in Business Administration

    Universidad del Pacífico

    Graduated second in my class.

06 — Teaching↑ Back to the map

Building knowledge. Sharing it.

University teaching in natural language processing and artificial intelligence, and thesis supervision.

07 — Talks & Events↑ Back to the map

Ideas that step off the screen.

Artificial intelligence is also built through conversation, shared experience and learning from other people. Here I gather the talks, conferences and workshops I take part in.

Upcoming

  1. Photos will be added after the event

    Coming soonConference

    From the lab to mass adoption

    What does it take for an artificial intelligence initiative to stop being an experiment and become a solution used at scale?

    In this conference I’ll explore the path from the first trials to putting AI solutions into production: the technical challenges, the strategic decisions and the conditions needed to drive real adoption.

    Because building a model is only the beginning. The real challenge is making AI work outside the lab.

    Date
    Institution
    Universidad San Ignacio de Loyola (USIL)

Technology

Tools of the trade.

AI / LLMs
LLM agents · Agent orchestration · Microsoft Agent Framework · LangChain · RAG · NLP · Speech analytics · Evaluation pipelines · Prompt engineering · Sentiment analysis
Languages & libraries
Python · Pandas · NumPy · PyTorch · TensorFlow · Transformers / Hugging Face · SQL
Cloud & infrastructure
Azure OpenAI · GCP · Vertex AI · BigQuery · APIs REST · MongoDB · Qdrant
Full-stack development
TypeScript · JavaScript · Angular · HTML / CSS
Business
KPIs · Roadmapping · Agile methods · Stakeholder prioritisation
Languages
English (advanced)

Contact

Let’s buildwhat comes next.

Portrait of Josselyn Ordóñez

For collaborations, research, teaching or conversations about applied AI.