cleopatra douglas

Build Fintech AI Systems That Actually Ship

Goldman Sachs

Flutterwave

GUARANTY Trust Bank

Cleopatra Douglas

CEO & Co-Founder, Recital Finance | ex @ Goldman Sachs, Flutterwave (YC Unicorn)

Identify the 3 architectural mistakes that kill fintech AI projects, and the decision patterns that prevent them.

Why fintech AI projects fail before production

You'll see a real reconciliation agent in action and understand how to structure autonomous workflows around messy data

How to design an agentic workflow for financial data

Leave with a checklist covering observability, ML lifecycle, and the guardrails that separate demos from shipped systems

The production checklist nobody teaches you

Lead AI initiatives with clear goals, defensible evaluation, explicit risk decisions, and exec updates that drive alignment and investment.

CPO, GM xBraintrust, Nextdoor, OpenTable

Braintrust 🧠

Nextdoor

LiquidSpace I Work from where it works.

OpenTable

BlackRock

Elena Luneva

f-CPO. Product executive (Braintrust, Nextdoor, OpenTable, LiquidSpace)

Ex-Alexa AI Principal PM

Amazon

Elsevier

Schneider Electric

Polly Allen

Ex-Alexa AI PM turned founder at AI Career Boost

Magic

Juggernauts

AI increases what your ICs can do. It also breaks the management systems most teams rely on.Prototypes multiply. Quality becomes subjective. Risk ships quietly. You end up in every review because no one is sure what "good" looks like — or who's accountable for evals, failure modes, and rollout decisions.If you're a Director, Head of Product, or VP with multiple AI initiatives in flight: you're managing something you didn't build a system for yet. Execs keep asking "How do we know it's good?" and "What's the ROI?" — and you're the one fielding it.This two-day workshop gives you the operating system. Not theory. Not frameworks. The actual playbooks, artifacts, and rituals high-performing, AI-native teams use — built during the workshop so you leave with real deliverables, not homework.Leave with:1. A 90-day AI portfolio — clear bets, owners, and decision gates so nothing gets orphaned2. A repeatable risk review process your team can run without pulling you in3. A shared quality bar — examples, acceptance criteria, and review gates so "is this good enough?" stops being a judgment call4. Reusable operating artifacts built during the workshop — actual deliverables, not slides

Get the operating system used by high-performing AI-native teams

Install an AI-native operating cadence that keeps speed and alignment

Run AI risk reviews that drive decisions and confidence

Own and drive evaluation metrics and process, before and after launch

Implement playbooks that let your team move with you, not wait for you

Director/Head of Product: Leads AI initiatives; turns prototypes into production with clear quality, gates, and exec updates.

Eng leader (Sr Mgr/Dir/VP): Ships AI fast while managing reliability, security, and cost with consistent eval + risk reviews.

Data/ML leader (Dir/Head): Owns evals and performance; aligns product and execs with shared language and decision-ready tradeoffs.

Future-proof your finance career by mastering AI tools, predictive modeling, and autonomous agents that handle real finance workflows.

Cohort 1

Professor & AI Expert (540K+ Students)

Microsoft

General Motors

Samsung

HSBC

Dr. Ryan Ahmed

Professor, AI expert, & YouTuber who has taught 540,000+ learners worldwide.

Cohort 2

⭐"Join the instructor trusted by 540K+ students with 40K+ five-star reviews and 50M+ minutes of AI training watched worldwide."AI Agents are transforming how business and finance teams operate. 6 months ago, building a financial model took a junior analyst ~1 day. Today, a team of autonomous AI agents builds, audits, reports, and presents it in 10 minutes.Organizations are moving beyond manual workflows toward AI-native systems, where intelligent agents analyze data, generate reports, and automate tasks.The problem: Most professionals still use AI for basic Q&amp;A, they lack the skills to build AI agents that execute real business and finance tasks autonomously.The solution: This bootcamp teaches you to build intelligent agents that reason, use tools, access data, and complete workflows automatically using Claude Code, Cowork, &amp; Copilot agents.What makes this bootcamp unique?<ul><li>AI Agent Workflows: Automate research, reporting, and operational tasks</li><li>Build AI Agents: Connect agents to financial data and generate insights</li><li>Predictive Analytics: Use ML agents for forecasting, classification, and risk scoring</li><li>Autonomous Agent Teams: Deploy teams of agents that collaborate and improve continuously</li></ul>

Build AI Agents That Automate Business & Finance Workflows & Get Certified

Automate Business & Finance Workflows with AI Agents

Build Predictive Financial Models with AI Agents

Connect Agents to Financial Data with MCP

Build & Deploy Autonomous Finance Agent Teams

Master Agent Architectures & Guardrails

Capstone: Deploy an End-to-End Agent System

Finance Professionals &amp; Analysts wanting to automate workflows, build predictive models, and deploy AI agents for reporting and forecasting.

CFOs, Controllers &amp; Finance Managers who want to lead AI adoption and deploy autonomous agents for reconciliation and decision support.

Data-Savvy Accountants &amp; FP&amp;A Teams who want to move from manual spreadsheets to AI-powered workflows that analyze and forecast at scale.

Stop watching AI tutorials. Start shipping.

Ship your first agent in one morning

Apple

LinkedIn

Udemy

Nathan Wang

20+ AI Agents Running 24/7 | 18 Products | PhD Engineer/TPM @ Apple & Meta

Workshop 1

Most people spend months watching AI tutorials. They understand the concepts. They still haven't shipped anything.This workshop changes that.In 2 hours, you'll build a real working AI agent — one that solves a problem you actually have. Not a toy demo. A deployed agent you can use starting today.I run 20+ AI agents that manage my social media, trade my portfolio, and run my entire business — with no team, while holding a day job and raising two kids. Every single one started the same way: one afternoon, one problem, one build.This is that afternoon.Attendees receive a promo code at the end to apply the full $497 workshop cost toward AI Superpower Cohort 3.

By the end of this workshop, you'll have:

A deployed, working AI agent

The 3-layer architecture pattern

Confidence to build more

PMs, Founders &amp; Operators — You have workflows you want to automate. You’ve seen the demos. Now you want to build one yourself.

Non-technical builders — You don’t code — and you don’t need to. If you can describe a problem, you can build an agent with Claude Code.

Engineers who want to move fast — You can code, but you want the 3-layer agent architecture pattern that lets you ship in hours, not weeks.

Find and prioritize your AI's biggest failures in 2 days — using your own data.

ML Engineer with 20+ years experience

Airbnb

GitHub

DataRobot

Hamel Husain

Trained 4,000+ AI practitioners from 500+ companies on AI evaluation.

ML Systems Researcher 

Google

Stanford University

UC Berkeley

Shreya Shankar

ML Systems Researcher Making AI Evaluation Work in Practice

Cohort 1: Debug Your Data

This isn't a course — we roll up our sleeves and work on your product with your data.You bring your real traces and interaction logs. Over 2 days, we systematically find where your AI is breaking down, why users are losing trust, and what to fix first. Most teams building AI products are stuck in the same loop: ship a change, hope it helps, manually spot-check a few outputs, repeat. Meanwhile, users hit failures nobody on the team has even seen.In this private workshop, we break that cycle. You bring real traces and interaction logs from your product. Together, we systematically uncover where your AI is breaking down, build a catalog of failure modes specific to your use case, and leave with a prioritized plan to fix what matters most.This methodology has been refined across 4,000+ practitioners from 500+ companies, and is part of what we teach in our <a target="_blank" rel="noopener noreferrer nofollow" href="https://maven.com/parlance-labs/evals">full-length course</a>. It's the highest-ROI activity in AI product development.Each workshop can accommodate a team of up to 6 participants. We can help you identify which team members to bring (trust us, you don't want more than 6).Below is a sample agenda, this can be customized to your needs and schedule.

Walk away knowing exactly where your AI product is failing, why, and what to fix first — with a concrete plan your team can execute immediately.

Find hidden failure patterns in your AI product

Build a prioritized roadmap to fix what matters

Design metrics that prove your fixes work

This workshop is hands-on with your data. You need a deployed product generating real interactions we can analyze together.

A live AI product or feature with real users

We work directly with your production data. You'll receive a prep guide with instructions on what to collect and how to format it.

Access to recent traces or interaction logs

Engineers, PMs, and domain experts who know the product. The best results come from cross-functional teams who can act on findings immediately.

A dedicated team of 2-5 participants

Engineering teams with a live AI product that has real users.

Product managers responsible for AI features who need a data-driven improvement plan instead of guessing which changes will move the needle.

Technical leaders who want to stop relying on manual QA and spot-checks, and instead build a systematic approach to improving AI quality.