Rakia Finley
Turning working technology into deployable systems and accountable decisions
London, United Kingdom
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Rakia Finley works at the point where technology, operating reality, and executive decision-making meet. As a technology strategist and enterprise readiness advisor with Copper & Vine Studio, Rakia helps technical founders, product leaders, and mission-led organizations determine whether a promising system is truly ready to deploy, govern, and scale.
Rakia’s work connects the decisions that are often separated: product and architecture, data and measurement, governance and ownership, automation and human judgment, and growth and unit economics. The result is not another strategy document. It is a decision structure leaders can use to choose what to build, what to stop, what evidence is missing, who owns the next action, and what must change before implementation.
On stage, Rakia teaches practical readiness gates for trustworthy AI, automation, product launches, and evidence-based governance. The through line is simple: working technology is only the beginning. Readiness is what makes it usable, explainable, accountable, and commercially durable.
As the Founder and CEO of Copper & Vine Studio, she advises startups, enterprises, public-sector organizations, and emerging leaders on how to responsibly scale technology, build resilient operating systems, and prepare institutions for the next era of AI-enabled business and society.
Her work focuses on translating complex innovation into practical implementation; helping organizations move from fragmented experimentation into scalable systems, governance frameworks, operational clarity, and measurable growth. She is especially known for her ability to bridge executive strategy, emerging technology, security, human behavior, and organizational design into conversations that are both visionary and deeply actionable.
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Topics
Zero Trust + Open Source: A New Compliance Blueprint for Financial Systems
Financial innovation shouldn’t come at the cost of regulatory chaos. But as firms race to modernize tech stacks, many risk introducing gaps in security, governance, and stakeholder trust. In this talk, Rakia Finley presents a battle-tested blueprint for embedding compliance directly into digital product design—leveraging open-source components with zero-trust architecture. She’ll showcase how her team at Copper & Vine helped a fintech organization align their product pipeline with DORA and ISO standards using open-source tools, secure-by-design patterns, and proactive threat modeling. Rakia will also highlight how inclusive governance can reduce risk by aligning systems with the communities they serve.
Your Agent Left Evidence. You Just Don't Know How to Read It Yet.
When an agent gets compromised, the context window is a forensic artifact. The KV cache held the injection. The orchestration state logged the lateral move. The retrieval context carried the payload. None of it showed up in your SIEM because nobody told your logging pipeline that these things existed, let alone that they were worth capturing.
This talk opens by carving a prompt out of a memory dump from an agent orchestration process — walkthrough style, showing exactly where it lived in the memory hierarchy and why conventional detection missed it entirely.
From there: a breakdown of the four AI memory layers that matter forensically (host RAM, GPU HBM, context window, agent orchestration state), weighted toward context window and orchestration state because that is where the actual risk concentrates in production agentic systems. The specific logging failures that make AI-augmented attack surfaces invisible — no prompt logging by default, no tool-call provenance, encrypted API traffic, reasoning traces discarded, retrieval context not retained. The distinction between a memory-resident payload and a memory-resident instruction, and why that distinction changes your IR playbook. What your stack should be logging, how to instrument it, and a forensic readiness checklist attendees take home, mapped to MITRE ATLAS technique IDs.
The Real Cost of Fast AI: How to Build Systems That Don’t Break the Future
Everyone wants to build fast, but the infrastructure behind AI innovation often buckles under scale, security concerns, or ethical misalignment. This panel brings together product leaders, data scientists, and CTOs who have had to choose between speed and sustainability. Rakia will moderate or contribute insights into how organizations can balance velocity with architectural foresight and social responsibility.
Secure by Design: Embedding Ethics and Resilience in AI-Driven Systems
As organizations race to adopt AI, the failure to embed ethical and resilient design in data systems has led to operational and reputational risks. In this session, we’ll explore how enterprises can implement secure-by-design principles to mitigate vulnerabilities in AI system architecture. Drawing from real-world projects in healthcare, government, and finance, attendees will learn how to elevate their AI infrastructure while aligning with ethical and compliance standards from day one.
Secure By (Human) Design: Integrating Behavioral Architecture into Software Security
The next frontier of secure software isn’t just code it’s the people writing it, deploying it, and trusting it. In this session, Rakia Finley explores how secure design must expand beyond technical patterns to include behavioral systems, decision environments, and inclusive collaboration across engineering, design, and leadership. Drawing from enterprise product launches, startup DevSecOps adoption, and systems theory, Rakia will walk attendees through a model for embedding secure thinking at every human and technical layer. From engineering rituals to risk architecture, this talk makes the case that secure software starts not with tools, but with intention.
nclusive AI at Scale: Designing Transparent, Auditable Financial Systems from the Start
The promise of AI in finance hinges not only on performance but on explainability, compliance, and inclusion. In this session, Rakia Finley, Fractional CTO and Managing Partner of Copper & Vine, explores how open-source frameworks can be harnessed to create AI systems that are both audit-ready and user-conscious. She’ll walk through a real-world case study of deploying an AI-powered financial advisory tool across underserved markets, with attention to bias mitigation, regulatory transparency, and scalable architecture. With a 20-year background building ethical tech for the White House, Apple, and global impact startups, Rakia offers hard-won lessons for anyone architecting intelligent systems for real people—and real scrutiny.
From Systemic Gaps to Shared Models: Equity-Driven Standards for Financial Interoperability
The Common Domain Model (CDM) offers a unified standard, but to be truly transformative, it must reflect the diversity of the systems and users it intends to serve. In this session, Rakia Finley challenges the assumption that interoperability is neutral. She outlines a new approach to CDM design grounded in inclusive modeling, real-world stakeholder mapping, and adaptive system architecture. Through case examples from public-private innovation projects, she demonstrates how equity-aware frameworks can reduce friction, enhance trust, and future-proof standardization efforts across the financial landscape.
From Spreadsheet to Strategy: Building AI-Ready Infrastructure for Enterprise Decision-Making
Many enterprise AI efforts stall because the underlying data infrastructure wasn’t designed with scale, ethics, or security in mind. In this hands-on session, Rakia will guide attendees through the core elements of transitioning from legacy data ops to an AI-optimized backend. We’ll cover modular architecture, data audit trails, and real-time system observability—all without requiring a complete rebuild.
Agentic DevOps in Action: Building Resilient AI Microservices with .NET & Azure
This immersive 2-day lab walks development teams through building a secure, AI-enabled microservices stack using .NET, Azure OpenAI, and Azure Kubernetes Service (AKS). Participants will go from design to deployment, applying DevSecOps practices and leveraging agentic development patterns. This workshop is tailored for teams preparing to scale GenAI workloads without sacrificing control, compliance, or performance.
What AI Agents Actually Need from Your Cloud Stack
Everyone wants an AI assistant. No one wants to maintain the infrastructure behind one. In this practical session, Rakia Finley unpacks the cloud-native realities of building AI agents that aren’t just cool but stable, scalable, and secure.
You’ll learn what RAG workflows actually demand of your storage and container orchestration, how to build latency-aware event pipelines that play nice with LLMs, and what monitoring looks like when your system is generating outputs you can’t always predict. Whether you’re prototyping GenAI features or scaling a production-ready AI tool, this talk helps you make sure your stack is ready for the complexity ahead.
The GenAI Stack is Broken: What I Learned Rebuilding It for Real Clients
Most GenAI demos are slick. Most GenAI systems in the wild are brittle, confused, and failing at scale. In this session, Rakia Finley breaks down what happens when GenAI moves from the lab to real-world production. From hallucinating customer support agents to broken RAG pipelines and silent prompt injection vulnerabilities, she’ll share hard-earned insights from shipping systems for social ventures, government teams, and startups racing toward product-market fit. You’ll walk away with a clearer picture of how to architect GenAI infrastructure that doesn’t collapse under pressure and how to avoid building a Frankenstein of disconnected tools and plugins.
Beyond the Prompt: Building Generative Agents that Think with Context
A good GenAI agent doesn’t just respond, it reasons. But most of what we’re seeing today is just prompt-chaining dressed up as intelligence. In this session, Rakia Finley walks through what it takes to design generative agents that truly leverage memory, task orchestration, and operational context. She’ll share real use cases from startups and enterprise environments, highlighting design decisions that unlock smarter behavior and pitfalls that leave agents stuck in loops. Whether you’re a builder or just GenAI-curious, you’ll leave with a better understanding of where agentic design is heading and how to start building systems that think before they talk.
Privacy by Pattern: Architecting Ethical AI into National-Scale Platforms
How do you design AI systems that respect privacy at scale across borders, bureaucracies, and behavioral patterns? In this talk, Rakia Finley shares behind-the-scenes insights from her work architecting enterprise-grade, AI-powered platforms for civic, financial, and healthcare institutions. Rather than bolt on compliance late in the lifecycle, she’ll demonstrate how to use design patterns, embedded logic, and multi-system orchestration to build governance-first infrastructure. This isn’t about checkboxes, it’s about pattern-matching privacy into every layer of your stack so regulation doesn’t become the bottleneck to innovation.
Trust, But Verify: LLMs, Prompt Injection, and the New Frontier of Secure AI Dev
Prompt injection is one of the most underestimated attack vectors in modern .NET applications using LLMs. In this lightning-fast talk, Rakia breaks down how developers can proactively secure AI prompts in app workflows, monitor misuse, and implement real-time controls. You’ll walk away with actionable Visual Studio tooling and GitHub workflow integrations that prevent prompt exploitation before it reaches production.
From Prompt to Breach: Memory Forensics in AI-Augmented Attack Surfaces
AI-augmented applications are redefining the attack surface, from prompt injection in LLMs to memory-resident payloads that blur the lines between inference and intrusion. This session examines real-world case studies where generative AI systems were exploited and how memory forensics plays a pivotal role in uncovering volatile threats. We’ll walk through advanced techniques for detecting and analyzing malicious behavior in memory, especially where conventional logging fails, and offer a forward-facing look at what “threat surfaces” truly mean in a post-AI era.
Beyond Prompts and Policies: Threat Modeling the Invisible Risk in AI Systems
While most AI conversations center on data privacy and model hallucinations, the real threat lies in what we don’t model: shadow APIs, opaque decision layers, and system misuse vectors. This session breaks down how to threat model AI pipelines from the start, including open-source tools, role-based red teaming, and mapping misuse early.
Designing Cross-Platform AI with Responsibility in Mind
AI in mobile apps shouldn’t just be lightweight; it should be accountable. As more teams build with Flutter, Firebase, and cross-platform ML tooling, the need for ethical-by-design systems is more urgent than ever.
In this session, Rakia Finley shares a playbook for building AI features into mobile and cross-platform products using Google tools without sacrificing transparency, user autonomy, or performance. She’ll cover edge compute with TensorFlow Lite, privacy-aware analytics in Firebase, and platform design principles that reflect human-centered tech.
Human in the Loop: Engineering AI with People at the Center
As AI systems grow in autonomy and complexity, the role of human oversight is more critical than ever. In this session, Rakia Finley—CEO of Copper & Vine Studio and CTO of SökerData—makes the case for “human-in-the-loop” design as both a moral imperative and a systems engineering advantage. She shares how the most effective AI ecosystems aren’t fully autonomous—they’re co-designed with people at the core.
Drawing from 20+ years of building human-centered technology for governments, global health orgs, and startups, Rakia outlines how human empathy, intuition, and context must be integrated into AI pipelines—from training and validation to deployment and accountability. With practical takeaways and proven frameworks, this session will challenge technologists to think beyond automation and build AI systems that adapt to people—not the other way around.
What You’ll Learn:
- What “human-in-the-loop” means beyond compliance—and how to architect it
- Where and when human oversight strengthens AI outcomes
- Case studies from real-world AI systems in health, gov, and social sectors
- How to build multidisciplinary teams that center empathy and accountability
- Why people-centric AI drives better product design, trust, and resilience
No Justice, No Models: Designing Responsible AI from the Stack Up
We talk a lot about fairness in AI, but rarely about where fairness lives. Hint: it’s not just in your dataset. This session dives into the technical stack decisions, data engineering, inference orchestration, cloud storage models, and pipeline governance that shape AI behavior long before it reaches the interface.
Led by Rakia Finley, Fractional CTO and founder of Copper & Vine Studio, you’ll explore how today’s cloud-native architectures (including Google Cloud tools) can either scale equity or reinforce bias depending on how they’re structured. With real-world examples from social impact tech, Rakia will show how to align performance with responsibility across the AI lifecycle.
Leading AI with Intention: How CTOs Can Embed Ethics into Every Layer of the Stack
This session explores practical frameworks for embedding ethical principles into AI design and deployment, with insights from Rakia’s real-world experience leading public and private AI systems. Learn how to align business outcomes with ethical responsibility at scale.
Threat Models Aren’t Enough: Building AI Systems That Defend Themselves
We’ve reached the tipping point where AI models are not just tools, they’re targets. Yet, too many organizations are trying to protect AI systems with yesterday’s threat models. In this session, Rakia Finley draws on her experience designing AI-infused platforms for critical industries to reframe how we secure next-gen systems: with self-defending architecture that evolves with every prompt, query, and edge case. Attendees will explore common LLM attack vectors, breakdowns in enterprise model pipelines, and where fine-tuning meets fine-failure. You’ll leave with practical strategies for governing AI behavior, protecting datasets, and ensuring that models act in the interest of your users, not your attackers.
Rakia Finley
Turning working technology into deployable systems and accountable decisions
London, United Kingdom
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