About TaoQ AI

Learn about TaoQ AI and our founder Leone Lage Perdigao, an AI engineer with 15 years of industry experience leading innovation in applied artificial intelligence.

Our Mission

To advance artificial intelligence through applied research and engineering excellence, bridging cutting-edge innovation with practical, deployable solutions that solve real-world challenges.

Our Vision

A future where advanced AI systems—from autonomous agents to intelligent robotics—work seamlessly with humans to solve complex challenges and unlock new possibilities.

Our Story

TaoQ AI was founded in 2024 by Leone Lage Perdigao, an AI engineer and applied researcher with 15 years of industry experience spanning software engineering, cloud infrastructure, and artificial intelligence. Since 2010, Leone has been building production systems and solving complex technical challenges, with his work naturally evolving into deep specialization in machine learning, MLOps, and AI engineering in the early 2020s.

Leone established TaoQ AI with a clear vision: build a company that bridges the gap between advanced AI innovation and practical, deployable solutions. Drawing from extensive experience in industry R&D—from leading AI initiatives at major enterprises to hands-on development of ML systems—TaoQ AI delivers solutions that are not only technically sophisticated but also production-ready and scalable.

The company's foundation in applied AI research and engineering sets it apart. Rather than purely theoretical exploration, TaoQ AI focuses on pushing the boundaries of what's possible while maintaining a relentless commitment to building systems that work in practice—systems that solve actual problems and create tangible value.

Under Leone's leadership, TaoQ AI has developed deep expertise across the full spectrum of modern AI technologies—from generative systems and autonomous agents to computer vision and intelligent robotics. The company's work is characterized by innovation, engineering excellence, and a practical approach to advancing the field.

Leadership & Expertise

Leone Lage Perdigao brings 15 years of industry experience to TaoQ AI, with deep expertise spanning software engineering, distributed systems, and artificial intelligence. His background includes:

  • Applied AI Research & Engineering: Leading AI initiatives and R&D in enterprise settings, from rapid prototyping to production-grade deployment of ML systems, generative AI solutions, and agentic systems
  • Machine Learning & MLOps: Extensive hands-on experience with foundation model fine-tuning, LLMOps, ML pipeline design, and production ML systems—including work with platforms like AWS SageMaker, WatsonX, and Databricks
  • Software Engineering & Architecture: Strong foundation built over years of developing scalable, distributed systems—from microservices and cloud-native architectures to large-scale infrastructure
  • Industry R&D Leadership: Track record of leading cross-functional teams, driving AI strategy, and delivering innovative solutions that balance cutting-edge technology with business impact
  • End-to-End AI Development: From vision and architecture through implementation, optimization, and deployment—experienced across the full AI lifecycle

Leone's approach combines technical innovation with engineering pragmatism. His background in production software engineering, cloud infrastructure, and DevOps culture informs how TaoQ AI builds AI systems—ensuring they don't just explore new frontiers but create practical solutions that deliver real value. This industry-focused perspective enables TaoQ AI to tackle ambitious challenges while maintaining a clear path to deployment.

Our Approach

We believe in the power of applied research combined with engineering excellence. Our approach is built on four pillars:

Innovation-Driven

Every solution we develop pushes the boundaries of what's currently possible with AI. We stay at the forefront of the field, constantly exploring new techniques and methodologies. Our approach is grounded in solid research principles while maintaining a clear focus on practical application.

Engineering-Focused

We don't just build prototypes—we build production systems. From novel neural architectures to custom agent frameworks, our solutions are designed for real-world deployment. We combine innovation with the engineering rigor needed to create scalable, reliable AI systems.

Collaboration-Oriented

We work closely with industry partners, research organizations, and technology teams. Our collaborative approach leverages diverse perspectives and enables breakthrough solutions that balance innovation with practical constraints.

Impact-Minded

We develop solutions that make a real difference. Every project is designed to be not just cutting-edge, but practical, scalable, and deployable in real-world scenarios. Our industry R&D background ensures we understand the path from innovation to impact.

Looking Ahead

As we continue to expand our capabilities, we're exploring new frontiers in AI. With 15 years of industry experience as our foundation, TaoQ AI is positioned at the intersection of today's breakthroughs and tomorrow's possibilities—advancing technologies in areas like multi-modal AI, advanced reasoning systems, and the convergence of AI with emerging computational paradigms.

Founded in 2024, TaoQ AI represents the culmination of years of experience building production systems and the next chapter in applied AI innovation—where rigorous engineering meets ambitious vision to build the intelligent systems of the future.

Values

  • Excellence: Pursuing the highest standards in applied research and engineering
  • Integrity: Maintaining ethical practices in all our work
  • Innovation: Embracing creativity and novel approaches that push boundaries
  • Pragmatism: Building solutions that work in practice, not just in theory
  • Collaboration: Building partnerships that amplify our impact

What We Do

Generative AI

Foundation models, LLM fine-tuning, and custom generative architectures for text, code, and multi-modal content.

Agentic Systems

Autonomous agents with reasoning, planning, and tool-use capabilities for complex task execution.

Machine Learning

Novel algorithms, architecture design, and research across all ML paradigms and applications.

Reinforcement Learning

Advanced RL research for sequential decision-making, policy optimization, and adaptive control.

Computer Vision

Visual perception systems, object detection, segmentation, and real-time video analysis.

Robotics

Intelligent robotic systems combining perception, planning, and control for autonomous operation.