Co-Founder | AI Strategy, Agentic AI & Enterprise Architecture
Co-Founder | AI Strategy, Agentic AI & Enterprise Architecture
Mohsen Asghari is a Co-Founder and AI Strategy & Architecture Lead focused on helping organizations turn artificial intelligence into practical, scalable business capabilities.
He works with organizations at every stage of AI adoption—from leaders determining where AI can create value to teams ready to design, build, integrate, and scale AI solutions across the enterprise.
Mohsen helps bridge the gap between AI strategy and technical execution. Rather than approaching AI as a collection of isolated tools or experiments, he helps organizations evaluate their business processes, data, technology environment, and strategic priorities to determine where AI can produce meaningful outcomes.
His work spans AI strategy, agentic AI, generative AI, Retrieval-Augmented Generation (RAG), enterprise AI architecture, intelligent automation, machine learning, data architecture, and AI-enabled workflow transformation.
AI transformation is as much a leadership challenge as a technical one.
We work with executives and leadership teams to translate rapidly evolving AI capabilities into practical business decisions.
Through advisory engagements and executive workshops, we can help organizations understand:
AI roadmaps • AI opportunity assessment • AI readiness • use-case prioritization • technology strategy
AI agents • multi-step AI workflows • LLM applications • intelligent automation • human-in-the-loop systems
RAG • enterprise knowledge systems • LLM integration • APIs • cloud architecture • scalable AI systems
Machine learning • NLP • anomaly detection • predictive modeling • large-scale data processing • information retrieval
AI evaluation • model reliability • responsible AI • monitoring • human oversight • information quality
Executive AI advisory • technology evaluation • vendor assessment • AI workshops • prototype strategy
Our approach starts with the business problem—not the technology.
We first identify where AI can create meaningful value. We then determine the data, technology, architecture, and workflow changes required to support it. From there, we can help validate the concept, design the system, and establish a path toward production and scale.
The objective is simple:
Build AI capabilities that solve real problems, integrate with how organizations actually operate, and create measurable business value.
Mohsen brings more than 15 years of experience across software engineering, data architecture, machine learning, and AI.
His background includes developing agentic Retrieval-Augmented Generation systems using Azure OpenAI, integrating large language models with enterprise knowledge, architecting large-scale data pipelines processing billions of records, developing machine-learning systems, and building technology solutions across cloud, healthcare, and telecommunications environments.
He holds a PhD in Computer Science and Engineering from the University of Louisville, with research focused on machine learning and natural language processing.
That technical foundation allows him to advise organizations not only on what AI could do, but on what it would actually take to design, build, integrate, and scale it.