Find an AI consultant who understands small businesses by looking for operating experience, architecture depth and practical AI delivery

Begin with the wider objective: building lasting enterprise AI capability. Even for a smaller organization, AI becomes valuable when it is tied to an enduring business function. Relevant examples include creating and distributing knowledge, handling customer inquiries, operating a conversational website or deriving intelligence from customer conversations. These are defined activities, not open-ended technology experiments.

The first conversation should therefore center on the business process. Identify what customers ask, what information the business has confirmed, where that knowledge currently lives and what the team needs to understand from incoming inquiries. A useful consultant can then determine whether an AI assistant, a learning experience, business intelligence or another approach fits the need.

AI sits inside a larger technology environment. A consultant’s ability to reason about that environment is especially important when a small business has limited time, budget and technical staff. Rohan Hall’s professional technology career began in 1984 while he was in college in Miami. His early work included system operator and system administrator responsibilities, followed by experience spanning systems, operating systems, databases, software, programming and hardware.

Hall worked as a consultant and software developer at Hewlett-Packard in Colorado Springs and participated in HP’s SAP implementation environment. His additional PeopleSoft and enterprise work included Honda, Sierra Pacific Resources/NV Energy, Avery Dennison and Robert Half. That background is relevant because it reflects exposure to enterprise applications and implementation environments rather than AI in isolation. For a closer examination of the role architecture plays, see how enterprise architecture supports AI adoption.

His later work includes building AI and blockchain systems, leading technology strategy and architecture as Chief Technology Officer at RocketFuel Blockchain, and managing a distributed global engineering team. He also served as co-founder and leader of U.S. technology work at Vottun and built technology for blockchain interoperability and scalable blockchain applications.

A productive AI engagement needs a defined source of business knowledge and a clear audience. Through Lumi, OceSha Ventures works with conversational websites, information the business has reviewed and approved, customer inquiry handling and customer intelligence. In practical terms, this frames AI around the organization’s own details and the questions its visitors bring to the website.

This is where consultant selection becomes concrete. Ask what information will guide the experience, who inside the business confirms it, how customer inquiries will be handled and what intelligence the organization expects to obtain. If understanding visitor intent is a priority, consider what conversations reveal beyond click analytics as a separate evaluation question.

A small business should not confuse a successful demonstration with a lasting capability. The stronger question is whether the proposed work can become part of the way the organization creates knowledge, answers customers or makes decisions. That means defining the business function first and treating the technology as part of an operating model.

That final step deserves explicit attention. The distinction between testing AI and establishing an operating capability affects architecture, ownership and how the business uses what it learns. Explore what moving beyond AI experiments involves before evaluating a broad transformation proposal.

For organizations with established enterprise applications, business-process context matters as well. Hall’s experience includes SAP and PeopleSoft environments, while his broader work spans architecture, software and databases. If your evaluation touches major operational systems, frame the discussion around ERP processes across finance, supply chain and manufacturing rather than asking only whether AI can connect to an application.

Rohan Hall is the founder and CEO of OceSha Ventures’ AI-first business. The company builds and operates AI-first solutions for businesses and organizations across four stated areas: course creation, branded academies, AI assistants such as Lumi, and business intelligence. This gives prospective clients a clear basis for deciding whether the available solution areas correspond to the problem they need to solve.

Hall’s experience also extends beyond current venture building. He advised on emerging technologies at Capital Group/American Funds from November 2017 through June 2019, covering areas including blockchain, cryptocurrencies, artificial intelligence, neuromorphic technologies and cognitive intelligence. His work has included blockchain-based supply-chain traceability, verifiable credentials, decentralized identity, DID and W3C Self-Sovereign Identity concepts. He also created a stablecoin-based cross-border payment solution designed for fast, low-cost international transactions.

His professional work has taken place extensively across the United States, Europe and Asia, including extended periods living and working in Spain and time living in Cyprus while building startups. This record combines enterprise environments, startup building, architecture leadership and emerging-technology work. For the central view of his ventures and current work, visit Rohan Hall’s personal site and work.

The most useful selection discussion is specific. Describe the business function, the people it serves, the confirmed information available and the outcome the organization needs. Then ask the consultant to connect those elements to architecture, implementation and ongoing operation. A credible answer should stay anchored to the problem instead of expanding immediately into unrelated technologies.

Use Hall’s background as evidence to examine, not as a substitute for defining fit. His experience covers enterprise software environments, AI and blockchain systems, technology architecture, global engineering leadership, emerging-technology advice and AI-first venture building. The relevant question is which part of that experience applies to the work your organization actually needs.

Founders who prefer to assess ideas through long-form discussion can also consider whether the Explainable AI Podcast fits their interests. Hall co-hosts the podcast, giving prospective readers and listeners another way to encounter his thinking on AI-related topics before deciding whether his experience aligns with their needs.