Karthick Raju

Karthick Raju

Chief of AI and Co-Founder, NeoBram

Karthick leads NeoBram's AI engineering practice, helping industrial organisations turn business problems into a practical technical plan and a working system.

01

Karthick’s role in the AI practice

Karthick’s role includes use-case qualification, architecture and evaluation, together with the responsibilities needed to put a system into production. Customer experts define process rules, explain difficult cases and review the result.

The delivery lead, engineering roles and customer responsibilities for a particular project are agreed when the engagement is scoped.

02

Start with the operating decision

The first questions are about the work: who makes the decision, what information they trust, how an error affects the business and how improvement will be measured. Those answers guide the choice of model, software and deployment environment.

A useful first discussion can begin with a recurring problem and a person who understands it. The technical specification follows once the need and the available evidence are clearer.

03

Make the deployment boundary explicit

Private AI involves more than where a model is hosted. Access, data flows, updates, backups, licensing and support also affect how a system operates. Local, fully offline and connected systems have different dependencies. These need to be understood before implementation.

04

Judge the result in the real workflow

Industrial AI needs relevant evidence, meaningful tests and a person accountable for consequential decisions. For an assistant, that can mean checking both the retrieved material and the answer. For a prediction, it means examining whether the output improves a decision the team can actually make.

A pilot should provide evidence for continuing, revising or stopping the work. The evaluation needs to include difficult cases, uncertainty and the effort people spend reviewing the result.

05

Bring the problem before the specification

Tell us about a decision, document task or operational problem your team wants to improve. The next step is to identify the evidence, expertise and scope needed to assess it.

More clarity

Questions and answers

Who will work on our project?

The delivery lead, engineering roles and customer responsibilities are agreed when the engagement is scoped.

Can we discuss an idea before it becomes a specification?

Yes. Describe the task and what makes it difficult. We can then identify what information is needed to assess an appropriate next step.

Start with one business problem

Discuss an industrial AI problem

Discuss an industrial AI problem

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