Global Industry Consulting Firm – AI Advisory & Getting Started, and AI-Driven Engineering & Safety Workflows
US-based industry consulting firm with regional headquarters in Singapore, serving oil & gas, chemicals, and manufacturing clients across Asia-Pacific.
Engagement scope: AI Advisory and Getting Started engagement with top management, AI automation across engineering document workflows, process safety, and field operations.
The client was highly-technical, experienced and AI-savvy, representing numerous AI vendor partners to its clientele. However, adoption of agentic AI internally had yet to take off. The services arm of the client faced high manual effort across four parallel workflows: Hazard & Operability (HAZOP) documentation analysis, Piping & Instrumentation Diagram (P&ID) redline extraction, Quality Assurance/Quality Control (QA/QC) defect detection, and Process Safety Management (PSM) system integration. Each was handled manually with significant engineer time and error risk.
B-Sharp AI held AI Advisory and Getting Started sessions with the management team to get them up to speed using agentic AI in their daily routines. B-Sharp AI also deployed custom AI pipelines for each manually-intensive workflow using Claude and Anthropic APIs. The solutions included an agentic AI integration for one of their client's PSM systems, as well as integration to a mobile 5G & IoT hub for field deployment using head-mounted tablets and similar devices. Additionally, an AI platform comparison analysis was conducted to support the client's broader agentic AI strategy.
Management team brought up to speed to gain the power of agentic AI. Automated pipelines deployed across all four engineering workflows, reducing manual engineer effort and improving accuracy of safety-critical documentation. Platform comparison analysis delivered as a structured decision framework for the client's agentic AI investment planning.
Major Australian Retailer – Agentic AI for S&OP
Australia's largest home improvement retailer. Engagement with head of Sales & Operations Planning (S&OP).
Engagement scope: agentic AI adoption across S&OP and supply chain execution.
Manual S&OP exception management was creating bottlenecks across a high-volume, high-SKU supply chain. Forecast exceptions and supply execution alerts required human intervention at a scale that was not sustainable. The organization needed AI that could triage, prioritize, and act on exceptions – not just flag them.
B-Sharp AI conducted a structured agentic AI readiness assessment and designed a two-platform architecture taking advantage of tools and infrastructure the client already had in place but was not utilizing: Microsoft Copilot / Copilot Studio for supply chain execution exception automation, integrating with existing Microsoft infrastructure; and Blue Yonder Cognitive Solutions for demand forecast exception management, enabling an AI-driven S&OP workflow automation. A phased adoption roadmap was delivered covering 24 months of deployment, with projected benefits modeled against current manual intervention costs and lost margin from unresolved exceptions.
Projected benefits of A$42–80 million over 24 months across inventory optimization, exception resolution velocity, and demand forecast accuracy.
Deliverable: board-ready roadmap and business case.
Singapore Healthcare Provider – AI Getting Started & Website Automation
Independent dental clinic, Singapore.
Engagement scope: AI in-housing, systems analysis, and agentic website automation.
The client had limited resources for internal administrative and systems support, relied heavily on outsourcing for website and application development, and had no clear view of how to optimize AI usage internally. The objective was to establish self-sufficient AI use and automate routine digital tasks – without adding headcount while reducing reliance on outsourcing.
B-Sharp AI delivered an AI getting-started program covering tool selection, governance, and prompt engineering, alongside a full systems analysis for integration planning. An agentic AI pipeline was built for website development, improvement, and deployment using Claude / Cowork, Vercel / GitHub, WhatsApp MCP, and LinkedIn MCP.
Client achieved self-sufficient AI use across core business functions within the engagement period. Website now maintained and deployed through an automated pipeline with no developer dependency. In-housing plan delivered with defined roles, tools, and governance framework.
US Law Firm – Website Assessment & AI Search Optimization
Established family law practice in the Pacific Northwest, US, with over 35 years of operation. The firm offers a distinctive collaborative legal model and relies on its website as its primary channel for attracting new clients across a multi-county service area. The site had been live for several years without a formal assessment of its effectiveness in reaching prospective clients.
Engagement scope: comprehensive, agentic AI-enabled, website review covering AI search visibility, content strategy, technical configuration, legal compliance, accessibility, and security.
The legal industry is undergoing a fundamental shift in how prospective clients discover and evaluate firms. Industry data shows that over 77% of legal search queries now trigger AI-generated overview answers, and AI-referred traffic to legal websites more than doubled between 2024 and 2025. The firm's website had no structured data, no content optimized for AI citation, and no strategy to ensure visibility in this rapidly growing discovery channel. The firm's genuinely distinctive service model – a strong candidate for AI-generated citations – was not structured in a way that AI search engines could identify, interpret, or reference.
B-Sharp AI used an agentic AI-enabled process to conduct the assessment – programmatically retrieving and analyzing all pages across 11 dimensions including AI search visibility and Generative Engine Optimization (GEO), SEO and technical configuration, content quality, desktop and mobile usability, visual design, security (31-control library), and compliance. The agentic workflow enabled a depth and consistency of analysis across the full site that would be difficult to achieve manually, identifying specific structural changes needed to position the firm's content for citation by Google AI Overviews, ChatGPT, Perplexity, and other generative search engines. The review also brought the site's legal, privacy, and accessibility posture up to current US federal and state standards.
Delivered a prioritized three-tier roadmap with immediate, 30-day, and ongoing recommendations. The firm received a clear path to AI search competitiveness built around its unique service offering, along with modernized compliance documentation and improved technical configuration. All recommendations were designed to be implemented on the existing platform without migration.
US Hospitality Property Owner – Fire Safety & Security Assessment
Owner of a rural bed-and-breakfast property in central Texas seeking an independent assessment of wildfire and physical security risks.
Engagement scope: evidence-based, agentic AI-enabled, risk assessment, fire protection options analysis, and security system design, all within a defined budget.
The property was located in a region experiencing elevated wildfire conditions, with the majority of the state under active drought classification during peak fire season. The owner needed a clear, research-backed understanding of the actual risk level and which protection measures would deliver the greatest impact for the investment. Commonly marketed fire-retardant treatments needed to be evaluated objectively. The property also required a practical security system suited to a rural setting, ideally with no ongoing subscription costs.
B-Sharp AI used an agentic AI-enabled research process to conduct the assessment, drawing exclusively from government agencies, national standards bodies, and peer-reviewed academic publications – no blogs, vendor marketing, or unverified sources. The agentic workflow systematically evaluated wildfire risk data, protection options, product claims, and security system architectures, producing a level of source-verified analysis that would typically require significantly more time through conventional research methods. The analysis identified a key existing structural asset that eliminated the single most expensive wildfire protection upgrade, then designed a phased program around the three remaining priorities. Fire-retardant coatings were evaluated against peer-reviewed weathering studies and determined to be ineffective in the local climate, redirecting budget to higher-impact measures. For security, a locally-stored system was designed with specific solutions for monitoring a remote entry point beyond standard wireless range.
Delivered a phased investment plan projecting an estimated 80% reduction in fire vulnerability, with the highest-priority measures representing a fraction of total potential spend. A complete security system was specified, enabling no ongoing subscription costs to the client for the continued security of the property. The report included a property-specific questionnaire for obtaining contractor quotes and immediate-action items timed to the active fire season.