Ex-McKinsey and BCG team launches AI platform aimed at cutting enterprise costs

A Houston-based AI platform built by former McKinsey and BCG professionals says it can cut enterprise infrastructure and analytics costs by up to 80% while speeding decisions from weeks to hours. The pitch targets FMCG companies under pressure to reduce consulting spend, lower cloud and LLM costs, and improve execution.

Why it matters: - Decision Pulse AI is aimed at a common enterprise problem: high spending on consulting, analytics and AI infrastructure with slow returns. - The platform is positioned to help FMCG and other large companies move from insight generation to automated action, which could reduce delays in pricing, inventory and supply chain decisions. - The company says the approach could lower infrastructure and analytics costs by up to 80%.

What happened: - Decision Pulse AI was launched by former McKinsey and BCG professionals in Houston. - The platform is designed for enterprise decision intelligence and focuses on moving decisions into execution. - The press release highlights a U.S. FMCG company case study that could save $12 million annually using the platform. - A demo request link was provided: For a demo.

The details: - Decision Pulse AI connects data across ERP, CRM, supply chain and marketing systems. - The platform is built to generate real-time insights, recommend decisions and trigger actions inside enterprise systems. - The company says the system also optimizes infrastructure and LLM usage to reduce operating expense. - The release says the platform embeds consulting-style logic and coordinates decisions across functions. - The release points to four target use cases in FMCG: demand forecasting and inventory optimization, pricing and promotion optimization, supply chain efficiency and marketing spend optimization. - In the demand and inventory use case, the platform is described as enabling real-time demand sensing, automated inventory rebalancing and dynamic production planning. - In pricing and promotions, the platform is described as enabling continuous price optimization, automated promotional adjustments and competitor-aware pricing. - In supply chain, the platform is described as supporting predictive adjustments, automated rerouting and real-time disruption management. - In marketing, the platform is described as supporting real-time campaign optimization and dynamic budget reallocation.

Between the lines: - The release reflects a broader shift in enterprise software from dashboards and analysis toward systems that make or execute decisions. - The emphasis on former McKinsey and BCG talent is meant to signal both strategy rigor and operational credibility. - The cost-savings message suggests the selling point is not only AI capability, but AI economics. - The $12 million savings figure is presented as a modeled case study, not a disclosed customer contract.

What's next: - Decision Pulse AI appears to be pursuing enterprise adoption through demos and use-case-led sales. - The platform’s next test is whether it can show repeatable savings and faster execution across additional customers and industries. - For more information, the company directs readers to its demo request page.

The bottom line: - Decision Pulse AI is pitching itself as a way for enterprises to cut costs and automate decisions, not just analyze them.