Mphasis, a global AI-led technology solutions provider, has announced the acquisition of Theory and Practice Business Intelligence Inc. (TAP). Based in Vancouver, TAP is the developer of Continuum AI, a Decision Intelligence platform that merges advanced AI with behavioral economics. The acquisition includes an upfront consideration of CAD 10 million, with potential milestone-based payments of up to CAD 20 million.
The Acquisition: Mphasis acquires Theory and Practice (TAP) to integrate its Decision Intelligence layer.
The Platform: Continuum AI, a modular system focused on demand forecasting, pricing, and supply chain optimization.
Strategic Integration: TAP will become a core component of Mphasis’ NeoIP™ platform, adding a causal modeling and behavioral economics layer.
Key Leadership: TAP Founder & CEO Dr. Rogayeh Tabrizi joins Mphasis as Executive Vice President – CPG and Head of Decision AI.
Target Industries: Financial Services, Retail, and Consumer Packaged Goods (CPG).
Focus Shift: Moving beyond simple task automation toward systems that reason over business objectives and constraints.
While many AI tools focus on descriptive or predictive analytics, TAP’s Continuum AI specializes in the Decision Layer. By using causal inference and optimization, the platform helps enterprises understand why consumers behave in certain ways and translates those insights into intervention strategies. This approach is particularly valuable for high-stakes business decisions in pricing, marketing promotions, and revenue optimization.
"TAP’s Continuum AI will be a key catalyst for NeoIP™," said Nitin Rakesh, CEO and Managing Director of Mphasis. "This combination allows us to move beyond task automation towards systems that can reason over business objectives... to deliver measurable economic outcomes."
The acquisition strengthens Mphasis' "context engineering" layer. According to Ramanathan Srikumar, Chief Solutions Officer at Mphasis, a robust layer that structures context and links concepts is foundational for agentic workflows. By integrating TAP’s reusable model ontologies, Mphasis enables AI agents to perform higher-order reasoning, ensuring that AI-driven outcomes are designed, executed, and measured with precision.
Dr. Rogayeh Tabrizi brings a unique academic background to Mphasis, having worked on the ATLAS Detector at CERN and studied under renowned Stanford economist Professor Matthew Jackson. Her expertise in particle physics and economics provides the scientific rigor behind TAP's behavioral AI models. "Together, we are building a path for Enterprises from experimentation to repeatable and scalable value," said Dr. Tabrizi.
Mphasis is an AI-led, platform-driven company that helps global enterprises modernize and scale with agility. Through its NeoIP™ platform and Front2Back™ transformation framework, Mphasis embeds autonomy and intelligence into every layer of the technology stack, serving marquee clients across the globe.
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