Prophet launches agentic AI platform MAIA
Prophet, a San Francisco-based strategy and marketing consultancy, has launched its agentic AI platform MAIA (Multi-Agent Intelligent Assistant).
The platform is a one-stop shop for teams to access Prophet’s suite of AI-driven client solutions. MAIA is now available to all of the firm’s employees, and will be available for client co-creation and collaboration later this year.
MAIA integrates with client workflows and features access to multiple LLMs (Anthropic, Google, OpenAI); has a portfolio of pre-built, customizable AI agents to enhance research, insights, exploration, innovation, validation, and activation; and provides access to a network of vetted AI partners that work in conjunction with Prophet’s advisory services across marketing, intelligence, creative, and agentic workflows.
“When we surveyed the landscape, there wasn’t a solution offering broad choices, commercial agility and scalability and effective governance in one platform, and that’s why we built MAIA,” said Chan Suh, senior partner and chief digital officer, Prophet. “As the LLMs see widespread adoption and the risk of their commoditization grows, MAIA empowers business leaders and marketers to unlock growth with individualized solutions at the speed of technology.”
Prophet says MAIA’s AI-driven benefits include deeper market understanding, real-time customer pulse checks, faster-to-market pilots, and stronger business cases for new products and services.
The firm has already used MAIA to build a custom market-sizing agent for a major consumer brand and a bespoke multi-agent system for a large software company.
Prophet was founded in 1992 and has more than 500 employees across 15 offices globally. The firm has practices in business strategy, brand building, marketing excellence, experience and innovation, and organization and culture.
Prophet’s business strategy offerings include growth landscaping and opportunity identification, forecasting and scenario planning, offer portfolio optimization, and business modeling.
