BrandJet AI Launches New GTM Platform
BrandJet AI, a brand intelligence platform, announced the launch of Artemis. The new Model Context Protocol (MCP) layer is designed to help go-to-market teams use natural language to execute complex, multi-step workflows for outreach and automation.
- The Artemis platform is built on the Model Context Protocol (MCP), an open-source standard introduced by Anthropic in November 2024 to standardize how AI models connect with external data and tools. This protocol is designed to solve the problem of AI models working in isolation by giving them secure access to real-time data from various sources without needing custom integrations for each one. - BrandJet AI was founded in 2025 by Marsad Aurangzeb (formerly Siddique) and Nirav Shah serves as the CEO. The Seattle-based company is currently unfunded and aims to reduce fragmentation in the sales and marketing tech stack by unifying brand monitoring, lead enrichment, and outreach execution. - The newly introduced "Forward Deployed Account Executive" (FDAE) role is a commercial position designed to help customers integrate the AI platform into their revenue operations. This role mirrors the "Forward Deployed Engineer" position seen at other AI companies, which acts as a technical and strategic bridge between the AI platform and the customer's specific business challenges. - Go-to-market (GTM) teams are increasingly adopting AI, though a 2025 survey showed that 83% of leaders estimated less than half of their team uses AI for their job. AI is used in GTM to synthesize customer data, identify market trends, define target audiences, and automate marketing workflows to make outreach more personalized and efficient. - BrandJet AI's platform aims to consolidate a typically fragmented GTM toolkit, which often includes separate systems for monitoring brand mentions, identifying prospects, enriching data, and managing outreach campaigns. The goal of Artemis is to allow users to execute these multi-step processes using natural language commands, reducing the manual handoffs between different platforms. - The Model Context Protocol (MCP) functions like a universal connector, allowing an AI application (the "host") to communicate with various external data sources and tools (the "servers") via a standardized client-server architecture. This enables AI agents to perform actions like querying a database or sending an email, moving beyond static knowledge to dynamic, real-time operations.
