BrandJet AI Launches New 'Artemis' Layer
BrandJet AI, a brand intelligence platform, announced the launch of Artemis, a new Model Context Protocol (MCP) layer. The technology is designed to help go-to-market teams execute complex, multi-step workflows using natural language. The company also introduced a new "Forward Deployed AE" role to support AI-driven sales and marketing teams.
- The "Artemis" layer is built on a Model Context Protocol (MCP), an open standard initially released by Anthropic in late 2024 that allows AI models to connect with external data sources and tools in a standardized way. This architecture is designed to unify BrandJet AI's capabilities for monitoring brand mentions, enriching data, and executing outreach into a single layer that can be controlled by natural language prompts. - The newly introduced "Forward Deployed Account Executive" is a hybrid role that mirrors the "Forward Deployed Engineer" position popularized by companies like Palantir. This role is highly technical and customer-embedded, focusing on configuring the platform, designing workflows, and managing the production environment directly with the client, moving beyond traditional sales to a hands-on implementation and adoption-driving function. - BrandJet AI, founded in 2025 by Marsad Siddique, aims to reduce fragmentation in the go-to-market tech stack by combining brand intelligence with multi-channel outreach tools (Email, LinkedIn, X, WhatsApp, Instagram) in one platform. The company is currently unfunded and based in Seattle. - The use of AI in go-to-market strategies is a growing trend, with over 70% of businesses reporting improved marketing and sales performance from its use. A survey of tech leaders revealed that 60% expect the competitive landscape to be the top area of AI-driven disruption, and 58% predict the most significant changes will be in selecting channels and routes to market. - For platform engineering leaders, the introduction of AI layers like Artemis into vendor tools highlights a broader industry shift toward AI-powered developer experiences. AI is increasingly used to automate the generation of API documentation, create intelligent code completion, and provide natural language interfaces for complex platform operations. - The Model Context Protocol (MCP) standardizes how AI agents access external tools and data, functioning like a universal connector. This is distinct from a traditional API, as an MCP server provides metadata that helps the AI model understand what tools are available and how to use them, enabling more dynamic and less brittle integrations.
