Surface Labs

Surface Labs builds a marketing system that connects buyer signals, campaign execution, and revenue outcomes and then learns from what works. It aims to improve campaigns by feeding outcomes back into the system so future efforts are more effective. The approach centers on separating human and agent work while maintaining clear controls over autonomous actions. The team emphasizes starting from first principles and staying close to users to support marketing with AI.

Surface Labs describes its platform as a system that learns from revenue context, integrates buyer signals and CRM outcomes, and uses autonomous agents to research, create, and execute campaigns across channels. The product emphasizes governance and escalating trust as agents handle more tasks. The overall goal is to turn revenue context into better campaigns through repeated cycles of measurement and improvement.

It highlights features such as traffic intelligence, lead enrichment, and AI-driven campaign planning and execution, while emphasizing visibility into AI search and attribution across engines. The company frames the system as adaptable for scale with governance and customization.

The platform advertises plans that include Basic, Agentic Marketing Operations, and Marketing Superintelligence, with various inclusions and pricing. It mentions a shared workspace, unlimited team seats, unlimited agents, and agent actions, along with enterprise features such as SLA, SSO, and audit logs for higher tiers. The docs and pricing pages reference integrations, governance, and startup pricing options.

Use cases

• Turn revenue context into better campaigns