--- title: "AI Agents" url: https://metadata.io/agents description: "Meet the seven Metadata AI agents that plan, build, launch, analyze, and operate enterprise B2B advertising programs." source: metadata.io --- # Seven AI agents that do the work. This is not a chat wrapper around dashboards. Metadata agents create audiences, copy, creative, offers, landing pages, budgets, campaign drafts, reporting views, and optimization recommendations for human review. Across 141 MCP tools, the agents can take 140 different actions in your ad channels, CRM, and data warehouse. ## Full overview of what the agents can do. The team runs the entire paid-media lifecycle, end to end. Flip any stage to meet a customer who proved it. ### Strategy Turn a revenue or pipeline goal into channel mix, account strategy, test plan, and budget groups. ### Audience building Assemble firmographic, technographic, intent, retargeting, and suppression audiences from the 500M graph. ### Creative & offers Generate ad copy, image concepts, video prompts, and offers from your brand kit and proof library. ### Campaign assembly Build campaign objects with naming, budget groups, exclusions, UTMs, and approval states. ### Launch Push approved campaigns live across every channel in one motion. ### Optimization Self-optimize every channel continuously, killing losers and scaling winners toward pipeline. ### Reporting Performance views tied to pipeline, opportunity quality, and CAC, not vanity metrics. ### Operations & MCP Keep integrations, account setup, and governance organized; hand off headless over MCP. ## What the agents produce in the actual product. The app flow shows audience creation, creative generation, campaign drafting, and feedback while the agent team works. ### Watch Max build a technographic audience from one prompt. A real session: companies running Salesforce + Marketo, matched from the live graph — with the team reporting exactly what it could and could not build. ### Prompt-first campaign brief Start in the LLM-first interface and ask the agent team for the outcome, audience, channel mix, or campaign you need. ### Creative generation Generate ad copy, concepts, visual variants, and offer direction from the brand kit and customer proof library. ### Campaign review surface Inspect campaign objects, launch state, budgets, channels, and approvals in the SaaS interface before spend moves. ## Prompt types, tool access, and outputs. Each agent has a role, but the important buyer question is what it can actually do. These prompts map to public MCP tool families and reviewable outputs. ### Mei Plans campaigns, coordinates the team, translates executive outcomes into work orders, and keeps approvals moving. ### Zoe Turns brand DNA, customer proof, offers, and landing-page context into ads for every channel. ### Max Builds firmographic, technographic, intent, retargeting, and suppression audiences from the 500M profile graph. ### Eva Designs the offers and promotions behind each campaign: lead magnets, trials, assessments, incentives, and landing-page hooks matched to audience and funnel stage. ### Ann Assembles campaigns, attaches audiences and assets, sets budgets, and prepares launch plans for review. ### Tom Reads performance, identifies winners, and recommends optimizations tied to pipeline and CAC. ### Raj Manages integrations, budget groups, account setup, guidelines, and MCP handoff for headless execution. ## What the agents own. Decision makers get strategic leverage. Operators get fewer repetitive tasks. Every action remains reviewable. ### Strategy to task plan Turn a business goal into channels, segments, offers, tests, budget groups, and launch dependencies. ### Audience creation Find the accounts and people most likely to care using account data, contact data, intent, technology, and CRM context. ### Creative production Produce copy, image ideas, video prompts, cards, banners, and landing-page recommendations consistent with your brand. ### Campaign assembly Build campaign objects with naming, budgets, exclusions, UTMs, approval states, and launch readiness checks. ### Optimization cadence Identify winners and losers faster than a manual team can check every channel. ### Operational control Keep credentials, integrations, account setup, and budget guardrails organized for review and MCP handoff. ## One brain, every channel. Everything your go-to-market generates flows in. The agents and your strategist operate from one seat. Approved work flows back out to every channel, and performance flows back in. The optimization loop never stops. ## Your data, plus a decade of learned spend. The agents reason over your CRM pipeline and revenue, your marketing-automation leads and journeys, and Metadata proprietary data across 15+ sources with $1B+ in managed spend learned, alongside frontier LLMs and live market signals. ## One seat, every channel, full control. From one interface, approved campaigns flow out to LinkedIn, Meta, Google Ads, TikTok, Reddit, X & Bing, programmatic, and ChatGPT Ads. Performance flows back in and the agents optimize against it continuously, with every action reviewable by a human before launch. ## What the agents replace. No human team or agency can keep up with hundreds of thousands of optimizations a month, and when people leave, their knowledge walks out the door. The agents run 24/7 and remember everything. #### Teams can't keep up Manual execution caps out long before the optimizations do. The agents have run 263K+ experiments and self-optimize every channel without burning out or losing the plot. #### Knowledge that stays The agents kill the experiments that underperform and double down on winners, learning from $1B+ in managed spend. That learning compounds and never leaves with a departing hire. ## Your GTM stack was built for a world that no longer exists. Legacy ABM platforms tell you who to target, then hand the work back to your team. The agents close that gap — live intelligence and autonomous execution in one place. ### Legacy ABM platforms - Lagging intent signals from stale third-party data - Human-driven dashboards across 5+ disconnected tools - Manual campaign setup taking days per channel - Bid and creative optimization by hand - Intelligence-only: tells you who to target, never runs the campaign ### Metadata - Live buyer intelligence unified from CRM, web, and behavioral signals - One interface, one prompt, eight channels - Campaign launch in minutes, not days - AI agents autonomously optimize bids, budgets, and creative - Full execution engine: audiences, campaigns, experiments, attribution ## Metadata vs. legacy ABM. | | Legacy ABM (6sense, Demandbase) | Metadata | |---|---|---| | Signals | Lagging intent data from third parties | Live, unified buyer intelligence from your own data | | Execution | Human-driven dashboards | AI-driven, prompt-based campaign execution | | Optimization | Manual campaign tweaks | Autonomous AI agents optimizing in real time | | Channels | Display ads only (DSP) | 8 channels: LinkedIn, Meta, Google, Bing, X, Reddit, Instagram, LLM | | AI / MCP | No MCP server, no agent execution | 141 MCP tools, 7 autonomous agents, any LLM | | Time to launch | Days to weeks per campaign | Minutes from prompt to live campaign | > “What I really like about the Metadata MCP is that I can now interact and engage and actually get summarized learning of what changes were made and why and how I can learn more about my audience as a result.” ## Frequently asked questions Seven AI specialists - Mei, Zoe, Max, Eva, Ann, Tom, and Raj - that build audiences, creative, offers, campaigns, budgets, and reporting, then optimize live while your team approves every object. Across 141 MCP tools, the agents take real actions across your ad channels, CRM, and data warehouse. The agents prepare and optimize the work, but your team reviews and approves audiences, creative, budgets, and launches before anything goes live. LinkedIn, Google, Meta, X, Microsoft Advertising, Reddit, and ChatGPT Ads.