Metadata exists because intelligence platforms tell marketers where demand might be, agencies add manual capacity, and ad channels optimize for their own metrics. Enterprise teams need an execution layer that can build, launch, learn, and prove revenue impact.
A marketer should be able to ask for an outcome, inspect the audience and creative logic, review budget controls, and know exactly what changed after launch.
Metadata is the execution layer for B2B paid media, where people, technology, and data work together so humans lead and AI executes. Four values decide how we build and how we run campaigns.
We have a bias to shipping. Strategy only matters once it is live, so we turn a brief into running campaigns in hours, not quarters. The execution layer collapses the distance between an idea and a launched audience, offer, and budget, then learns from real spend instead of waiting for the perfect plan. Across a decade and 263K+ experiments, the teams that win are the ones that move first, measure fast, and let momentum compound.
Owners are trusted to make decisions. We run small teams with real ownership over their outcomes, their budgets, and the work in front of them, because the people closest to the customer make the best calls. That same principle runs through the product: humans lead with strategy, judgment, and approvals while keeping full control over what ships. Autonomy is what lets us manage $1B+ in media without slowing down to ask permission for every step.
Every decision is measured against one question: does it move customer pipeline and revenue. We do not optimize for channel-native vanity metrics or internal convenience. We optimize for sourced pipeline, CAC, and learning velocity, the numbers 200+ customers are actually accountable for. When a tradeoff is unclear, the customer outcome breaks the tie, and the proof lives in named customer stories and public reviews rather than category claims.
AI agents do the repetitive execution, building audiences, drafting creative, structuring budgets, running experiments, and assembling reporting, so people are free to focus on judgment and strategy. We default to letting AI do the work and reserve human attention for the decisions that need it: brand, approvals, and where the agents should stop. Backed by 7 patents, this is how a small, autonomous team operates at the scale of a much larger one.
The team building and running the execution layer for B2B paid media, across product, engineering, data, and go-to-market.
The company story should make it clear that Metadata is an execution layer for paid media, not a generic AI wrapper or another intent dashboard.
Enterprise buyers should see where humans review budgets, campaign objects, brand guidance, credentials, launch timing, and optimization changes.
Named customer stories, public G2 proof, and product visuals should carry the credibility burden instead of unsupported category claims.
The buyer should understand why work starts in the LLM-first app, gets reviewed in the SaaS platform, and can be extended through MCP.
Marketing, RevOps, finance, security, and technical evaluators should each find a path to the questions they need answered.
"Metadata.io is rated 4.6/5 on G2 across 299 public reviews and is listed across ABM, account intelligence, advertising, and analytics categories."Public G2 proof
Metadata is an AI agency for enterprise paid media - end-to-end demand creation from paid media, run by AI agents your team directs and approves.
Enterprise B2B demand and revenue teams expected to create demand from paid media, not just capture it.
ABM platforms are built to capture existing demand. Metadata builds audiences, creative, offers, and campaigns across every channel and optimizes toward pipeline - creating demand, not just scoring it.
Yes. Your campaign data, performance history, and AI learnings remain yours. Metadata stores these within your account, so if you return, you can pick up where you left off.