Industry Solutions

How do you build AI agents for advertising?

Advertising agents assemble campaign briefs, check creative against brand rules, summarise research and monitor performance with function calling and retrieval. The workable pattern keeps a human approval gate before anything publishes, enforces brand and legal checks as tools, and logs every step. Plugsky supplies the compatible API, 30+ models and embeddings behind it.

Key facts

Agent stackChat completions, function calling and embeddings are live
Use casesBrief assembly, creative QA, research digests, performance summaries
Brand rulesExpose style, legal and claims checks as tools the agent must call
ToolsAny internal API can be exposed via function calling or MCP
Models30+ models; small aliases for checks, stronger ones for synthesis
ApprovalKeep a human gate before anything publishes or spends budget
Pricing modelFlat monthly self-serve plans with unlimited fair-use usage
RoadmapImage, audio and batch endpoints are coming soon

TL;DR

  • Automate the brief, the checks and the digest, not the publish button.
  • Encode brand and legal rules as tools the agent cannot skip.
  • Ground research and performance claims in retrieved sources.
  • Keep humans accountable for spend and final creative approval.
  • Measure cycle time and rework, not the number of drafts generated.

How it works, step by step

  1. Choose one workflow such as creative QA or the weekly research digest.
  2. Write the brand, legal and claims rules as discrete check functions the agent must call.
  3. Ground research in a retrieval index over approved sources and your own past campaigns.
  4. Generate drafts with citations and attach the check results to each one.
  5. Route to a human approver for sign-off before publishing or committing budget.
  6. Log tool calls and approvals, then measure review time and rework rate.
1Choose one workflowsuch as creative QAor the weekly2Write the brand,legal and claimsrules as discrete3Ground research ina retrieval indexover approved4Generate draftswith citations andattach the check5Route to a humanapprover forsign-off before6Log tool calls andapprovals, thenmeasure review time

Try it yourself

Open the agent workflow designer →

Advertising workflows an agent can own

Agents do best where steps repeat and evidence is checkable:

  • Brief assembly: combine the client request, audience notes, past performance and constraints into a structured brief.
  • Creative QA: check copy against tone, legal and claims rules and flag every violation with the rule cited.
  • Research digests: summarise market and competitor material from an approved source set.
  • Performance summaries: turn campaign numbers into a plain-language recap with caveats.

Anything public or budgeted still needs a named human owner.

Architecture and brand-safe tooling

Model the workflow as a short, bounded loop:

  • Planner: turns a request into steps and required checks.
  • Retriever: pulls approved sources, style guides and past campaign results.
  • Tools: brand check, legal check, claims check and asset lookup, called explicitly.
  • Composer: drafts with citations to the retrieved material.
  • Approver: a human reviews the draft and the attached check results.

Make the checks mandatory tool calls rather than instructions; instructions can be ignored, a required tool call can be enforced in code.

Guardrails, spend and disclosure

Never let an agent commit media spend or publish without approval. Cap any budget action behind a human confirmation step and a hard limit. Keep an audit log that records the prompt, sources, check results, model version and approver for every asset, so you can reconstruct why something was released. Separate environments and keys for each client or brand where confidentiality demands it. Where a client or market requires local processing, run the same compatible workload inside a VPC, on-prem or air-gapped deployment.

Evaluating an advertising agent

Prototype on plugsky-micro or plugsky-lite against a small set of past briefs and creatives, then use the 14-day full-access trial to test a frontier model on synthesis-heavy work. Track brief cycle time, number of human edits, rule violations caught and false positives, and the share of claims with a valid source. Self-serve plans are flat monthly with fair-use usage, so high-volume testing does not create per-token spikes. Keep prompts and rule sets versioned, since brand guidance changes often.

Honest comparison

CapabilityPlugskyTypical agent frameworkBuilding in-house
Tool callingLive function calling over internal APIs and MCP toolsFramework-specific adaptersYou build and maintain
Retrievalplugsky-embed plus RAG over brand and research sourcesAdd-on or external storeYou integrate everything
Approval gateYou enforce publish and spend gates in codeVariesYou design controls
DeploymentCloud, VPC, on-prem and air-gappedUsually cloud-onlyYou operate GPUs and serving
PricingFlat monthly self-serve, fair-use usageVaries by framework and modelGPU plus operations cost

Frequently asked questions

Can the agent publish ads directly?

No. Keep a human approval gate for anything public or budgeted; the agent should prepare the asset, evidence and check results for sign-off.

Which endpoints does an advertising agent need?

Chat completions, function calling, JSON mode and embeddings are live. Image, audio and batch endpoints are coming soon.

How do we enforce brand rules?

Encode them as tools that must be called before a draft is accepted, and fail the run when a check is missing or returns a violation.

Is there a free plan?

Yes. The free plan includes plugsky-micro and plugsky-lite with no credit card, which is enough to prototype brief assembly and creative QA.

How does pricing work?

Self-serve plans are flat monthly with unlimited fair-use usage. See the live pricing page for current plans and enterprise options.

Can we isolate client data?

Yes. Use scoped keys and separate projects or deployments per client, including VPC or on-prem where confidentiality demands it.

How should we measure it?

Track cycle time, number of human edits, violations caught, false positives and audit completeness rather than drafts generated.