Media teams are under constant pressure to prove campaign performance, respond to changing results & deliver client insights faster. But when hours go into pulling reports, investigating issues & making routine adjustments, there's less time for strategic work.
Decision Foundry helps media agencies put agentic AI to work across campaign workflows, turning scattered data and repetitive tasks into more time for better decisions.
“Our team spends hours every Monday consolidating campaign data and preparing client reports.”
“We identified the budget overrun only after the campaign had ended.”
“Our optimization decisions rely too heavily on the experience of a few senior traders.”
“Clients expect actionable insights, but our analysts are tied up preparing presentations.”
“Every new client adds more platforms, reporting requirements, and manual work to our team's workload.”
From campaign delivery to client reporting, these agents help media agencies manage complex workflows, surface actionable insights, and scale operations across client accounts.
Turn campaign data into clear client insights with MemoSight Insights. Consolidate performance metrics, identify trends, and create actionable reports.
Use MIX-IQ to analyze media performance, understand channel contributions, and identify opportunities to improve campaign effectiveness and budget allocation.
Track media spend against planned budgets with the Campaign Spend Optimizer. Identify pacing issues, flag potential overspending, and address delivery gaps.
Use CampTag to maintain consistent campaign naming across platforms. Identify tagging issues and standardize campaign labels for more reliable reporting.
Turn successful projects into compelling case studies with RapidCase. Organize project details and create structured drafts with less manual effort.
Support agency sales teams with PitchPal. Access relevant solution and pricing insights to prepare client proposals and strengthen pitch conversations.
Use Quikstack to modernize agency technology infrastructure, identify improvement opportunities, and build scalable cloud environments that support AI adoption.
Our AI Maturity Assessment for Marketing helps you assess your current capabilities, uncover opportunities to streamline campaign operations and reporting, and identify the highest-value AI use cases to prioritize.
We work with media holding companies, independent and performance agencies, specialist agencies in regulated sectors such as healthcare and financial services, and in-house media teams at brands. For holdcos, agents run on a shared foundation with strict data isolation between agencies and clients.
We shadow your reporting, trading, and pacing routines to find where hours go and which decisions follow clear rules.
We check connectors, taxonomy, and KPI definitions, and tell you honestly whether your data is agent-ready.
Together we set spend limits, approval thresholds, client-specific rules, and escalation paths before any agent can act.
One focused agent runs alongside your team on live accounts, typically within 6 to 10 weeks, so you can compare its output with your current process.
We extend the agent across clients and platforms, connect it to your existing tools, and train the people who will supervise it.
Agent tracing, cost tracking, and drift detection keep performance visible, with regular reviews as your client mix changes.
Our team brings together Salesforce Marketing Champions, Tableau Zen Masters, and Marketing Cloud Intelligence (Datorama) specialists to address the data and operational challenges media agencies face.
We build on proven Decision Foundry products, including MemoSight, CampTag, MIX-IQ, and Campaign Spend Optimizer, designed to address real marketing data, reporting, and campaign management needs.
We work with Salesforce Agentforce, Azure AI Foundry, Anthropic Claude, OpenAI, and open-source frameworks, with expertise across Databricks and Snowflake. This lets us align the technology stack with your data, workflows, and business needs.
Our approach includes guardrails, audit trails, and escalation paths. Agents operate within defined permissions, with budget-related actions restricted to limits approved by your team.
We bring two decades of data engineering experience to building on clean, governed data. Our approach supports role-based access, client-level data isolation, and GDPR-related requirements, with SOC 2 compliance where applicable.
From campaign monitoring to client reporting, Decision Foundry helps you identify the right AI opportunities and turn them into practical workflows that scale with your agency.
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Only within the permissions you define. You decide which actions agents can execute automatically, which require human approval, and what spending limits they must follow. This helps your team automate routine tasks while retaining control.
Media agencies can evaluate ROI by tracking improvements in reporting efficiency, time saved, campaign response times, budget pacing, and team productivity. Read our article on measuring the ROI of agentic AI to explore how to assess business value.
AI agents can be integrated with advertising platforms such as Google Ads, Meta, and LinkedIn, as well as analytics tools, CRM systems, and data warehouses. The available integrations depend on your technology stack and data access requirements.
No. You can build agentic AI workflows around your existing technology stack, including Marketing Cloud Intelligence, Salesforce, Snowflake, or Databricks, depending on your requirements. Decision Foundry can assess your current infrastructure and recommend a practical starting point without requiring you to adopt an entirely new platform.
Client data can be protected through client-level data isolation, role-based access controls, and clearly defined agent permissions. These controls help ensure agents access only the information needed for their assigned tasks.
A focused proof of value typically takes 6 to 10 weeks, depending on the workflow, data readiness, and integration requirements. By testing with live accounts and agreed success metrics, your team can evaluate outcomes such as reporting time saved, improved budget pacing, and reduced manual effort before expanding to additional workflows or clients.
