Unify Data, Deploy AI Agents,
and Scale Accounts

NinjaCat is an AI agent platform built for multi-account marketing teams. It unifies marketing data from 150+ sources, deploys customizable AI agents to automate reporting, pacing, anomaly detection, and optimization, and delivers pixel-perfect client reports, all in one platform. It is used by agencies, portfolio companies, and multi-location brands to scale operations without growing headcount.

NinjaCat unifies cross-channel marketing data, automates reporting and analytics workflows, and deploys AI agents that handle tasks like budget pacing, anomaly alerts, QA, and performance optimization across hundreds of accounts simultaneously. It replaces manual data pulling, spreadsheet reconciliation, and repetitive reporting tasks so marketing teams can focus on strategy and client growth.

NinjaCat is built for multi-account marketing teams: specifically digital agencies managing hundreds of client accounts, portfolio companies overseeing dozens of brands, and multi-location brands with thousands of locations. It is designed for marketing engineers, analysts, operations leads, and agency executives who need to scale without adding headcount.

NinjaCat AI Agents are customizable, automated workers that run continuously across all your accounts. They can detect anomalies, flag pacing issues, audit ad copy for brand compliance, prepare client call briefs, recommend budget changes, compile performance reports, and more, all without manual intervention. Each agent is tuned to the context of the specific account it monitors, and human teams approve or deny recommended actions before they execute.

NinjaCat supports 150+ pre-built data connectors including Google Ads, Meta, Microsoft Ads, LinkedIn, TikTok, Pinterest, YouTube, Amazon Ads, Google Analytics, DV360, Snowflake, The Trade Desk, Shopify, Google Cloud, Mailchimp, and many more. New integrations are added regularly to keep pace with the modern marketing stack.

Unlike traditional BI tools that require analysts to build queries and pull data manually, NinjaCat is an active AI agent platform: it does not just visualize data, it acts on it. NinjaCat's AI agents proactively surface issues, recommend optimizations, automate reporting, and let teams approve actions rather than assemble them. It is purpose-built for the workflows of multi-account marketing, not general-purpose analytics.

Yes. NinjaCat automates the full reporting lifecycle, from data ingestion and normalization to report assembly and delivery. Customers have reported up to a 90% reduction in manual data analysis time. Reports are generated automatically on schedule, branded to each client, and delivered without analyst intervention.

Yes. NinjaCat supports fully branded, pixel-perfect client reports. Agencies can customize reports to match each client's branding, ensuring every deliverable looks hand-crafted, even when generated automatically at scale across hundreds of accounts.

NinjaCat is designed for rapid deployment: teams can deploy AI agents across all accounts in days, not months. The platform includes 340+ pre-built starter agents across 15 categories that can be configured and activated without engineering resources.

Yes. NinjaCat is enterprise-grade and trusted by major marketing organizations including VML, Wpromote, Cox Media Group, MiQ, Amsive, Seer Interactive, Gannett, and Anthropologie. It is built to handle hundreds of accounts and thousands of data streams with governed, normalized data and enterprise security standards.

NinjaCat AgentOS is the core platform layer that powers the entire NinjaCat ecosystem. It includes the Data Cloud (unified, governed marketing data), the Accounts layer (account-level context that tunes every AI agent), AI Agents (automated workers deployed per account), Data Apps (natural-language analytics powered by your data), and Reporting (automated, client-ready report delivery). Together they form a complete operating system for multi-account marketing.

No. NinjaCat is designed for marketers, not engineers. Its Data Apps feature lets users ask questions about their data in plain language with no SQL required. Agents are configured through a visual interface, and reports are built with drag-and-drop tools. Technical users can go deeper, but the platform is fully accessible to non-technical marketing professionals.