Onmo – AI Campaign Management / Ads Automation

Onmo: Building an AI-Powered Marketing Performance Platform at Builder.ai

Onmo was one of the most forward-thinking and technically challenging projects I worked on during my time at Builder.ai. Over a six-month period, I served as the Senior Product Manager leading the product vision, the end-to-end ad-management experience, and the seamless integration of AI into every layer of the marketing performance engine.

The goal of Onmo was bold: create a centralized AI platform that could manage, optimize, and scale marketing campaigns across multiple channels: Meta, Google, TikTok, Snapchat, and more, all from one intelligent dashboard. Agencies and performance teams were drowning in operational complexity, repetitive daily tasks, inconsistent insights, and the mental overhead of jumping between channels. Onmo aimed to eliminate that chaos through automation, intelligence, and beautifully simplified workflows.

But when I joined the project, nothing was working the way it needed to. The experience was fragmented, the campaign creation flow was incomplete, and the product lacked the intelligence required to deliver value. Over the next six months, I rebuilt the entire experience from the ground up.

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Re-Architecting the Core Experience

My first challenge was to rewrite the entire Ad Management Journey based on a technical brief and a complex recorded meeting that outlined dozens of requirements, edge cases, and unknowns. Instead of simply refining the existing version, I redesigned the entire system how agents create campaigns, how budgets are allocated, how audiences are selected, how creatives are structured, and how results are interpreted.

I crafted a clean, logic-driven campaign wizard that worked across all channels while accounting for channel-specific requirements. The system could create a Meta campaign, a Google Ads search campaign, or a TikTok video campaign while maintaining a consistent structure for the end user. This clarity was essential, because the entire value of Onmo depended on reducing complexity, not adding to it.

As I refined the experience, I defined the internal data architecture as well: accounts, workspaces, campaign groups, campaigns, ad sets, creatives, audiences, budgets, and optimization events. Everything needed to connect smoothly so the AI engine could read data, analyze performance, and generate insights in real time.

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Seamlessly Integrating AI Into the Marketing Workflow

The most transformative part of the project — and my biggest achievement — was designing how AI integrates into the heart of marketing performance.

I shaped the platform so AI wasn’t a feature; it was the engine. It supported performance teams in every stage:

• During campaign creation, it recommended budgets, assets, and audience combinations.

• During performance monitoring, it analyzed results, predicted outcomes, highlighted anomalies, and suggested optimizations.

• During daily operations, it automated repetitive work, reallocated budgets, paused underperforming assets, and pushed spend toward high-performing channels.

This required me to design complex intelligence layers: alert systems, optimization triggers, budget rerouting logic, and predictive performance models, all in a way that felt human, transparent, and trustworthy.

Onmo became more than a dashboard. It became a performance co-pilot, built to assist marketing teams the same way AI assists product teams today.

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Building for Two User Roles: Agent and Admin

The platform served two distinct personas:

Agents, who managed campaigns daily, and Admins, who oversaw performance, permissions, multi-client structures, and reporting.

I built the experience so agents could focus on execution and optimization, while admins could see the bigger picture: KPIs, profitability, budgets, client performance, and the health of every workspace inside Onmo. This dual-role structure became the backbone of the product’s usability and scalability.

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From Strategy to Execution: Leading the Product to MVP

Throughout the six months, I led the entire product direction:

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• I translated abstract business goals into clear requirements.

• I built the technical flows the engineering team needed.

• I defined every scenario of campaign creation, performance monitoring, and optimization.

• I worked closely with design to refine dashboards, user journeys, and the AI interaction model.

• I gave the engineering team the clarity and structure they needed to move quickly.

By the time the MVP was ready, Onmo was no longer just an idea it was a fully structured, AI-powered platform with a complete marketing intelligence engine, a unified multi-channel experience, and a scalable foundation that could support future automation and advanced performance logic.

A Strong Product with an Unexpected Ending

Unfortunately, just as the MVP reached a stable, ready-to-move-forward state, Builder.ai collapsed, causing the project to halt before moving into production rollout. The platform was strong, the value was clear, and the engineering direction was ready but the organization powering it could no longer continue.

Despite the unexpected ending, Onmo remains one of the most technically rich and visionary products I’ve delivered: a true example of how AI can reshape agency workflows by removing friction, lowering operational cost, and making performance management more predictive, intelligent, and scalable.

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