Agentio Innovation, Technology & Agility

What types of products or services does your engineering team build? What problem are you solving for customers?

Agentio is an AI-powered platform for creator marketing that plans, executes and optimizes creator-led advertising for brands. Built on foundation models and autonomous workflows, Agentio turns a brand’s objectives and context into end-to-end campaign actions — strategy generation, creator and content sourcing and approvals, activation and continuous performance optimization — while learning from results to compound efficiency and outcomes over time.

One example of our AI capabilities is our content review system. Traditionally, when a creator submits a video draft, brands need to manually watch it and verify the creator followed the brief — checking talking points, product placement, messaging and dozens of other requirements. This review process was a major bottleneck, often taking days per video. Our AI-powered content review system uses cutting edge vision models to automatically watch video drafts and evaluate them against the brand’s brief in real-time. This helps brands significantly speed up their review process, transforming what was once the slowest, most manual part of creator sponsorships into an automated, scalable operation.

Tell us about a recent project where your team used AI as a tool. What was it meant to accomplish? How did you use AI to assist?

One of the most exciting recent projects is making data access truly self-serve across the company. As we’ve grown, the volume and complexity of data questions from different teams has grown. Things like campaign performance breakdowns, creator comparisons and revenue attribution used to always go through engineering or data science. That created friction and delays.

To solve that, we prototyped a system that adds MCP functionality directly to our API. That lets reasoning-capable models act as an interface between people and our data. Instead of writing SQL or waiting for someone technical to pull numbers, anyone can now ask questions in plain language, like “Which creator campaigns had the highest view through rate last quarter?” and get back real, structured results right away.

The impact has been huge. Non-technical teammates can move faster and explore data on their own and engineers spend more time building instead of responding to ad-hoc requests. It’s opened new ways to use the powerful analysis capabilities of AI. By pairing our domain-specific data with reasoning models, we’re giving everyone at the company a smarter, faster way to make decisions.

What would that project have looked like if you didn’t have AI as a tool to use? 

If we had built this without AI, it would have looked completely different. The only real option would have been to build many custom dashboards and canned reports for every team. That would mean months of engineering and data work up front and a constant backlog of new requests whenever someone needed a slightly different view. It also would have locked people into whatever questions we had anticipated ahead of time, instead of letting them explore data freely.

With AI in the loop, we didn’t have to solve every edge case ourselves. The reasoning layer handles the complexity and interpretation that would otherwise require custom code or human involvement. That meant we could prototype something valuable in weeks vs quarters and it continues to improve over time as models get more capable.

AI is changing how we think about building software. We’re starting to design systems around collaboration between people and models rather than static interfaces. That lets us move faster, build more flexible tools and give each team at Agentio more leverage without adding headcount. It’s becoming a core part of how we work, not just something we layer on after the fact.