Artificial Intelligence is changing the way marketing teams make decisions, and Plurio is a concrete example of that happening in practice.
Imagine spending hours buried in dashboards, jumping from platform to platform, just to understand what happened with a campaign yesterday. That was the daily routine for many performance marketing specialists managing hundreds of thousands of dollars in ads every month, and nobody was really happy about it. The problem was never a lack of data — it was too much of it, scattered across tools that didn’t talk to each other, forcing analysts to burn precious energy on operational tasks instead of thinking strategically.
Plurio showed up with a straightforward proposition: turn that slow, fragmented process into something that takes minutes, not hours. The company developed an AI agent built specifically for teams managing $500K or more per month in ad spend, bringing together data analysis, outcome forecasting, and execution of changes into a single interface. It’s no longer about having more tools — it’s about having the right tool that actually understands what’s going on in your campaigns before the lagging numbers even show up. 🚀
The company grew out of Elly Analytics, a cross-platform marketing analytics startup founded in 2023, and has since evolved to focus on automating performance workflows for consumer-facing businesses with longer conversion cycles. To understand how it all came together, we spoke with Seva Ustinov, co-founder and CEO of Plurio, who walked us through everything from the origin of the idea to the results already showing up for real clients.
Who is Seva Ustinov and how Plurio got started
Seva Ustinov brings more than 20 years of experience building businesses in performance marketing, much of that time working alongside Kirill Kasimskiy. Before Plurio, the duo built an agency from scratch to over 100 people, serving clients in sectors like consumer software, fintech, healthtech, and others. Interestingly, that agency is still running today, even without their direct involvement.
In 2023, they founded Elly Analytics, focused on automating cross-platform marketing analysis. The project grew fast, reaching support for over $100 million in annual ad spend, and is now fully integrated into the Plurio ecosystem.
The story of Plurio starts with a problem that’s very familiar to anyone who’s ever worked with performance marketing at scale. According to Ustinov, in consumer products and services, he kept seeing the same scene play out: strong teams spending their days not on growth, but stitching data together manually. It never felt right that the best people in the room were buried in dashboards for hours, waiting on lagging signals just to figure out what was happening. Most days felt like 10% thinking and creating, and 90% clicking from platform to platform.
It was watching this pattern up close that sparked the central question behind the company: what if an artificial intelligence could handle all of that in an integrated way, in real time, and actually act on the data instead of just reporting it? Plurio was born from that frustration — from wanting to give teams their time and attention back and finally make fast decision-making possible.
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From prototype to the real deal
When asked about his favorite memories building the company so far, Ustinov highlighted two standout moments. The first happened while the AI agent was still in its early, unstable phase. He was leaning heavily on Cursor for most tasks and decided to test their own agent on a real problem: generating analysis and cut-off rules for underperforming creatives.
The plan was simple — start with the company’s agent and switch to Cursor when it broke. But he never had to switch. The agent handled the entire task on its own. That was the moment it became clear this wasn’t a prototype anymore — it was a real product.
The second moment came when they announced their funding round. The response blew past expectations. At the same time, the company was running webinars and live sessions, and people started showing up not out of curiosity, but with genuine intent to use the product. It was obvious this wasn’t just launch hype — there was real demand. That shift from pushing a story to watching people pull the product in was probably the strongest emotion of the entire journey.
How Plurio’s AI works in practice
At the core of Plurio is an artificial intelligence agent that operates across channels like a full-fledged performance marketing professional. It was designed to replace the outdated, fragmented workflows of teams managing consumer software and service brands with long conversion cycles.
This isn’t a system that just answers questions or spits out automated reports. Plurio’s agent reads early signals — like shifts in creative performance, audience quality, and channel behavior — and infers what’s going to happen before lagging metrics confirm it. It can tell when a creative is about to hit fatigue, when a winning trend is forming, or when a budget adjustment will improve performance down the line, always delivering attribution-driven decisions.
The tool integrates advertising, CRM, and revenue data into a single source of truth, genuinely understanding what drives growth. Teams interact with Plurio through natural language commands — like asking where revenue will land if 10% of spend is shifted from Meta to TikTok, or requesting to pause Meta ads whenever ROAS drops below 2.0.
The agent evaluates all the factors influencing results — from seasonality and audience quality to funnel efficiency and revenue trends — and explains what changed and why. It projects scenarios, recommends the next move, and executes approved changes. Under the hood, it runs a closed-loop optimization, learning from every outcome and improving its predictions with each cycle. This natural language approach dramatically cuts the learning curve and democratizes access to deep operational insights — something that previously required a specialized data analyst. 📊
The challenge of reinventing product-market fit every three months
One of the most interesting parts of the conversation was when Ustinov talked about a very current market challenge. In his view, product-market fit is no longer a milestone you hit and move on from. Today, it’s a temporary status that lasts about three months.
Large language models evolve, Claude Code evolves, and competitors gain access to the same tools. So you need to find a new product-market fit every three months — inventing, building, shipping, and launching things that deliver real value and a wow factor for users. That intense pace of reinvention has become part of the team’s routine.
Plurio’s technology has also evolved dramatically since day one. The company started as a marketing analytics product focused on aggregating and structuring data across platforms. Today, it’s an AI agent that automates up to 90% of a performance specialist’s workflow — from analysis to decision-making and execution. And it keeps expanding, with the team working to add capabilities like generating creatives directly inside the agent, eliminating the need to switch tools.
Key milestones and the funding round
The company’s trajectory has well-defined milestones year by year. In 2023, Elly Analytics was founded, with the build-out of the data platform, multi-touch attribution for lead generation businesses, first paying customers, and the start of fundraising. In 2024, the customer base grew to over 30 active clients and the first funding round was announced.
By 2025, agentic AI had reached the point where it could finally automate the work clients had been spending hours doing in dashboards every day. The company hired a dedicated AI team, launched a pilot program, and reached over $500 million in total annual ad spend under client management.
In March 2026, Plurio raised an additional $3.5 million from AltaIR Capital, DVC, Yellow Rocks, and strategic angels including Kos Stiskin, CEO of Finom, and Mike Yan, founder of ManyChat. That’s when the rebrand to Plurio happened, bringing total funding to $4.5 million.
Real results and the TripleTen case
One of the most interesting parts of the conversation was when Seva started talking about the results real clients are seeing. Instead of vague metrics, the cases he shared show pretty tangible impact. TripleTen, one of the largest online education companies, sells courses internationally and has a performance team in the United States spending over $1.5 million per month on ads across Meta, Google, YouTube, and TikTok. That’s more than 20 ad sets on Facebook alone, with dozens of creatives inside each one, all generating leads that take weeks to convert into paying students.
Max Epifanov, VP of Performance Marketing at the company, was one of the first users of the AI pilot. With Plurio, campaign analysis dropped from 1 to 1.5 hours down to just 10 to 15 minutes. That adds up to 20 hours saved per month. That savings alone, factoring in team costs, already covers the entire cost of the product before even counting any automation gains.
Full team adoption took two weeks. By March 2026, they already had 11 automated rules running across Search, YouTube, Facebook, and creative fatigue detection. The agent proposes specific actions — like increasing budget, reducing budget, or pausing a creative — and executes them directly in the ad accounts. Trust reached a point where the team moved past just reviewing recommendations and entered the next phase, where the agent doesn’t just replicate what a human would do but actually improves the process itself, writing better rules based on what it has learned.
Among Plurio’s first public results, Ustinov highlighted 100% retention from pilot proposals across global EdTech and FinTech companies, 2x growth in sales and over 20% reduction in CAC as initial pilot outcomes, plus the $500 million in total annual ad spend across clients.
Market opportunity and differentiation
When talking about the market the company is going after, Ustinov brought up some interesting numbers. The global digital advertising market is heading toward $1.3 trillion by 2030. Marketing software and AI tools capture about 4% of that spend, putting the total addressable market at roughly $15 billion. The serviceable market is narrower: U.S.-based companies spending $500K or more per month on paid acquisition, primarily across Google, Meta, and TikTok, representing about $6 billion.
What sets Plurio apart from the competition is its focus on a specific audience that, until now, has been largely overlooked when it comes to real automation: performance teams at consumer-facing companies with long conversion funnels. Subscription apps, fintech, edtech, health, meal kits — businesses where the customer signs up today but revenue doesn’t show up until weeks or months later.
An AI-first company inside and out
One detail that reinforces the company’s philosophy is the fact that it operates as an AI-first organization internally, not just in its product. The entire 30-person team — across marketing, customer success, sales, and engineering — works inside a shared AI workspace. Tools like Confluence were removed, and all knowledge, processes, and client context live in structured, machine-readable formats ready for AI agents to act on. Ustinov even made the template for this model openly available on GitHub.
The company spends about 4% of payroll on AI subscriptions and tokens, and expects that to hit 10% within a year. The return is measurable: team productivity has jumped 2 to 3x. For Ustinov, this matters as much as the product itself, because it shows that being an AI-first company isn’t a buzzword — it’s a specific, reproducible way of working.
What’s next for Plurio
When asked about next steps, Seva was direct in naming two big goals. The first is reaching fully autonomous performance marketing — building a system that handles the complete cycle on its own, from analysis to action to optimization. The second is ambitious: managing $100 billion in ad budgets. That’s the scale the company is building toward.
What becomes clear after understanding Plurio’s trajectory is that the company isn’t just building another marketing automation tool. It’s fundamentally rethinking how high-performance teams operate, placing artificial intelligence at the center of the decision-making process in a practical, accessible way with measurable results. For anyone working with large volumes of paid media who still feels like they spend too much time staring at numbers and not enough acting on them, this is exactly the kind of solution worth keeping on your radar. 💡
