Four product and engineering leaders. 55+ years of combined experience across startups, scale-ups, and enterprises. One shared frustration: B2B ad operations is broken — and nobody was fixing it with the right technology.
Between us, we have spent decades inside B2B companies — from early-stage startups figuring out their first paid channel, to the Microsofts of the world running eight-figure ad budgets across dozens of platforms. We have been the growth lead managing Google Ads at 2 AM because the agency missed the brief. We have been the engineer building dashboards that marketing never uses. We have been the product leader watching pipeline meetings where nobody can explain why cost-per-acquisition doubled last quarter.
The pattern was always the same. Marketing generates MQLs — marketing qualified leads — through paid campaigns. Those MQLs enter a CRM. Sales qualifies some of them into SQLs — sales qualified leads. Product tracks a separate set of PQLs — product qualified leads — based on in-app behavior. And somewhere between these three acronyms, money disappears.
The Google Ads campaign that generated 200 MQLs last month? Only 12 became SQLs. The LinkedIn campaign targeting VP-level decision makers? Half the leads were individual contributors who clicked out of curiosity. The Meta retargeting campaign running for 6 weeks? Nobody checked if the creative was still converting — it was not. CPA had tripled.
We watched this happen at company after company. Not because the people were bad — the marketers were smart, the sales teams were sharp, the product teams were data-driven. The problem was structural. Ad operations in B2B requires connecting data from CRM systems, analytics platforms, and ad networks — in real time — and making optimization decisions every few hours based on statistical evidence. No human team, no matter how talented, can do this consistently at the speed the platforms demand.
The agencies were not solving it. They charge $10,000 to $30,000 per month, run the same playbook for every client, and optimize once a week — if you are lucky. The freelancers were not solving it. They move too slowly, lack the data infrastructure, and cannot monitor campaigns around the clock. The in-house teams were not solving it. They are stretched across 12 tools, context-switching between creative briefs and bid management, and spending more time in spreadsheets than in strategy.
Every B2B company we worked with was essentially running their ad operations blind. They had data in HubSpot, data in Google Analytics, data in Mixpanel, data in their ad platforms — and no system connecting it all into actionable intelligence. The result? Campaigns built on assumptions instead of evidence. Audiences defined by job titles and guesswork instead of actual customer behavior. Optimization that happens weekly instead of every 6 hours. Creative that runs until someone remembers to check it — usually after the CTR has already collapsed.
We kept asking ourselves the same question: what if there was an AI agent that could read all your business data, discover who your best customers actually are, build campaigns informed by that data, deploy them directly to Google Ads, LinkedIn Ads, and Meta — and then optimize every 6 hours while you sleep?
Not a dashboard. Not a reporting tool. Not another SaaS platform with 47 tabs and a 3-month onboarding. An autonomous agent. One that thinks, plans, and acts — on your real data, across your real ad accounts, with your approval on every decision that matters.
We are four founders who have each built, scaled, and led product, growth, and marketing teams — from first customer to millions in revenue. Every one of us has been a founder before. We have lived through the zero-to-one phase multiple times, felt the pressure of making every marketing dollar count when runway is measured in months, and experienced firsthand what happens when the gap between your customer data and your ad execution costs you the quarter.
One of us spent 25 years at the intersection of product leadership and go-to-market strategy — from leading product and marketing teams at one of the world's largest technology companies to founding and scaling startups where product-led growth was the only viable path. That meant owning the entire customer journey: defining the positioning, building the product, setting up the demand generation engine, measuring what converts and what does not, and making the hard calls about where to invest the next marketing dollar. That product-marketing discipline — building for the customer, not for the roadmap — is embedded in every layer of YEpsilon.
Another spent a decade as a growth and marketing leader in B2B SaaS — building and managing growth teams, owning pipeline and revenue targets, running paid acquisition across Google, LinkedIn, Meta, and programmatic channels, and scaling companies from seed to Series B. That meant hiring marketers, setting up the attribution stack, building the MQL-to-SQL handoff process, fighting with Google Ads at midnight because a competitor launched a campaign, writing the 14th version of an RSA headline, and sitting in pipeline meetings explaining why CPA doubled when nobody was watching the campaigns. That lived frustration is exactly why YEpsilon's campaign creation feels like talking to a growth teammate, not configuring another SaaS tool.
The other two founders bring deep product management and marketing operations expertise — each having founded their own startups, built product and marketing teams from the ground up, and shipped products used by thousands of businesses. One led product for a platform that connected to every major CRM — HubSpot, Salesforce, Pipedrive — and learned that the best marketing technology is invisible: it connects data, surfaces insights, and lets the marketing team focus on strategy instead of spreadsheets. The other built demand generation infrastructure and analytics integrations across GA4, Mixpanel, Amplitude, and Segment — understanding that the gap between collecting marketing data and acting on it is where most B2B companies lose their competitive edge.
What connects us is not just the ability to build this product — it is the founder's instinct for knowing what product, growth, and marketing teams actually need versus what vendors try to sell them. Every one of us has sat on the buyer side. Every one of us has managed ad budgets under pressure. Every one of us has built marketing funnels, tracked MQLs through to closed-won, and agonized over attribution models that never quite tell the full story. We built YEpsilon to be the product we wished existed at every company we have ever led — one that turns your actual customer data into campaigns that convert, and then optimizes them relentlessly so your marketing team can focus on the work that humans do best: strategy, creativity, and building relationships.
The B2B advertising market is worth over $30 billion annually, and growing. Yet the tools available to B2B marketers were designed for a different era — one where campaign setup was a one-time event, optimization was a weekly check-in, and audience targeting was based on demographic assumptions rather than real customer data.
We believe the future of B2B ad operations is autonomous. Not "automated" in the sense of rule-based triggers and if-then workflows. Truly autonomous — where an AI agent reads your first-party data, discovers patterns in who converts and why, builds campaigns informed by those patterns, deploys them to the platforms that matter, and optimizes every 6 hours based on statistical evidence. Where every decision is logged, every action is explainable, and every high-impact change goes through your approval before it executes.
YEpsilon is that agent. We connect to your CRM (HubSpot, Salesforce, Pipedrive) and your analytics tools (Google Analytics 4, Mixpanel, Amplitude, Segment). We run every contact through an 8-stage intelligence pipeline that resolves identities, classifies attributes, scores signals, and generates audience personas — not from industry benchmarks, but from your actual customer data. We then use those personas to create campaigns on Google Ads, LinkedIn Ads, and Meta — with keywords researched via the Keyword Planner API, RSA ads written to match search intent, and targeting configured to reach the people who look like your best existing customers.
Once campaigns are live, the ROAS optimization engine takes over. Every 6 hours, it runs a 14-stage pipeline: anomaly detection, data quality checks, performance snapshots, kill logic for underperformers, scale logic for winners, budget shift logic across platforms, bid adjustments, creative rotation checks, A/B test evaluation, persona weight updates, drift detection, and approval routing. Every action is recorded as an immutable audit event. Low-risk moves auto-execute. High-impact decisions are flagged for your review.
At Day 14, the Creative Studio runs statistically valid A/B tests using z-test for proportions. When a winner is declared, losers are paused and new challengers deploy. At Day 30, creative fatigue detection triggers an LLM-powered refresh — generating new copy variants based on the messaging patterns that actually converted for each persona.
This is not a vision document. This is what YEpsilon does today, in production, on real ad accounts. We built every line of code ourselves. We designed every API integration. We tuned every optimization threshold. And we work directly with every early customer — because at this stage, every engagement teaches us something new about how to make the agent smarter.
Every optimization action is logged, explained, and auditable. You see exactly what the AI did, why it did it, and what changed. We built a full immutable audit log — not because regulators asked, but because we believe you should never trust a system you cannot inspect. No hidden algorithms, no unexplainable results, no "the AI decided" without a reason attached.
We encrypt everything at rest using AES-256-GCM and in transit using TLS 1.3. We never use customer data for model training. Your personas, your targeting configurations, your campaign performance — that is your intellectual property. You can export or delete your data at any time. We built YEpsilon to leverage your data for your benefit, not ours.
No annual contracts. No lock-in. We start every engagement with a pilot — typically one month — because we believe you should see measurable results before making any commitment. If we are not delivering, you should leave. That constraint forces us to ship value fast, optimize relentlessly, and treat every customer engagement as if our existence depends on it. Because it does.
When you book a conversation with YEpsilon, you speak with the people who built the product. Not a sales development representative reading from a script. Not an account executive who has never touched Google Ads. The founding team directly. We believe that early-stage companies earn trust through competence, not through sales motions. Every engagement is a partnership where we learn as much as you do.
Whether you are a B2B team spending $5k or $500k per month on ads, we would love to show you what YEpsilon can do with your data. No pitch deck. No demo environment. Your real accounts, your real data, your real results.