We built this because the problem is real.

Most AI consulting firms were built by strategists. Telos was built by a builder.

A decade of building AI products that actually ship.

Rodrigo Rivera started his career as a data scientist at a consulting firm, then founded Realize — an ML-based demand planning startup in Guatemala that was eventually acquired. After the exit, he joined a company as a forward-deployed engineer, embedding directly with client teams to build AI products that solved real business problems.

Most notably: an ML demand planning model for one of the world's largest record labels that reduced unsold merchandise by ~$10M per year by predicting how similar artists' sales behavior would transfer to new releases.

For the past three-plus years, Rodrigo has managed AI products at GoTo — a complex SaaS company with 20+ products and multiple commerce systems. He built Revy AI, one of GoTo's first Claude-based internal tools, and led Simplified Bookings, a company-wide financial reporting unification used by Sales, Finance, Revenue, and Operations teams.

Through all of it, the same pattern appeared: AI projects succeed or fail not because of the technology — but because of what happens (or doesn't happen) between the demo and the business outcome. The product management layer that most AI projects are missing.

Telos Intelligence is built to supply that layer — for mid-market SaaS and CPG companies that are ready to stop experimenting and start generating real value from AI.

Built in the field. Tested under real conditions.

The Telos methodology wasn't designed in a consulting firm or a business school. It was built — and stress-tested — inside one of the most complex AI deployment environments in enterprise SaaS: a $1B+ revenue company with 20+ products, multiple commerce systems, and stakeholders across every business unit.

That's where the hard questions got answered. Not "can we build this?" but "will people actually use it?" Not "does the model work?" but "can the CFO measure it?" Not "is it impressive?" but "is it still running six months later?"

Every phase of the Telos framework — intake, prioritization, UAT, adoption, ROI measurement — comes directly from solving those questions at scale. With real teams, real data, and real consequences if the answer was wrong.

"The gap between AI potential and AI execution is a product management problem. Most companies don't have a PM who specializes in AI adoption. We built Telos to be that partner."

— Rodrigo Rivera, Founder

Four words that define how we work.

Purposeful

We don't build AI for the sake of AI. Every initiative has a defined problem and a dollar outcome. If we can't articulate the business case before we start, we don't start.

Honest

If AI isn't the right solution for your problem, we'll tell you. Even if that means a smaller engagement. Our reputation is worth more than a short-term contract.

Durable

We build for your team to own. Our exit is planned from day one. A great engagement ends with a client who doesn't need us anymore — and refers us to someone who does.

Direct

No padding, no jargon, no consulting theater. We say what we mean. Short sentences. Clear outcomes. Proposals you can read in under 10 minutes.

Ready to work with a team that has done this before?

Every engagement starts with a 30-minute discovery call. No pitch deck. Just a direct conversation about your highest-value AI opportunity.

Or email us at hello@thinktelos.ai