Clarica Labs partners with product leaders taking AI-forward SaaS from launch to scale. Product leadership, product data science, and monetization strategy — from a single operator.
Every AI-forward SaaS moving from launch to scale leans on three disciplines: product leadership, product analytics, and pricing strategy. Whether you're a post-traction founder scaling the first product or a growth-stage team launching a new AI line, those are the functions that shape what gets built, what gets measured, and how it gets paid for.
Clarica Labs can flex across all three — or plug in where it's needed most. Own the full stack as the embedded product operator, pair with an existing product leader on analytics and pricing, or drop in on a single discipline when that's the sharp edge. One operator, scoped to the shape of the work.
Three disciplines, one operator. Each service anchored in strategic thesis before tactical work.
Embedded product leadership for AI-forward SaaS. Shaping a product thesis for where AI creates lasting customer value in your domain.
Translating that thesis to production: agent design, evaluation loops, prototyping with engineering, and the AI-specific tradeoffs that determine what ships.
Product data science for AI-forward SaaS. Owning the voice of product data in the business — what's healthy, what's at risk, and what to do about it.
Translating that thesis to practice: metric strategy, exploratory analysis that surfaces the questions the dashboard can't ask, and self-service capabilities that put product data into the hands of everyone making decisions — not just the data team.
Monetization strategy for AI-forward SaaS. Pricing as a product — architected for iteration, grounded in willingness-to-pay research, and designed for the customer each model actually attracts.
Translating that thesis to practice: value metrics, packaging, and the research and experimentation that turn pricing from intuition into evidence — including outcome-based vs. usage-based tradeoffs, where the pricing model selects your customer base as much as your marketing does.
Clarica Labs is founded and operated by Jeremy Rodriguez — a product and strategy operator with 15+ years of experience and over a decade embedded inside product and R&D organizations, building teams and systems from the ground up.
His career spans product strategy and data science, growth and pricing, across B2B SaaS, digital marketplaces, and early-stage startups.
AI-native product management, in the work of agent design, evaluation loops, and the tradeoffs that take natural language products from prototype to production — after a decade inside data-driven product organizations.
Bringing data into product decisions. Defining what to measure, instrumenting tracking, designing experiments, analyzing feature adoption, and translating usage data into roadmap recommendations — at the intersection of product and engineering, which required a working understanding of the underlying technical systems.
Pricing as a product. Built and owned a pricing analytics and strategy function at a public SaaS company, where pricing was treated as a product: research, experimentation, business cases, and implementation of a company-wide pricing overhaul across product, engineering, finance, and go-to-market teams.
Full-funnel perspective. A perspective rare in product roles — beginning in market research, moving into growth and user acquisition, then product data science and pricing. One operator thinking about how users are acquired, activated, and monetized, rather than any single stage.
Selective engagements, 2026. If you're taking an AI-forward product from launch to scale, there's likely a conversation worth having.