Applied AI strategy + execution
I work with founders, operators, and product teams to build practical AI systems across LLMs, forecasting, pricing, recommendation, and automation. The focus is always the same: clear business outcomes, clean implementation, and production reliability.
Why teams bring me in
I am an AI and machine learning consultant with a hands-on background in forecasting, pricing, recommendation systems, and production data products. I have spent the last decade building systems that have to work in messy, high-stakes environments where reliability matters more than novelty.
Today I help teams navigate the shift from classic ML to modern AI. That can mean shaping an AI roadmap, designing a grounded LLM workflow, standing up evaluation and observability, improving an existing model stack, or helping a founding team turn an idea into a focused, shippable product.
My style is pragmatic, technical, and business-aware. I like working closely with decision-makers, shipping quickly, and building systems that are understandable enough to maintain once the first launch excitement wears off.
Scaled network forecasting
Built forecasting systems that could survive constant network change, new locations, new product launches, and noisy operational data.
Made pricing models more usable
Focused on practical model design, latency, interpretability, and business continuity in environments where downtime is expensive.
Led through ambiguity
Strong projects need more than model quality; they need communication, trust, and systems people can operate.
Services
Clarify where AI fits, which use cases deserve investment, what the architecture should look like, and how to sequence execution without overcommitting too early.
Design grounded assistants, retrieval workflows, internal knowledge tools, and process automation that respect latency, cost, security, and trust.
Build or improve forecasting, pricing, recommendation, scoring, and optimization systems with an emphasis on measurable business impact.
Partner with founders or product leaders on technical direction, vendor evaluation, hiring, team mentoring, and go-to-production execution.
Core expertise
Retrieval-augmented generation, prompt workflows, source-grounded answers, evaluation loops, and internal copilots.
Forecasting, regression, classification, recommendation, anomaly detection, and experimentation in real operating environments.
Pricing services, operational planning tools, automation pipelines, and data products that have to support live business decisions.
Bridging founders, executives, operators, analysts, and engineers so that complex systems are usable, trusted, and aligned with the business.
Engagement models
A focused engagement for early-stage teams exploring AI product ideas, architecture, or MVP scoping.
Ongoing support for teams that need senior technical judgment without a full-time AI executive hire.
Hands-on implementation, review, and coaching alongside product, engineering, or analytics teams.
Looking for a partner?