Services
Hands-on senior leadership that ships production data and AI systems, as fractional leadership or a scoped build, with a team in the US or Latin America when you need the capacity.
Fractional data and AI leadership
The problem: Leadership has stopped trusting the numbers, the roadmap depends on data and AI work nobody senior owns, and a full-time hire is months away.
What we deliver
- Assessment of the data foundation and a plan to build trust in it
- Metric definitions, standards and governance your teams actually follow
- Architecture reviews and technical due diligence
- A prioritized data and AI roadmap tied to business outcomes
Engagement and outcomes
Typical engagement: Part-time embedded retainer, often paired with a hands-on build
Outcomes:
- Core metrics the leadership team trusts
- Clear ownership and governance for data
Technologies we use
Production AI systems
The problem: AI prototypes are easy to demo and hard to trust. Without evals, monitoring and cost controls they stall before production or get expensive once they are there.
What we deliver
- LLM-powered matching and enrichment of product catalogs
- Search relevance, ranking and recommendation systems
- Agents and RAG systems grounded in your own data
- Orchestration harnesses that let agents run scientific and biotech pipelines
- Eval harnesses built before launch, not after
- LLM cost right-sizing: spend matched to value, smaller models where evals allow
Engagement and outcomes
Typical engagement: Scoped build, often followed by a fractional retainer
Outcomes:
- AI features running in production
- Evals that catch regressions before customers do
- LLM spend that tracks the value it creates
Technologies we use
Modern data platforms and observability
The problem: Legacy databases and manual reports cannot keep up, and data problems reach customers or executives before the data team hears about them.
What we deliver
- Cloud data platforms on Snowflake or Databricks, modeled with dbt
- Orchestration with Airflow or Dagster
- Self-serve analytics apps, including Streamlit in Snowflake
- Anomaly detection and data-quality monitoring with alerting
- Healthcare claims ingestion: medical, pharmacy and eligibility files
- Legacy-to-cloud modernization without disrupting the business
Engagement and outcomes
Typical engagement: Scoped build with a clear handoff to your team
Outcomes:
- A platform your team can extend on its own
- Data issues caught before they reach users
- Faster answers through self-serve analytics
Technologies we use
Team building and delivery
The problem: You need more engineering capacity than you can hire, and outside vendors are hard to evaluate until you are already committed.
What we deliver
- Vendor selection and RFPs run on your behalf
- Teams in the US and Latin America, selected, stood up and led by us
- AI-accelerated engineering in the Anthropic Claude Code and OpenAI Codex ecosystems: agentic coding workflows, CI and code review
- Onboarding, documentation and knowledge transfer to your team
Engagement and outcomes
Typical engagement: Team extension, ongoing or tied to a scoped build
Outcomes:
- Capacity that overlaps your working hours
- Engineering practices that hold up as the team grows
- A team that can keep running without us
Technologies we use
How we engage
Three ways to work together. Most clients start with one and add another as needs change.
Fractional leadership
Ongoing, part-time embedded
A senior technical leader who scopes product and data and engineering strategy, and builds solutions with modern AI code orchestration.
Scoped build
Typically 6-12 weeks
Fixed scope and clear deliverables, ending with a system in production and a handoff your team owns. Larger programs run in phases.
Team extension
We select, stand up and lead
A team in the US or Latin America, led by us and working your hours, for when you need capacity.