Whatever your industry, each engagement is scoped to your specific challenges. We build production systems that deliver measurable outcomes — dashboards, data platforms, AI models, and strategic leadership.
Real-time visibility into the metrics that run your business — so decisions are made on live numbers, not last month's spreadsheet.
We build custom dashboards that unify your key metrics — revenue, operations, retention, quality, whatever drives your P&L — into a single source of truth. No more spreadsheet wars or waiting days for answers: your team gets live visibility with proactive alerts, so you spot problems before they cascade.
Leaders in every industry face the same challenge: data trapped in silos, manual reporting that's always outdated, and blind spots that surface only when customers complain. We solve this by integrating your ERP, CRM, operational systems, and spreadsheets into unified, real-time dashboards built around your specific KPIs.
We don't deliver generic templates. Every dashboard is designed around how your business actually works — the teams, flows, and metrics that matter. Alerts fire when a queue backs up, a vendor underperforms, or a number crosses a threshold. The result: meetings focused on action instead of data reconciliation, and problems caught while they're still small.
Monday meetings start with 45 minutes reconciling different spreadsheets. Reports are three days old. The problem showed up on the P&L — nobody saw it coming. You spend more time defending your data than improving the business.
Dashboards are on screen before the meeting starts. Same numbers everywhere. Last week an alert caught a backlog building before it became a problem — fixed in two hours. You focus on improvement, not firefighting.
A modern data foundation that turns fragmented data into trustworthy, actionable insight — and frees your engineers from plumbing.
We design and build cloud data warehouses on BigQuery, Snowflake, Redshift, or Microsoft Fabric — with tested dbt models, orchestration via Dagster, Airflow, or Step Functions, and documentation your team can actually maintain. Your engineers stop spending 60%+ of their time keeping the lights on and start working on things that matter.
Most data teams are stuck in a cycle: every new report requires a custom data pull, engineers spend most of their time on maintenance, and no one trusts the numbers enough to make real decisions. We break this cycle by building a unified platform tailored to your business — connecting your ERP, CRM, product databases, sensors, and APIs into a single governed warehouse with tested, documented models.
Every model is version-controlled and tested on every pipeline run. Documentation is generated automatically. New data sources integrate in days, not months. The architecture scales with your business instead of becoming technical debt you'll rewrite in two years. When we're done, your analysts self-serve and your engineers do high-value work.
Data everywhere — an ERP, two operational systems, 50 Google Sheets, databases nobody fully understands. Finance says $2M, Ops says $2.4M, nobody knows who's right. Your data engineer spends 70% of her time keeping the lights on.
All data flows into one warehouse through automated pipelines. 200+ tested, documented models. Finance and Ops see the same number — it comes from the same source. New sources integrate in days. Self-service adoption at 80%.
Production-ready AI — forecasting, anomaly detection, and LLM-powered automation — with measurable ROI, not science projects.
We deploy ML and AI systems that run reliably in production: demand forecasting with documented accuracy, anomaly detection with monitored drift, LLM-powered assistants and automation with clear boundaries. No shelfware — just measurable improvements to cost, quality, and speed.
The gap between AI hype and AI reality frustrates most leaders. Pilots never deploy. Vendors promise magic and deliver PowerPoints. Internal teams can build models in notebooks but can't get them into production. We bridge this gap with a production-first approach: starting from your data foundation, we build forecasting that reduces variability, anomaly detection that catches fraud and defects early, and AI assistants that automate repetitive knowledge work.
Every system we deploy includes accuracy metrics, drift monitoring, and clear documentation of what it does and doesn't do. We design for explainability — your team understands why the model recommends what it does — and we train your people to maintain, retrain, and improve it. AI becomes a capability you own, not a dependency you rent.
You bought an "AI-powered" tool two years ago — it's shelfware. Your team built a model in a notebook that never reached production. Forecast errors still cost millions. Competitors talk about AI while you're in spreadsheets.
Forecasting runs in production, updated daily, integrated into planning. Accuracy up 22 points. Anomaly detection caught a $300K fraud pattern. An AI assistant handles 60% of routine queries. Your team maintains the models.
Senior data leadership and execution at a fraction of full-time cost — embedded in your organization, accountable for progress.
You know data is strategic. But hiring a senior data leader takes six-plus months, costs $300K+ fully loaded, and carries real risk — you might not find the right person, or they might not work out. Meanwhile your data team lacks direction, projects stall, and tools sit underutilized.
Our Fractional Head of Data model gives you experienced leadership from day one. We develop your data strategy tied to business outcomes, prioritize a roadmap that balances quick wins with foundational work, mentor your team with weekly 1:1s and technical guidance, evaluate vendors and negotiate contracts, and execute hands-on when needed.
This isn't advisory work — we're embedded in your organization, accountable for progress, and invested in your success. When you're ready to hire full-time, we help define the role and can assist with the search.
You have tools — Snowflake, dbt, Looker — but no strategy. Projects start and stall. Your engineers are talented but junior. You've tried to hire a data leader for eight months. The team feels leaderless.
Within a month: data strategy aligned with business priorities and a clear sequence of high-impact projects. Weekly 1:1s with a senior mentor. $150K in redundant tooling rationalized. When you're ready to hire, you know exactly what profile you need.
Most engagements combine elements from several services. Book a 30-minute discovery call and we'll help you identify what makes sense — whether that's working with us or not.
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