SERVICE 01

Operations Control Tower

Real-time operational visibility that turns scattered data into confident decisions.

We build custom operations dashboards that unify your WIP, TAT, Yield, Aging, and Discrepancy metrics 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 identify bottlenecks before they cascade.

What We Build

Operations leaders in repair, logistics, and manufacturing environments face a common challenge: data trapped in silos, manual reporting that's always outdated, and blind spots that surface only when customers complain. Our Operations Control Tower solves this by integrating your WMS, ERP, sensor data, and operational systems into unified, real-time dashboards built for your specific KPIs.

We don't deliver generic templates. Every dashboard is designed around how your operations actually work — the stations, vendors, flows, and metrics that matter to your business. Alerts trigger when a station backs up, a vendor underperforms, or aging inventory crosses a threshold. The result: ops meetings focused on action instead of data reconciliation, and problems caught while they're still small.

The Transformation

Before

Monday ops meetings start with 45 minutes reconciling different spreadsheets. TAT reports are 3 days old. The inventory aging problem showed up on the P&L — nobody saw it coming. You spend more time defending your data than improving operations.

After

Dashboards are on screen before the meeting starts. Same numbers everywhere. An alert caught WIP backing up in the repair queue before it became a problem — fixed in two hours. SLA compliance is up 15 points. You focus on improvement initiatives instead of firefighting.

Business Outcomes

Eliminate manual reporting — typically 15-30 hours/week recovered

Reduce SLA breaches through early warning systems

Lower inventory write-offs via aging visibility

Cross-functional alignment on metric definitions

Foundation for AI/ML initiatives with clean, visible data

Why Now

  • Recent SLA breach triggered customer complaint or penalty
  • Inventory write-offs just hit the P&L
  • New COO or ops leader mandated to "fix visibility"
  • Volume is scaling and current systems can't keep pace
  • Board asking for operational metrics you can't confidently provide

What Makes Us Different

We speak operations — WIP, TAT, Yield, Aging, Discrepancies. Our dashboards aren't generic BI templates; they're built around how your operations actually work. First dashboards go live in 4-6 weeks, not 6 months. And we include alerting infrastructure so you catch problems before they cascade.

SERVICE 02

Unified Data Platform & Warehouse

A modern data foundation that turns fragmented data into trustworthy, actionable insights.

We design and build cloud data warehouses on BigQuery, Snowflake, Redshift, or Azure 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 on data plumbing and start working on things that matter.

What We Build

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 data platform tailored to your business — connecting SAP, WMS, CRM, sensors, and APIs into a single, governed warehouse with tested, documented data models.

Every model is built with dbt, version-controlled, and includes tests that run on every pipeline execution. Documentation is generated automatically. New data sources integrate in days, not months. The architecture is designed to scale with your business, not become technical debt you'll need to rewrite in two years. When we're done, your analysts can self-serve and your engineers can focus on high-value work instead of keeping the lights on.

The Transformation

Before

Data everywhere — SAP, two WMS systems, 50 Google Sheets, databases nobody fully understands. Finance says inventory is $2M. Ops says $2.4M. Nobody knows who's right. Your data engineer spends 70% of her time just keeping the lights on. Every new report is a special project.

After

All data flows into one warehouse through automated pipelines. 200+ dbt models, tested and documented. Finance and Ops see the same number — because it comes from the same source. New data sources take days to integrate. Your data engineer focuses on strategic projects. Self-service adoption at 80%.

Business Outcomes

Reduce engineering time on data plumbing — typically 40-60% recovered

One set of numbers — Finance and Ops stop arguing

New data sources integrated in days, not months

Clean, tested data foundation ready for ML and advanced analytics

New team members onboard in weeks, not months

Why Now

  • Cloud migration or ERP/WMS implementation underway
  • Key data person just left, taking tribal knowledge with them
  • Board or investors asking about data capabilities
  • Previous data warehouse project failed and needs rebuild
  • Compliance audit revealed data governance gaps

What Makes Us Different

We've integrated SAP, WMS, sensor data, GPS, device logs, CRM, and ERP systems across manufacturing, logistics, repair, sports analytics, and subscription businesses. We work across GCP, AWS, and Azure. Everything is built with dbt — tested, documented, version-controlled. Your team owns and extends what we build. No black boxes, no dependency.

SERVICE 03

AI for Operations

Production-ready AI that forecasts demand, detects anomalies, and automates operational decisions.

We deploy ML models that run reliably in production — demand forecasting with documented accuracy, anomaly detection with monitored drift, and automated decision workflows with clear boundaries. No science projects or shelfware; just measurable improvements to inventory costs, quality control, and operational efficiency.

What We Build

The gap between AI hype and AI reality frustrates most operations leaders. Pilots never deploy. Vendors promise magic but deliver PowerPoints. Internal teams lack ML engineering capacity to move models from notebooks to production. We bridge this gap with a production-first approach: starting with your clean data foundation, we build and deploy forecasting models that reduce demand variability, anomaly detection that catches fraud and defects before they cascade, and AI assistants that handle repetitive operational queries.

Every model 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 makes recommendations. And we train your team to maintain, retrain, and improve these systems. AI becomes a capability you own, not a dependency you rent.

The Transformation

Before

You bought an "AI-powered demand planning" tool two years ago. It's shelfware — never worked with your data. Your data science team built a model in a Jupyter notebook, but it never made it to production. Demand forecast errors still cost millions in inventory. Competitors talk about AI while you're in spreadsheets.

After

Demand forecasting runs in production, updated daily, integrated into planning systems. Forecast accuracy improved 22 points. Anomaly detection caught a fraud pattern that would have cost $300K. Your AI assistant handles 60% of routine operational queries. Your team understands and maintains the models.

Business Outcomes

Inventory cost reduction from improved demand forecasting accuracy

Revenue protection from early fraud and defect detection

Analyst time recovered through automated query handling

Models with documented accuracy, drift monitoring, and explainability

Internal team trained to maintain and improve deployed models

Why Now

  • Board asking "what's our AI strategy?" every meeting
  • Competitors announcing AI-powered operations
  • Demand forecast errors just caused a major inventory problem
  • Previous AI investment failed to deliver — need to show ROI
  • Data foundation now stable enough to support ML workloads

What Makes Us Different

We deploy to production. Every model includes documented accuracy metrics, drift monitoring, and retraining procedures. We design for explainability so your team understands the recommendations. Models go live in 6-10 weeks with measurable baselines. No black boxes, no "trust us" — just observable, maintainable AI.

SERVICE 04

Fractional Head of Data

Senior data leadership and execution at a fraction of full-time cost.

Get an experienced Head of Data who sets strategy, builds your roadmap, guides your team, and actually executes — without the 6-month search and $300K+ salary. We embed in your organization to drive real progress, not just deliver advice that sits in a slide deck.

What We Do

You know data is strategic. But hiring a senior data leader takes 6+ months, costs $300K+ fully loaded, and carries significant 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.

The Transformation

Before

You have tools — Snowflake, dbt, Looker — but no strategy. Projects start and stall. Your data engineers are talented but junior; they don't know what "good" looks like. You've tried to hire a data leader for 8 months — can't find the right person or can't afford them. The team feels leaderless.

After

Within the first month, data strategy aligned with business priorities. Roadmap went from "everything is urgent" to a clear sequence of high-impact projects. Data team has weekly 1:1s with a senior mentor. Rationalized $150K in redundant tooling. When ready for a full-time hire, you know exactly what profile you need.

Business Outcomes

Senior leadership at 30-40% of full-time cost

Clear data strategy and prioritized roadmap within 30 days

Reduced wasted spend on wrong tools and failed projects

Data team retention improved through mentorship and career pathing

Board-ready reporting on data capabilities and value

Why Now

  • Head of Data search has been open 6+ months
  • Last data hire didn't work out
  • Data team turnover creating knowledge gaps
  • Board presentation on data strategy coming up
  • Need to rationalize tool spend before budget cycle

What Makes Us Different

We execute. We're embedded in your organization with regular team interaction, not a consultant who delivers a deck and disappears. We've built data functions from scratch, rationalized tool sprawl, developed strategies that secured funding, and mentored teams from junior to senior. When you're ready for a full-time hire, we help you find the right person.

Not sure which service fits?

Most engagements combine elements from multiple services based on your specific situation. Book a 30-minute discovery call and we'll help you identify what makes sense — whether that's working with us or not.