What we do
Four layers of AI transformation. Each one builds on the last. Start wherever you are — we meet you there.
Strategy
Before building anything, we find the right things to build.
Most AI initiatives fail because they start with technology instead of business outcomes. We embed with your leadership team to map every process, quantify the opportunity, and build a roadmap your entire organization can rally around.
This isn't a slide deck exercise. We interview operators, review workflows, audit your data landscape, and pressure-test every assumption before a single line of code is written.
From our work
An insurance distributor came to us wanting “an AI chatbot.” Three days into the engagement, we showed them their real opportunity wasn't a chatbot — it was the 200 hours a month their team burned re-keying renewal data between two systems. We shipped a roadmap in under a week. The first automation went live before the chatbot conversation even finished.
What you get
- AI readiness assessment across all business functions
- Process-level opportunity mapping with ROI estimates
- Data landscape audit — what you have, what you need
- Prioritized roadmap ranked by impact and feasibility
- Executive alignment workshop with your leadership team
- Build-vs-buy analysis for each initiative
Data foundations
Every AI initiative stalls at the same point: the data isn't ready.
Dirty data, siloed systems, no pipelines. Traditional data engineering projects take 6-12 months. Our AI accelerators automate the entire lifecycle — ingestion, transformation, quality checks, and delivery — compressing that timeline dramatically.
We don't just build pipelines. We implement data governance from day one — lineage tracking, access controls, quality monitoring, and automated alerting. Your data team inherits a production system, not a prototype.
See our AI accelerators→From our work
A healthcare group had 40 clinics running on a mix of spreadsheets, an EHR from 2014, and a billing system no one fully understood. Their “reporting” was a finance analyst copy-pasting numbers every Friday. We wired up automated pipelines in days, not months. That analyst now spends Fridays on actual analysis instead of data entry — and the CEO sees real numbers for the first time, not last month's guess.
What you get
- Automated data pipelines from all your source systems
- Clean, transformed, production-ready datasets
- Data governance framework — lineage, access controls, cataloging
- Data quality monitoring with automated alerting
- Build, train, transfer — we build it, train your team, hand it over
- Documentation, runbooks, and team training
- Support for hiring your first data engineer
Transformations
Automate the work your team does manually today — with humans in the loop.
Approvals, document processing, compliance checks, reporting — your team spends hours on work that AI handles well. We build and deploy production automation systems with human-in-the-middle review at every critical step.
Every workflow includes escalation paths, audit trails, and exception handling. AI handles the routine; your team handles the judgment calls. Over time, as confidence grows, you decide what to fully automate.
From our work
An education company's ops team was drowning — every enrollment application meant opening a PDF, eyeballing the documents, typing data into two different systems, then emailing someone for approval. They were hiring temps every quarter just to keep up. We built an AI workflow that reads the documents, validates eligibility, routes exceptions to a human, and populates both systems automatically. No more temps. Same team, 4x the throughput.
What you get
- Process audit to identify high-value automation candidates
- Production AI workflows deployed in your environment
- Human-in-the-middle review for critical decisions
- Escalation paths and exception handling built in
- Full audit trails for compliance and governance
- Integration with your existing tools and systems
- Monitoring dashboards with performance metrics
- Build, train, transfer — your team owns it when we're done
- Team training and documentation for ongoing operations
- Hiring support for operations and automation roles
Applications
Custom AI products built on your data that directly drive revenue.
Once your data is ready and your processes are automated, you can build AI products that create real competitive advantage. Recommendation engines, forecasting models, decision automation — applications that compound value over time.
Every application includes a rigorous evaluation framework — offline evals, A/B testing, and continuous monitoring. We track model drift, measure business impact, and retrain when performance degrades. You get production AI with the governance to trust it.
From our work
A consumer products company had a sales team making gut-call inventory decisions on 800 SKUs. Some items sat in the warehouse for months. Others sold out and they lost the sale. We built a forecasting model that pulls from their POS data, seasonality patterns, and supplier lead times — then pushes recommended orders directly into their buying workflow every week. Within a quarter, stockouts dropped 30% and the buying team went from reactive to strategic.
What you get
- Custom AI models trained and evaluated on your data
- Production applications with APIs and user interfaces
- Evaluation framework — offline evals, A/B testing, benchmarks
- Model monitoring with drift detection and automated alerts
- Retraining pipelines for continuous improvement
- Governance controls — explainability, bias testing, audit logs
- Full source code and model ownership transferred to you
- Hiring support for ML engineers to maintain long-term
Ready to start?
Tell us where you are and where you want to be. We'll show you how to get there in weeks, not months.
Get started→