We implement AI for businesses
that don't have AI teams.

Every workflow we build targets a specific, measurable outcome — hours saved, errors reduced, revenue recovered. In our healthcare work, a single order processing workflow recovered $1.2M in annual billing revenue. A reporting consolidation cut 40 hours of monthly work to 4. We don't build anything without a clear ROI model upfront, and the audit phase quantifies the opportunity before you commit to a build.

95% of AI projects fail — and almost always for the same reason: someone built a demo that impressed executives but never connected to actual production systems. The gap between "works in a demo" and "runs in your operation at 2 AM on a Saturday" is massive. That gap is mostly software engineering, not AI. It's data cleanup, API integration, error handling, and monitoring. That's what we do. We don't build demos. We build operations.

Good — that's where we start. 80% of our work is data engineering: cleaning, structuring, and connecting your data before any AI touches it. The case study where we unified 7 systems across 5 states into one platform? That was a data mess. The lab processing 45,000 specimens daily with an 8% failure rate? Data mess. We've never walked into a client with clean data. If your data were clean, you probably wouldn't need us.

No. That's the point. We are your technical team. You don't need to hire AI engineers, data scientists, or ML specialists. You need a single point of contact on your side — someone who knows your operations and can answer our questions during the audit. After that, we handle everything: architecture, development, deployment, monitoring, and maintenance.

RPA automates button clicks. It follows rigid scripts: "click here, copy that, paste there." When the UI changes, it breaks. When the data format varies, it fails. AI workflows understand content. They read a faxed order form with handwriting and extract the data. They review a contract and flag unusual clauses. They predict which claims will get denied before you submit them. RPA is a macro with a marketing budget. AI workflows are systems that think.

We build within your infrastructure, not ours. Your data stays in your environment. We follow SOC 2 practices, sign BAAs for healthcare clients, and design every workflow with audit trails and access controls. The compliance requirements in healthcare (HIPAA, CLIA) and financial services (SOX, KYC/AML) are things we've worked with directly. We don't treat security as an afterthought — it's built into the architecture from day one.

Thirty days notice. No long-term contracts. No penalty fees. Everything we build runs in your environment — you own the code, the data, and the workflows. If you cancel the retainer, the systems keep running. You just lose the ongoing monitoring, optimization, and new development. Most clients don't cancel because the ROI is obvious by month 3, but we never want you to stay because you're locked in. We want you to stay because the math works.

A single bad hire costs $150K+ per year. A consulting firm charges $200K+ for a strategy deck. An RPA implementation runs $40K-$75K with annual license fees on top. Our audit costs $5K-$10K. A typical build runs $25K-$75K. The monthly retainer is $3K-$8K. For most clients, a single automated workflow pays for itself within 90 days. The diagnostics lab that recovered $1.2M in billing revenue spent less than $100K with us. The ROI isn't theoretical — it's in the case studies.