We test your data, rank your opportunities by payback speed, and hand you a validated roadmap before you spend a dollar on development.
We build custom AI systems that deliver measurable ROI for established companies. Production-grade solutions built by engineers who've shipped 150+ AI projects. Purpose-built systems around your data, your workflows, and your team.
Projects with pre-defined success criteria and roadmaps are 4.5x more likely to deliver business value.
Companies that validate feasibility before building avoid the average 46% AI proof-of-concept abandonment rate.
Go from initial audit to a funded, buildable implementation plan in a single quarter.
Most AI projects fail because the wrong problem was picked, not because the technology isn't available. We figure out which ones will actually pay off.
We audit every department (sales, ops, finance, support) and score each bottleneck on frequency, business impact, data readiness, and error tolerance. You get a ranked list of AI opportunities ordered by how fast they'll pay back, not how exciting they sound in a pitch.
Every opportunity we recommend includes a financial model with build costs, revenue impact, cost savings, and payback timelines. Your CFO gets projections grounded in your actual operations, not industry averages pulled from a report.
We run experiments against your actual data to prove the approach works before you sign off on a development budget. If the data isn't ready or the approach won't hold up, we tell you that too.
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Every bottleneck in your organization is scored, ranked, and categorized into tiers from "build now" to "revisit later," with the math behind each ranking visible to your leadership team.
Architecture, model selection, integration points, security requirements, and phased milestones for each priority initiative. This is what your engineering team (ours or yours) needs to start building.
A financial model for each initiative covering phased adoption, revenue projections, cost savings, and break-even timelines your finance team can actually stress-test.
We sit down with the people who do the work. Every pain point, workaround, and manual process gets documented.
We assess what data exists, where it lives, and how clean it is. Then we test approaches against your real data. If K&L Wines taught us anything, it's that the obvious AI approach is often wrong. They tried off-the-shelf AI first, it failed, and a custom ML model ended up saving them $273K annually.
We build ROI models for each opportunity and rank them so you're funding the highest-payback projects first.
You receive implementation plans, financial models, and a prioritized opportunity scorecard ready for executive sign-off.
AI strategy with a measurable impact
Consulting teaches your team to use AI tools and builds governance policies. Strategy is the planning layer: we audit operations, test your data, model the ROI, and produce a buildable roadmap.
4 to 6 weeks for most companies, including stakeholder interviews, data assessment, financial modeling, and roadmap delivery.
Three deliverables: a prioritized opportunity scorecard, a technical implementation plan for each priority initiative, and a ROI payback model.
No. Evaluating your data readiness is part of what we do. Most companies don't know where they actually stand until we look.
Yes. We've shipped over 150 projects. Many clients move straight into development with us because the plan is already built. But you own everything and can build with anyone.
Build a new platform, or add AI capabilities to existing software, we deliver solutions that work in real operational environments.
Meet with founders Andrew Amann & Pavel Kirillov
Custom AI implementation roadmap
No sales pressure
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