Data Readiness Review
We assess whether your data is complete, accessible, and governed enough to train and run on.
AI Audit
You're ready to invest in AI.
You're ready to invest in AI.
Let's make sure it goes where it matters most.
The AI Audit maps your biggest opportunities, stress-tests your data and systems, and delivers a prioritized roadmap with real ROI numbers — in 2 to 4 weeks, fixed scope, no surprises.
—— What you walk away with
You leave with a plan, not a slide deck.
Every deliverable is built to give your team the clarity and confidence to make real AI investment decisions.
AI Opportunity Map
A prioritized list of AI use cases ranked by business impact, feasibility, and data readiness — with clear rationale.
Integration Risk Assessment
Identifies data gaps, API bottlenecks, and compliance concerns — exposing the integration landmines before deployment.
ROI Model & Cost Estimates
Realistic financial projections for your top use cases, with build costs, timelines, and expected returns.
Phased Implementation Roadmap
A concrete plan with sequenced phases, resource requirements, and decision gates — executable with or without a vendor.
—— Services
What the audit actually covers.
Six tracks of work that turn "we should do AI" into a decision you can defend — each feeding the roadmap you leave with.
Systems & Workflow Audit
We map your tech stack and integration points to find where AI can plug in without breaking what works.
Opportunity Mapping
We surface and rank candidate use cases by business impact, feasibility, and data readiness.
Build-vs-Buy & Model Fit
We weigh custom builds against off-the-shelf models so you spend on the right approach, not the trendy one.
Risk & Governance Review
We surface compliance and governance concerns early, aligned to the NIST AI Risk Framework.
Roadmap & Next Steps
We deliver a phased plan with decision gates your team can execute with or without a vendor.
—— How it runs
Four phases. Zero wasted motion.
Refined across hundreds of engagements, with clear inputs and outputs for every phase.
1
Week 1
Landscape & Data Assessment
Map your tech stack, data assets, integration points, and readiness — and spot the "integration black hole" before it costs you.
2
Week 1–2
Opportunity Identification
Working sessions to surface, evaluate, and prioritize use cases — stress-tested against feasibility, data, and business value.
3
Week 2–3
Team & Organizational Readiness
Evaluate internal capabilities, change-management readiness, and stakeholder alignment — because tech fails in unprepared orgs.
4
Week 3–4
ROI Modeling & Roadmap Delivery
Build the financial models, define success metrics, and deliver a phased roadmap that turns "we should do AI" into a plan.
—— What becomes possible
Start from clarity. Build from confidence.
The audit doesn't just assess what you have — it unlocks what you can do next.
Start with clarity, not a hunch
Most teams have 15 AI ideas and one budget. The audit tells you which three to bet on — and in what order.
Know your data is ready before you commit
We assess your data assets before a line of code is written — so there are no surprises two months in.
Walk into the board conversation with numbers
Real ROI models, real cost estimates, real timelines. A plan your CFO can sign off on.
—— The audit, week by week
A short audit, plotted out.
The audit itself runs 2–4 weeks. The later weeks show what it sets up — a build that starts from a plan, not a guess. Phases overlap; opportunity work doesn’t wait for the data review to fully wrap.
LANDSCAPE
OPPORTUNITY
READINESS
ROADMAP
RESULTING BUILD
WEEK 1Audit
WEEK 2Audit
WEEK 3Audit
WEEK 4Audit
WEEK 5Build
WEEK 6Build
WEEK 7Build
WEEK 8Build
WEEK 9Build
WEEK 10Build
WEEK 11Build
WEEK 12Build
—— Investment
A fraction of the cost of a failed build.
Fixed scope, fixed price — scaled to your organizational complexity.
Fixed-scope engagement
$10K–$20K
2–4 weeks · scoped to your organizational complexity.
Start your audit →- Prioritized AI opportunity map with feasibility scoring
- Integration risk assessment and data-readiness evaluation
- ROI model with defensible cost and timeline estimates
- Phased implementation roadmap with decision gates
- Go/no-go recommendation aligned to the NIST AI Risk Framework
- Executive presentation for internal stakeholder alignment
—— Selected work
The team behind the audit ships, too.
Our recommendations come with real cost estimates because we build as well as advise. A few of the products we’ve shaped — from connected fitness and healthcare to mobility and IoT.
—— Where the audit leads
The audit is the starting gun. Here's what comes next.
Your roadmap will point to one or more of these — each one picks up exactly where the audit leaves off.
AI Prototype Sprint
Validate your top use case with a working prototype in 3 weeks — before committing the full build budget.
Explore Prototype Sprint →AI-Native Development
Full-stack engineering for AI products — from architecture through launch, with a senior team that stays.
Explore AI-Native Build →AI Agentic Systems
Multi-agent architectures that reason, decide, and act — for workflows too complex for single-model solutions.
Explore AI Agentic Systems →Intelligent Automation
Turn manual workflows into AI-powered systems — document processing, approvals, data pipelines, and operational intelligence.
Explore Automation →AI Growth Engine
Growth strategy, acquisition channels, conversion optimization, and a team that runs it month over month.
Explore Growth Engine →—— Common questions
What teams ask first.
Whether you need an audit, what access we need, using the deliverables elsewhere, how we differ from consultants, and what a "no" means.
We already know what we want to build. Do we still need an audit?
Maybe not — if you have a clear use case, validated data readiness, and a technical plan. Otherwise an audit is the cheapest insurance you can buy against a six-figure mistake.
What access do you need from our team?
Key stakeholders for working sessions, your technology-stack documentation, and relevant data assets. No production systems or sensitive customer data required.
Can we use the audit deliverables with another vendor?
Yes. All outputs are yours and vendor-agnostic, designed for use with any provider. The audit still saves months of discovery and de-risks the investment.
How is this different from a consulting firm's AI assessment?
Most firms produce frameworks; we produce buildable plans. Our team has shipped 100+ products, so the recommendations come with real cost estimates from engineering experience — not theory with 3× variance ranges.
What if the audit concludes we should not build AI?
That's a successful audit — you just avoided spending $150K or more on the wrong thing. You'll get a clear explanation of why AI isn't the best path right now.
—— Field notes
What we’re writing about.
Field notes from the studio — what we’re learning about AI products, agent UX, and the messy reality of shipping software in 2026.
