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The AI Opportunity Audit

We find where AI moves
the needle in your business.

In 30 days we map your highest-value AI opportunities, put dollar estimates on each one, and hand you a prioritized plan to act on them. Engineers from Google, Amazon, and MIT — not generalists with a slide template.

check_circleProcess automation gaps
check_circleRevenue & forecasting opportunities
check_circleData you're collecting but not using
check_circleRanked by ROI and time to value
Book a 20-minute call arrow_forward See what's in the audit
30 days · kickoff to readout
Fixed fee · scoped upfront
Any industry · B2B focus
AUDIT Acme Corp — AI Opportunity Map
Day 28 of 30
Opportunities Identified
8 actionable builds

3 high-priority items addressable in under 90 days. Est. combined impact: $340K–$520K / yr.

smart_toy
Inbound triage automation
~14 hrs/week of manual routing eliminated
High ROI
bar_chart
Demand forecasting model
3 yrs of transaction data — currently unused
High ROI
description
Contract review assistant
Legal team: 6–8 hrs per contract today
Quick win
people
Churn prediction model
12-mo retention data available, no model
Medium term
Sample findings · B2B SaaS · 80-person company 8 of 8 mapped
Team pedigree
The gap

Most companies know AI matters.
Almost none know where to start.

The opportunity isn't obvious from the inside. You need someone who can read your operations, understand the technology, and connect the two — without a six-month engagement to get there.

70%
of AI initiatives fail to move past pilot

Wrong starting point

Most teams start with a technology and look for a use case. The ones that work start with a specific operational problem and work backwards to the right tool.

errorSolution looking for a problem
3–6
months typical time to first result

Too slow to validate

By the time most engagements produce a finding, the business has moved on or lost confidence. You need a short feedback loop — results before the budget cycle closes.

trending_upMomentum dies in discovery
$0
in measurable returns from most "AI strategies"

No dollar estimate

Vague recommendations with no ROI attached are easy to deprioritize. Every opportunity we identify comes with a dollar range and a time-to-value estimate.

errorPotential savings, not real ones
The Offer

What you get. What it costs.

You give us access to your team and your data. In 30 days we hand you a prioritized map of AI opportunities with ROI estimates on every line — not "potential savings." Specific opportunities, specific numbers, specific next steps.

Standard engagement
$25,000
Multi-company pricing available

What you get

  • AI Opportunity MapEvery viable use case, ranked by ROI and effort Core
  • Process Automation AnalysisManual workflows that AI can eliminate or accelerate Core
  • Data Asset InventoryWhat you're collecting that you're not using yet Core
  • ROI Estimates per OpportunityDollar ranges and time-to-value for each finding Bonus
  • 90-Day Action PlanSequenced builds, starting with highest ROI Bonus
  • Executive Readout60-min session with your leadership team Bonus
  • No-results guaranteeNo clear opportunities? You pay nothing. Risk Reversal

What we need from you

  • Access to 2–3 key stakeholdersOps, product, or whoever owns the workflows ~3 hrs total
  • Relevant data exportsWe'll tell you exactly what after the kickoff call Read-only
  • 60-min kickoff callScope, priorities, and access sign-off Once
  • 60-min readoutWe present findings; you bring the decision-makers Once
What comes next
Audit in hand, you choose:
build in-house or engage us to build it.
Either way, the findings are yours. No lock-in.
The guarantee: If the audit doesn't surface clear, actionable AI opportunities with a credible path to positive ROI, you owe us nothing.
Start an audit arrow_forward
How It Works

30 days, four touchpoints.
Minimal lift on your side.

No months-long discovery. No army of consultants in your office. You give us access to the right people and data — we do the work and come back with findings.

D-0Kickoff

Scope & access

60-min call to align on priorities, map the business areas we'll cover, and confirm data access. We lock the readout date 30 days out.

linkSigned agreement
D-7Discovery

We map your operations

Stakeholder interviews, workflow review, and data inventory. We build a clear picture of where time and money are going and what data assets you have to work with.

groups2–3 stakeholder calls
D-21Analysis

Opportunities sized

Every viable AI use case identified, assessed for feasibility, and assigned an ROI estimate. Ranked by impact and time to value.

analyticsValidation check with your team
D-30Readout

Plan & next steps

60-min executive readout. Written report. 90-day action plan with every opportunity sequenced by dollar value and ease of execution.

checklistYou decide how to act on findings
"Most AI engagements tell you AI is important and leave you with a roadmap you don't know how to execute. We tell you the three things worth building and why — then we can build them."
— Zach Chao, Co-Founder
The Team

Engineers who've shipped at scale,
not consultants who've advised on it.

We've built production systems at some of the most technically demanding companies in the world. That's the difference between finding opportunities that are theoretically possible and ones that will actually get built.

Zach Chao
Zach Chao
Co-Founder · Engineering & AI

Software engineer at Google, Amazon, and Twitter. UC Berkeley CS. Runs the technical side of every engagement — data pipeline, modeling, and the analysis that turns raw operational data into specific, actionable recommendations.

verified_userGoogle · Amazon · Twitter schoolUC Berkeley CS hubHealthcare data systems codeSearch · ads · revenue systems
Greg Lin
Greg Lin
Co-Founder · Platform Engineering

MIT CS. Co-founded CrossInstall — $50M+/yr ad-tech, acquired by Twitter. Senior Staff Engineer at Twitter post-acquisition. Brings the systems experience to handle any data infrastructure challenge that comes up in the audit or a subsequent build.

schoolMIT MS · CS & Engineering rocket_launchCrossInstall founder (acq. Twitter) verified_userTwitter Senior Staff Engineer dnsAd-tech · $50M+ revenue systems
Arnaud Pilpré
Arnaud Pilpré
Engineering Leadership & Strategy

MIT MSc. Former CTO at Chartboost. Led the 65-engineer MoPub team at Twitter post-acquisition. Co-founded CrossInstall — acquired by Twitter — where he scaled engineering from the ground up. Brings executive-level engineering judgment to every audit and roadmap.

schoolMIT MSc · Media Arts & Sciences verified_userCTO · Chartboost groupsTwitter · 65-engineer org rocket_launchCrossInstall founder (acq. Twitter)
Daniel Preda
Daniel Preda
Machine Learning & Data Science

PhD CS from UC Berkeley, MIT M.Eng. Staff ML Engineer at Twitter owning real-time bidding models for ads. Principal Data Scientist at CrossInstall. 6+ years at Quantcast growing from IC to team lead across display advertising and ML systems.

schoolPhD CS · UC Berkeley schoolMIT M.Eng. · CS verified_userTwitter Staff ML Engineer bar_chartReal-time bidding · Ad ML systems
Siddhartha Datta
Siddhartha Datta
AI Research

Postdoctoral researcher at Columbia. PhD in Computer Science from Oxford, with research at Cornell under Prof. Kilian Weinberger. Google Research Scientist intern. Finance background spanning Goldman Sachs, Credit Suisse, and Société Générale across trading and derivatives — bridging rigorous ML research with real-world financial systems.

schoolPhD CS · University of Oxford verified_userPostdoc · Columbia University searchGoogle Research Scientist bar_chartGoldman Sachs · Credit Suisse
Jason Lee
Jason Lee
Infrastructure & Site Reliability

UBC Computer Engineering. Senior SRE at Twitter post-acquisition. 6+ years as Senior Software Engineer at CrossInstall — handling 500 billion web hits a month on AWS. Keeps the systems we build running at scale in production.

schoolUBC · Computer Engineering verified_userTwitter Senior SRE dnsCrossInstall · 500B req/mo on AWS cloudInfrastructure at scale
Why us

We've shipped the systems you're trying to build. That changes what we look for.

Consultants who haven't built production AI systems will find different opportunities than ones who have. We know what's actually hard, what breaks in practice, and what can realistically be delivered in 90 days versus what's a two-year project.

30
Days to findings
Scoped, delivered, and actionable — before the next budget cycle.
3
Companies represented
Google, Amazon, Twitter — systems at scale, not slides.
$0
If we find nothing
No clear opportunities with a credible ROI path — you don't pay.
PhD
Quant on every audit
Every ROI estimate is modeled, not guessed.
Pricing

Fixed fee, fixed scope.

You know what you're paying before we start. No time-and-materials, no scope creep, no surprises.

Engagement
Fee
Notes
AI Opportunity AuditCORESingle company · guarantee included
$25,000
30-day engagement. Full opportunity map, ROI estimates, data asset inventory, 90-day action plan, and executive readout.
Multi-Entity AuditPortfolio companies or business units
$20K / entity
Run the audit across multiple companies or divisions simultaneously. Includes a cross-entity comparison report.
Build EngagementPost-audit implementation
Scoped separately
Once you have the audit in hand, we can scope and build the highest-priority items. Priced per project based on complexity.
Retained AdvisoryOngoing AI leadership
$10–15K / mo
For companies that want continued technical guidance as they execute on findings — roadmap reviews, build oversight, and a direct line to the team.
FAQ

Common questions.

That's the guarantee. If the audit doesn't surface clear, actionable opportunities with a credible path to positive ROI, you pay nothing. In practice, every company we've looked at has had multiple high-value AI opportunities that weren't being captured — the question is always prioritization, not whether they exist.
B2B companies with established operations — typically 20 to 500 employees — where there are real workflows, real data, and real decisions being made manually that don't need to be. Industry doesn't matter as much as operational complexity and data maturity. The best fit is a company that knows AI is relevant but hasn't had the technical bandwidth to figure out where to start.
Minimal. We need about three hours of stakeholder time total — a kickoff call and two or three short interviews. Everything else happens on our side. The readout is the only other meeting on your calendar.
No. The audit deliverable is yours regardless of what you do next. Some clients build in-house, some bring in other teams, some engage us. The findings are specific enough that any competent engineering team can act on them.
Two things. First: the team. Engineers from Google, Amazon, and MIT who have actually built the kinds of systems we're recommending — not strategists with a framework. Second: the deliverable. You get specific opportunities, specific dollar estimates, and a sequenced action plan. Not a capability assessment or a maturity model — something you can act on the day after the readout.
Agreements signed and kickoff scheduled within two weeks of your first call. Readout 30 days after that. Written findings in hand inside six weeks, start to finish.
Ready when you are

Find out where AI moves
the needle for your business.

20 minutes. We'll tell you if we're a fit, what the audit would cover, and what pricing looks like. If it's not the right engagement for your company, we'll tell you that too.

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