AI Strategy & Engineering

Enterprise-grade AI,
customized for your business.

We help small and mid-size companies move from experimenting with AI to running it, with the same rigor we bring to billion-dollar brands and a plan your team can own.

Build momentum. Fuel disruption. Drive ROI.

View Case Studies → Learn More

Approach

Assess. Plan. Build.

Most companies are already experimenting with AI: working groups, lunch-and-learns, pilot projects, and teams sharing the latest thing they tried in ChatGPT. That's activity, but not real progress.

FutureInSites helps clients move from experimentation to execution. We assess where you are, identify the opportunities most likely to save time, improve productivity, or create new value, and build the strategy and foundation to deploy them.

We work with professionals, businesses, and investors: from personal OpenClaw agent buildouts, to enterprise strategy and workflow deployment, to AI market intelligence and strategic diligence.

Our work spans retail, manufacturing, media, finance, healthcare, and bio-sciences: industries where AI is reshaping productivity, capital intensity, customer expectations, and competitive advantage.

The goal is not more AI activity. It is measurable business impact.

2 Complementary Practice Areas
$2T+ Market Cap Under Analysis
120+ AI Use Cases Analyzed
100% ROI-Focused Approach
14 AI Markets Mapped
200+ AI Vendor Profiles
Stage 1

Assess

↻ Measure on repeat

Audit your data, talent, culture, and current AI investments. On subsequent passes, measure what is running.

  • Capability Heatmap
  • Gap Analysis
  • Current State Audit
→
Stage 2

Plan

Translate findings into a prioritized roadmap, an architecture that protects optionality, and a clear next move.

  • Defining Architecture
  • Buy vs Build Decisioning
  • Use Case Prioritization
→
Stage 3

Build

↻ Optimize on repeat

Build and integrate under Build-Operate-Transfer. On subsequent passes, refine and upgrade what is running.

  • Custom Agent Development
  • Workflow Orchestration
  • Platform Integration
You operate what gets built. Embedded AI Engineering is available for ongoing support and upgrades.

Solutions

What we do

FutureInSites works across three audiences: individuals, businesses scaling from SMB through enterprise, and investors making AI bets in a fast-moving market.

Professionals

Done-for-you personal AI agent setups for executives and high-output professionals. Configured to your workflow, your tools, and your data, on hardware you own.

Businesses

AI strategy and transformation for SMB through enterprise. Readiness, roadmap, vendor selection, governance, and build, delivered under a Build-Operate-Transfer model your team can own.

Investors

Strategic counsel and AI market intelligence for fund partners, family offices, and corporate development teams. Vendor due diligence, thesis development, and quarterly briefings.
View all Solutions →
Signature Engagement

AI Transformation Session

A 2-day onsite intensive that takes your leadership team from "we should do something with AI" to a prioritized roadmap and live development. We come onsite with pre-researched analysis of your business; you leave with both clarity and momentum.

Day 1
The AI Landscape

Survey the terrain together. AI history, fundamentals, and the current vendor landscape. Frameworks for thinking about AI ROI, risk, and competitive timing. Where your industry sits on the inflection curve.

Day 2
Your AI Roadmap

Chart your path through the landscape. Readiness assessment, prioritized AI application analysis, buy-vs-build evaluation, and a sequenced roadmap built on pre-researched analysis of your business.

Why Us

Strategy plus execution, without the trade-off

Most firms force you to pick between thinking and building. We do both.

Traditional
Consultancies		 Outsourced
Engineering		 FutureInSites
What you get A deck and a roadmap A finished build to your spec A working asset you own, plus the playbook to run it
AI depth Generalists ramping on AI Builders without strategic context Practitioners tracking the AI landscape weekly
Engagement shape Large team, months of discovery Fixed scope, contractor handoff Small team, Build-Operate-Transfer
Speed to first value Quarters to a recommendation Weeks to a build Weeks to a pilot, with you trained alongside
After delivery Recommendations, then exit Project ends at delivery Co-operate while you grow into ownership
Cost shape Premium fees, large overhead Hourly billing, scope creep risk Defined offerings, priced by outcome

Selected Case Work

Three case studies. Three angles on AI value.

An NLP sentiment study of a major automotive brand. Investment-grade diligence on an AI infrastructure business. Forecasting analysis of AI's impact on an incumbent platform's economics. Three angles on how AI is changing how value is created, captured, and measured.

TESLA
Automotive · NLP & Sentiment Analysis

An NLP case study on Tesla's Twitter brand across 2018 and 2020. ~2.4M tweets analyzed through VADER, a default BERT classifier, and a BERT model fine-tuned on Sentiment140. Findings on engagement-weighted sentiment, hashtag evolution, and what model choice reveals about domain match.

VADER & BERT Engagement-Weighted Sentiment Social Listening
ORACLE
AI Infrastructure · Investment Diligence

An Investment Committee memo analyzing Oracle's $455B AI backlog. Two-scenario DCF, GPU economic obsolescence vs. extended GAAP useful lives, customer concentration across NVIDIA, AMD, and OpenAI. Strong Underweight; new normal fair value $75 vs. $164.52.

Two-Scenario DCF GPU Obsolescence Customer Concentration
Google
Incumbent Platform · AI Economics

A two-engine business architecture modeling Search/Services and Cloud separately. AI Overviews monetization, Gemini long-query monetization, and the 2026 CapEx / D&A trough explicitly preserved. Net call: AI raises continuing value, modestly. Maintain.

Two-Engine Architecture Cloud CapEx Continuing Value

Tesla, Oracle, and Alphabet are subjects of analysis, not engaged clients. Case studies are educational analytical work product authored by FutureInSites for illustrative purposes. All data is drawn from publicly available sources and cited inline.

Premier Case Study

Our most comprehensive engagement

A full-scope AI strategy: readiness assessment, competitive benchmarking, use case prioritization across 12 initiatives, governance framework, and a phased three-pillar implementation roadmap.

Premier Case Study
lululemon athletica

From PAVE to Platform: Building the AI Foundation for Lululemon's Next Growth Chapter

A full-scope AI strategy for a $10B+ premium athleisure brand at a strategic inflection point: declining U.S. comps, aggressive new competitors, and a newly appointed Chief AI & Technology Officer. Our analysis covers capability assessment, competitive benchmarking, use case prioritization, and a phased three-pillar implementation roadmap.

$400–600M Projected Revenue Impact
$85–110M 3-Year Investment Range
12 Initiatives Evaluated
4–7x Projected Return on Investment
View Full Case Study →
lululemon Premier Case Study · AI Strategy
lululemon lululemon lululemon

Team

Enterprise Expertise

Industry depth and research rigor across the verticals where AI is changing the economics fastest.

Greg Loeffelholz
Greg Loeffelholz
Founder & Managing Principal
Advertising & Media

Over 25 years scaling data, ML, and GenAI platforms as a strategic leader. Led engineering and data science at MotiveMetrics' AI SaaS platform optimizing $100MM+ in paid search, with P&L and SOC 2 governance. MarTech DSP & CDP leadership at Inmar Intelligence and Nelnet. Vanderbilt BA, Boston College MBA in AI & Machine Learning.

Jeff Hoffman
Jeff Hoffman
Principal Consultant
Healthcare & Retail

Two decades of digital product leadership across pharmacy, retail, and healthcare. VP roles at Walgreens leading 200+ product and engineering professionals, Best Buy heading Digital, Analytics, and Technology, and CVS Health as Chief Digital Officer for Pharmacy overseeing $13B in digital revenue. Tufts BA, Chicago Booth MBA in Strategic Management and Finance.

Miao Liu
Miao Liu
Technical Advisor
Investment & Finance

Assistant Professor of Accounting at Boston College's Carroll School, researching the intersection of accounting and AI. Builds RAG systems applied to financial disclosure and publishes on human-AI collaboration in corporate valuation. Teaches an AI Applications in Business course at BC. Wuhan University BA, University of Chicago PhD.

Ready to build your AI strategy?

Whether you're starting from zero or scaling an existing AI program, we'd love to explore how FutureInSites can help your organization move faster with more confidence.

To contact us, email strategy@futureinsites.com or use the form below.