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Fulkerson Advisors
Vol. I·MMXXVIAn advisory firm

AI strategyfor organizationsthat need it toactually work.

We help Fortune 500 leaders move beyond pilots — designing, building, and shipping AI systems that survive contact with production.

Schedule a briefingRead our work

Selected engagements

  • Profit Isle
  • IntelliVen
  • ALEE
  • $55B US Pension FundIndexing automation
  • Top-5 US Law FirmPre-litigation automation
  • Caribbean ConglomerateDemand forecasting CoE
Case file · No. 01

Financial Services · Pension Fund

Equity Index Strategy Backtesting

Sector
Asset Management
Region
United States
Engagement
Implementation & Strategy
Duration
16 weeks

The challenge

A prominent pension fund was looking to optimize its investment strategies, particularly in equity index investments. They needed a robust way to evaluate potential strategies by backtesting them against historical data.

What we built

We developed a sophisticated web application specifically designed for backtesting equity index strategies. This application leveraged GenAI to process and analyze vast amounts of historical financial data.

Outcome

The backtesting web application revolutionized the pension fund's approach to strategy development and evaluation. Investment managers can now rapidly test and refine their ideas, leading to more robust and well-validated investment strategies.

Read more case files
What we do

Four practices,
one engagement model.

We work with leaders who’ve seen the cost of pilots that never shipped. Each practice can stand alone or compose — most engagements span at least two.

  1. AI Strategy

    Decide where AI belongs in your business — and where it doesn't.

    Executive-aligned roadmaps that distinguish AI projects worth funding from the ones that will quietly stall in production.

    • Opportunity assessment by line of business
    • Build-vs-buy framework, with vendor diligence
    • Risk, compliance, and data-readiness review
    • Three-horizon investment plan with ROI bands
    Engage on AI Strategy

  2. Implementation

    Move from pilot to production — without the 18-month plateau.

    We pair our engineers with your team to ship AI systems that integrate with real workflows, real data, and real users.

    • Reference architecture and stack selection
    • Custom agent and pipeline development
    • Evaluation harnesses, observability, guardrails
    • Handover with runbooks and on-call coverage
    Engage on Implementation

  3. Adoption

    Make sure the people who'll use it, will actually use it.

    The hardest part of an AI rollout isn't the model — it's the team change. We bring playbooks honed across Fortune 500 deployments.

    • Stakeholder alignment workshops
    • Communication and rollout plans
    • Training tailored by role and skill level
    • KPI dashboards tied to business outcomes
    Engage on Adoption

  4. Value Realization

    Tie AI spend to business outcomes you can defend to the board.

    Most AI investments lack a credible measurement framework. We build one — with the same rigor you'd apply to any capital decision.

    • Baseline measurement and uplift modeling
    • Cost-to-serve and unit-economics tracking
    • Quarterly value-realization reviews
    • Honest assessments — including when to stop
    Engage on Value Realization
How we work

A five-stage method,
calibrated to your readiness.

We’ve refined this sequence across Fortune 500 engagements. Stages overlap. Calendars shift. The discipline is in moving in order: discovery before plan, plan before commitment, commitment before scale.

  1. Stage I

    Weeks 1–3

    Executive Discovery

    We sit with your leadership and operators to map current state, surface real constraints, and identify where AI can move the needle — not where it can be retrofitted into a slide deck.

    • Current-state assessment
    • Executive alignment report
    • Strategic opportunity map

  2. Stage II

    Weeks 3–6

    Strategic Roadmapping

    A sequenced plan that ties each initiative to a business outcome, with honest risk and cost ranges. Compliance, data readiness, and build-vs-buy decided before commitments are made.

    • Strategic roadmap
    • Resource and cost requirements
    • Risk mitigation plan

  3. Stage III

    Weeks 5–8

    Stakeholder Alignment

    The work that determines whether AI projects survive their first quarter inside a real organization. Stakeholder maps, communication plans, the people who'll quietly block the rollout if no one engaged them.

    • Stakeholder matrix
    • Communication strategy
    • Change-management plan

  4. Stage IV

    3–6 months

    Phased Implementation

    We deploy in waves — highest-confidence, highest-impact first. Each wave is instrumented so the business can see the value compounding before the next commitment.

    • Implementation schedule
    • Success metrics framework
    • Progress reporting cadence

  5. Stage V

    Ongoing

    Value Realization

    After hand-off, we stay to validate the numbers the business uses to defend the investment. Real measurement, honest reviews, and explicit decisions about what to scale and what to retire.

    • ROI analysis dashboard
    • Performance optimization plan
    • Value realization review
Leadership

The people you’ll actually work with.

No partner-and-bait. Every engagement is led by one of the three of us, supported by the network when specialist expertise is required.

Christian Adib

Christian Adib

Founder & Managing Partner

01

Areas of focus

  • Enterprise AI strategy for Fortune 500 organizations
  • Executive advisory on AI implementation and value realization
  • Track record of delivering significant ROI through strategic AI initiatives
  • Speaker at global technology conferences and executive forums

With over a decade at the intersection of enterprise technology and business strategy, Christian has established himself as a trusted advisor to Fortune 500 executives navigating the complexities of AI transformation.

His distinctive approach combines deep technical acumen with executive-level strategic vision, enabling organizations to translate AI's potential into measurable business outcomes and sustainable competitive advantages.

Credentials

  • B.E. Mechanical Engineering — Lebanese American University
  • M.S. Mechanical Engineering — Columbia University
  • S.M. Civil & Environmental Engineering — MIT
  • M.B.A. — MIT Sloan School of Management
Bilal Bitar

Bilal Bitar

Co-Founder & Managing Partner

02

Areas of focus

  • Enterprise-wide transformation strategy and execution
  • Organizational alignment and change management
  • Financial modeling and value creation frameworks
  • Thought leadership in enterprise digital transformation

Bilal brings extensive experience in financial and strategic advisory, leading large teams through enterprise-wide transformation programs in organizations across banking, retail, and technology sectors.

By translating complex innovations into actionable strategies, Bilal helps organizations reimagine processes, unlock untapped potential for long-term growth and competitive advantage, and create tailored solutions that drive tangible outcomes.

Credentials

  • B.A. Economics & Political Science — American University of Beirut
  • M.B.A. — INSEAD
Cynthia Hajal, Ph.D.

Cynthia Hajal, Ph.D.

Chief Operating Officer

03

Areas of focus

  • Translating complex AI initiatives into scalable operational frameworks
  • Bridging technical capabilities with business objectives
  • Optimizing organizational processes for AI integration
  • Leading cutting-edge technical implementations

Cynthia brings a unique blend of technical expertise and operational excellence to Fulkerson Advisors, leveraging her deep background in complex systems engineering and data-driven decision making to optimize AI implementation strategies.

Her experience in developing sophisticated analytical models and managing cross-functional research teams translates directly to helping organizations navigate the complexities of AI integration and operational transformation.

Credentials

  • B.A. Economics & B.S. Mechanical Engineering — Columbia University
  • S.M. & Ph.D. Mechanical Engineering — MIT
  • Recognized as a Rising Star in Mechanical Engineering
Advisory board

Counsel from operators who’ve done it.

Carl Nehme, Ph.D.

Carl Nehme, Ph.D.

Technology, Product & Sales Advisor

Carl Nehme brings over 15 years of leadership experience at the intersection of healthcare, technology, and consumer innovation. He has successfully built and scaled cross-functional teams across product development, data science, operations, B2B/B2C sales and marketing, people, and finance.

Most recently, as co-founder of Goodpath, Carl led the development of the first virtual clinic model for chronic care, pioneering innovation that delivered industry-leading health outcomes and significant cost savings.

Prior to Goodpath, Carl spent six years at McKinsey & Company, working in the Dubai and Santiago offices, where he focused on driving operational excellence in healthcare and logistics. In 2014, Carl relocated to Boston to co-found an e-commerce augmented reality (AR) startup, which was acquired by Wayfair in 2016. Following the acquisition, Carl joined Wayfair's product leadership team, where he played a key role in introducing machine learning-driven personalization to enhance the shopping experience.

Areas of focus

  • Product strategy and ML-driven personalization
  • Healthcare and consumer technology innovation
  • Building and scaling cross-functional teams
  • B2B and B2C go-to-market strategy

Credentials

  • S.M. Aeronautical & Astronautical Engineering — MIT
  • Ph.D. Aeronautical & Astronautical Engineering — MIT
Expert network

Specialists on demand,
not on payroll.

Twenty-plus curated subject-matter experts we’ve collaborated with on production engagements. We deploy them when an engagement needs depth beyond what the core team carries.

AI / ML Scientists

PhD-level researchers and practitioners specializing in machine learning, deep learning, and neural networks. Engaged on novel research-grade implementation problems.

Data Architects

Enterprise data architecture experts with experience designing and implementing large-scale AI systems and the infrastructure they sit on.

Security Specialists

Information security experts focused on AI system security, data privacy, and compliance frameworks — including SOC 2, HIPAA, and FedRAMP environments.

Domain Experts

Industry veterans bringing deep expertise in financial services, healthcare, retail, and technology sectors. Engaged for sector-specific judgment calls and regulatory awareness.

Integration Engineers

Technical specialists in enterprise system integration, cloud infrastructure, and distributed systems. The people who make AI deployments survive contact with your existing stack.

Implementation Leaders

Experienced project leaders who have overseen successful enterprise AI transformations globally. Engaged when an initiative needs senior on-site discipline.

Case studies

Selected engagements.

  1. Legal Services

    Legal Interview & Document Automation

    The automation system successfully handles initial client interviews and generates accurate pre-litigation documentation, significantly reducing attorney time spent on routine t…

  2. Technology · Data Management

    SQL Chatbot for Enhanced Data Interactions

    The implementation of the SQL chatbot transformed the company's data interaction landscape.

  3. Retail

    Store Labor Planning & Optimization

    The system delivered significant improvements in store profitability through optimized labor allocation, enabling data-driven workforce planning while maintaining high service l…

  4. Education Technology

    AI-Powered Content Generation for EdTech

    The GenAI solution revolutionized the startup's content creation capabilities.

  5. Enterprise Software

    GenAI Strategy for Enterprise Software

    The GenAI strategy provided the startup with a clear direction for innovation and growth.

  6. Data Integration Services

    Unstructured Data Mapping Pipeline

    The implementation of this GenAI-powered pipeline transformed the company's data integration capabilities.

  7. Healthcare · Medical Devices

    LLM Agent for Medical Device Support

    The implementation of the LLM agent significantly enhanced the company's customer support capabilities.

  8. Executive Leadership Development

    AI-Powered Executive Coaching Platform

    The platform successfully extended the coach's methodology to a broader audience while maintaining the depth of his approach.

  9. Conglomerate · Retail

    Demand Forecasting Center of Excellence

    Successfully established a world-class demand forecasting operation staffed by trained local talent.

Discuss a similar engagement
The research desk

Ask the assistant
trained on our work.

A research aide grounded in our case files and published essays. Useful for orienting before a briefing — and an honest preview of how we deploy these systems inside client engagements.

Try asking

Specimen exchange

Dispatch · No. 014

What was the hardest part of shipping the legal interview agent?

Two things, in order. First, latency budget — attorneys won't tolerate more than ~1.5s between turns, so we had to constrain context, cache aggressively, and parallelize retrieval. Second, evaluation: legal interviews don't have a 'correct' transcript to compare against, so we built a rubric-based judge that scored coverage of required topics, gentleness of redirection, and document-prep readiness. The model work was unremarkable; the evaluation harness was the real product.

— Excerpted from a longer note — March 2026.

Notes from the field

Letters from clients and partners.

Christian created an AI-powered MTL WHAT-WHO-WHY Sandbox that far exceeded my expectations in record time. He quickly intuited my needs, iterated efficiently, and delivered a scalable, user-friendly online tool in just a few days. Everyone I've shown his work to has been blown away and requested ongoing access. His ability to transform ideas into impactful, practical solutions, coupled with exceptional follow-through and responsiveness, is unmatched in my 40 years of experience working with tech experts.

Peter DiGiammarinoFounder & Managing Partner, IntelliVen
“Working with Christian was a game-changer for our business. His deep understanding of AI technologies and their practical application helped us focus our initiatives and uncover new opportunities. The insights and strategies he provided were not only innovative but also tailored specifically to our needs.”
John WassCEO, Profit Isle
“Christian's technical expertise initially drew us in, but his strategic mindset, flexibility, humility, and commitment have made him irreplaceable. He combines rare technical mastery with genuine partnership — making him the kind of partner you wish you could hire full-time. His willingness to listen first and execute second means he truly understands my vision and the mission of the company.”
MarjorieCEO & Founder, ALEE
“I am a software architect who has been developing solutions for clients worldwide for over 40 years. I am particularly impressed with his ability to articulate solutions by quickly building demonstrable, working prototypes, and the way he works with and guides a team to iterate toward production quality code. The results we produce together continue to impress clients — I would give Christian my strongest recommendation.”
GHTechnology Partner & Software Architect
“We engaged Fulkerson Advisors to automate a proprietary model for tracking changes across S&P U.S. indexes. The team exceeded our expectations at every stage — from understanding our requirements to conducting statistical analysis, as well as designing and executing the solution. The project was delivered on time with exceptional quality and flawless functionality.”
SGChief Investment Officer, $55Bn US Pension Fund
“Christian is a go-to expert and a one-stop-shop for all things Generative AI considered. The AI domain changes wildly fast and Christian was able to distill our requirements to a remarkable set of discrete deliverables that demonstrated durable value capture.”
SPProduct Management Executive
Insights

Notes from our practice.

  1. ·Strategy

    Beyond the pilot: why most enterprise AI dies in the 18-month gap

    The gap between a working demo and a production system that survives contact with users, data drift, and budget review is where most AI initiatives quietly fail.

    Christian AdibMarch 20268 min

  2. ·Implementation

    What we learned shipping LLM agents into a Top-5 US law firm

    Notes from automating pre-litigation interviews at scale: latency budgets, evaluation harnesses, and the unglamorous instrumentation that decides whether attorneys actually use the system.

    Cynthia HajalFebruary 202611 min

  3. ·Advisory

    Twelve questions to ask before approving an AI roadmap

    A working diligence checklist drawn from the Fortune 500 engagements where AI initiatives stalled — and the smaller engagements where they didn't.

    Bilal BitarJanuary 20266 min

All essays
Colophon

Schedule a briefing.

Forty-five minutes with Christian, our founder. He’ll listen first. If your situation isn’t a fit for what we do, he’ll say so — and where useful, point you to who can help.

Format
45-minute video call
With
Christian Adib, Founder & Managing Partner
Audience
C-suite and senior decision-makers
Outcome
An honest read on whether and how we can help
Reserve a time

Or write to us directly at info@fulkersonadvisors.com.