Skip to content
Ripoll Digital
Book a call
Ripoll Digital
504-920-9436ripoll.digital@gmail.com

Founded in New Orleans

Book a call

About

The two people you will actually work with.

Ripoll Digital Strategy & Technology is a technology and digital strategy consultancy founded in New Orleans by two Princeton computer science graduates. We work with owners and leaders of small and mid-sized businesses, in any industry, who want a straight answer and something that works.
Book a consultationRequest a quote
Education
Princeton Computer Science
Founded in
New Orleans
We work with
Businesses in any industry, nationwide

The founders

01

Portrait of Alfred Ripoll

Alfred Ripoll

Co-founder, Strategy and Financial Analytics

Alfred Ripoll leads our strategy and financial analytics work. A New Orleans native, Alfred holds a Princeton degree in computer science with a minor in finance. As a finance and risk analyst at Finance New Orleans, Alfred works on bond policy, underwriting standards and the credit and repayment risk of bond-financed projects. As a FINRA-registered representative and financial research analyst at 1964 Global, Alfred builds return and economic-impact models for major public projects, including the Morial Convention Center. Earlier marketing work for the Boston Red Sox and Mercedes-Benz USA keeps the focus on what moves a business. You get the numbers, the risks around them and a plain recommendation.

Background

Education
Princeton University, A.B. Computer Science, minor in Finance
Roles
Finance and risk analyst, Finance New Orleans. Registered representative and financial research analyst, 1964 Global LLC.
Licensing
FINRA Series 7, General Securities Representative
Also
Research and engagement associate, Keith Butler Foundation. Treasurer, New Orleans Youth Development Organization. Founder, Renaissance Productions.
Earlier
Marketing intern, Boston Red Sox. Retail sales and training intern, Mercedes-Benz USA.
Domains
Public finance, credit and risk analysis, investment research, marketing strategy

Contact

Alfred Ripoll on LinkedIn

02

Portrait of Caple Spence

Caple Spence

Co-founder, Technology and Products

Caple Spence leads our technology and product work. A Princeton computer science graduate, Caple is chief technology officer of ARMITA, which builds AI software that helps spinal surgeons plan operations from CT, MRI and X-ray scans, and heads research and development at MedAiCon, an AI assistant that answers patients' questions and guides them to the right care. Healthcare sets a high bar: software must be secure, tested with the people who use it, and careful about what it should never claim. Every website, app and AI assistant we build is held to that standard, backed by earlier work on AI search systems and drug-discovery research.

Background

Education
Princeton University, A.B. Computer Science
Roles
Chief technology officer, ARMITA. Head of research and development, MedAiCon.
Earlier
AI and machine learning engineer, Vast Vertex Media. Undergraduate researcher, University of Oklahoma Data Science and Analytics Institute.
Domains
Medical imaging, healthcare AI, AI search and retrieval, full-stack engineering

Contact

Caple Spence on LinkedIn

What we bring

Careful analysis, real engineering, and a head for business.

Between us we have worked across eight fields. Here is what each one means for you.

Analytical rigor

We check the numbers before we trust them, and we show you how we reached an answer.

  • Analytics

    We turn your records into a clear picture of what is working and what is not.

  • Fintech research

    Financial work teaches care. Small errors cost real money, so every figure gets checked.

  • Data algorithm development

    When a rule of thumb stops working, we build a method that can be tested and explained.

Technical depth

We write the software ourselves, so our advice comes from having done the work.

  • Full-stack software engineering

    We build the whole product, from the screen your customer sees to the systems behind it.

  • Med-tech

    Medical technology is unforgiving. That experience shapes how we test anything people rely on.

  • AI ethics

    Before an AI tool reaches your customers, we ask who it affects and what happens when it is wrong.

Business-oriented execution

A project only counts if it helps the business. We keep cost, time and results in view.

  • AI consulting

    We help you find where AI earns its cost, and we say so plainly when it does not.

  • CTO experience

    We have weighed budgets, hiring and risk as well as the technical choices, so we know what a leader has to balance.

Selected work

The kinds of project we take on.

These are samples of our work, and each one is marked as such. Real case studies will take their place as clients agree to share results.

SampleDigital Products

A website rebuild for a professional services firm

Problem
The old site looked dated, was hard to use on a phone, and rarely led to a call.
What we did
Rewrote the pages around what customers ask first, built a faster site, and put the phone number one tap away.
Result
[Result to confirm: change in calls and enquiries per month]

SampleDigital Products

An AI assistant for routine customer questions

Problem
Staff spent much of the day answering the same questions by phone and email.
What we did
Trained an assistant on the company's own documents, set firm limits on what it may answer, and sent everything else to a person.
Result
[Result to confirm: hours saved per week]

SampleAdvisory & Consulting

Part-time technology leadership for a growing company

Problem
The owners faced large software decisions but did not need a full-time technology executive.
What we did
Served as a fractional CTO, reviewed vendors and contracts, set a one-year plan, and trained staff on AI.
Result
[Result to confirm: annual software cost avoided]

SampleAnalytics, Research & Intelligence

A market and pricing study before an expansion

Problem
Leadership had to decide whether to enter a new market, with strong opinions and little evidence.
What we did
Gathered market and financial data, built a simple model of the likely outcomes, and wrote a recommendation with the reasoning shown.
Result
[Result to confirm: decision taken and its outcome]

Values and approach

What you can expect from us.

If a spreadsheet will do the job, we will say so.

  1. Plain words.

    If we cannot explain it simply, it is not ready for you.

  2. The decision comes first.

    We start with what you have to decide, then look for what bears on it.

  3. Show the reasoning.

    Every recommendation comes with its evidence, so you can question it.

  4. Small before large.

    We prove an idea cheaply before asking you to pay for the big version.

  5. Leave you able.

    We write things down and train your people, so you do not depend on us.

Prefer to talk it through?

504-920-9436ripoll.digital@gmail.com
Book a call