CTO2.0A MAXIOM VENTUREMaxiom TechnologyBook a time →
When someone says add AI

AI strategy for product teams

A named fractional CTO picks the one or two uses worth doing. You get guardrails, a named owner, and a pilot with a clear success check. The rest gets a no.

Who it's for

For leaders who are being told to add AI.

Founders whose board or investors want an AI plan

Product leaders with a list of AI ideas and no owner

Teams asked to put a chatbot or an assistant in the product

Operators who need a written no, not another experiment

What we hear

Everyone has an AI idea. Nobody owns the decision.

"The board asked for our AI strategy. I have a list of ideas and no decision."

Founder, B2B software

"We could add AI in six places. I do not know which one is worth the risk."

VP Product, SaaS

"Someone wants a chatbot on the site. Nobody has said what it is for."

Head of product, marketplace

"If this answers wrong, I cannot tell you who owns it."

COO, software

CTO 2.0 puts one named CTO on that decision. You get one or two uses, guardrails, an owner on your team, and a no for the rest.

What we do

What the CTO writes down.

The first 90 days

Pick, guard, pilot.

Each phase ends with documents you keep, whether or not you keep us.

Days 1 to 3001

Pick

NDA first, then read-only access. We read the product, the data, and the AI ideas already on the table.

  • Which ideas touch customer data
  • Where a use would change the product people already have
  • One or two to pilot, and the rest parked in writing
Days 31 to 6002

Guard

We write the guardrails and name the owner before anyone builds.

  • What data the pilot may use, and what stays out
  • Who on your team owns the pilot
  • The success check, written before the pilot starts
Days 61 to 9003

Pilot

The pilot runs against that check. You get a written call to continue, change, or stop.

  • The pilot, scoped to the uses you kept
  • The success check, scored in plain language
  • A decision you can hand a board: keep going, or stop
NDA before accessSigned before anyone sees a repository, an environment, or customer data.
Read-only by defaultWrite access only when you grant it, for a named task.
Your data stays with youThe pilot runs in your environment, on data you approve.
A written noUses that miss the success check do not get a second pilot unless you ask.
Proof from the Maxiom record

Work the team has already shipped.

smileMLPrivacy-first AI

Emotion recognition with a hard limit on the data

smileML uses emotion recognition to help people understand each other in video calls and face-to-face meetings. Maxiom built the product and staffed the team. The model runs on the device. Video and images are analyzed locally and are never sent to the cloud. SaleSpot, smileML's sales analytics tool, reads sentiment and body language during video calls. The stack includes Python and TensorFlow. The limit was part of the product: meeting video could not leave the device. This page is a fractional CTO who picks which AI uses are worth a pilot, sets guardrails, and names an owner. The smileML work was a product build. It was not this engagement.

Python · TensorFlow · On-device
Read the case study
Who the CTOs are

Three CTOs. One engineering team behind them.

Antonio Chagoury

Antonio Chagoury

Founder and CEO, Maxiom
Enterprise software and healthcare AI
Microsoft MVP20+ years
  • Founded and runs Maxiom, building software since 2002
  • Built software for AABB, the blood and biotherapies association
  • Built the Rezeo AI video resume platform
  • Published on software architecture
Washington DC-Baltimore Area
Gaurav Bagul

Gaurav Bagul

CTO, Maxiom Technology
Healthcare and AI SaaS
AWS Certified Security Specialist15+ years
  • Leads engineering as CTO of Maxiom Technology
  • Builds HIPAA and GDPR compliant digital health products
  • Platforms serving clients in the USA, UK, and Europe
  • Cloud on AWS, Kubernetes, and Terraform
Pune, India and Austin, TX

Nik Kalyani

Fractional CTO
Zero-to-one platforms and protocol architecture
Founder25+ years
  • Founder of Xibit and Vitruveo
  • Hands-on architect of L1 and L2 protocols and production smart contracts
  • Scaled systems across distributed teams for 25+ years
  • Zero-to-one product development
California

When a review needs more hands, Maxiom engineers in Ashburn, VA do the work under your CTO's direction. Same standards, same owner.

Meet Maxiom
FAQ

Straight answers.

Will you tell us not to add AI?

Yes, when that is the honest answer. Most ideas do not get a pilot. You get a written no, and one or two uses that are worth a success check.

Do you build the model?

This page is the decision, the guardrails, and the pilot. Maxiom also builds AI products. The smileML case study on this page is one of those builds: emotion recognition that runs on the device, so video never goes to the cloud. If you want a build, say so on the call.

What is the success check?

A check written before the pilot starts, in language a product owner can score. It says what the pilot has to do, which data it may use, and who owns a bad answer.

Do you certify the model or our compliance?

No. We are not auditors. We do not certify security, models, or compliance. You get the guardrails, the owner, and the written result of the pilot. If the data is protected health information, start at https://cto20.com/healthcare-cto.

How is this different from the other CTO 2.0 pages?

A healthcare CTO owns PHI, BAAs, and EHR calls. HIPAA readiness is a gap list before a questionnaire. Oversight reviews an outsourced team that is already shipping. Launch readiness is a checklist before the first users. Technical due diligence is a read before a deal or a raise. A stalled project review is for a build that is late, over budget, or stuck. That page is at https://cto20.com/rescue-a-stalled-software-project. This page is for the pressure to add AI: which uses get a pilot, who owns them, and which ones get a no.

How do we start?

Book a time. It is a 30-minute call about the AI ideas on the table, the data they would touch, and who is asking. You get a clear yes or no on fit.

Also on CTO 2.0
30 minutes

Tell us which AI ideas are on the table.

The product, the data those ideas would touch, and who is asking. You leave with a clear yes or no.

Book a time →