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Work

Selected engagements

  1. Defining the M1 Layer
  2. A deployment model for private AI
  3. Data readiness before an AI commitment
  4. Repositioning a strong product sold as a commodity

01

Defining the M1 Layer.

Enterprises hold years of owned operational data they cannot safely or usefully connect to AI. The market answers with point tools; nobody owns the progression from raw data to operational intelligence.

  1. Defined TacTech's category position: data mobilization and intelligence infrastructure, not AI services.

  2. Designed the M1 Layer, the framework that moves owned data through conditioning and governance into operational delivery.

  3. Built the engagement model around the framework so every client project strengthens the same architecture.

The M1 Layer now defines TacTech's product architecture, its engagement structure, and the language the company sells with.

02

Zynolabs logo

Vice President & CTO

2025

A deployment model for private AI

Organizations with real privacy, regulatory, or dependency constraints are told the only path to AI runs through public platforms. For many of them, that path is disqualifying.

  • Set Zynolabs' technical direction: controlled AI systems that organizations own and operate.
  • Defined the deployment model spanning on-premise and private environments, with access control treated as a first-class design constraint.
  • Positioned the company against platform dependency rather than against other AI vendors.

Zynolabs operates with a clear mandate: intelligence for organizations that cannot, or should not, surrender operational control.

In preparation

Advisory case studies are published only with client approval. These two are drafted and awaiting release; the shape of each problem is real, the identities stay sealed.

03

Case study in preparation

Data readiness before an AI commitment

Client
Client confidential
Industry
Established service business
Role
Strategic Advisor

An established operator preparing a significant AI investment without a clear picture of what its data could actually support.

  • Reviewed the data estate against the intended AI use cases.
  • Sequenced readiness work ahead of any model or vendor commitment.
  • Reframed the initiative from an AI purchase into an owned-infrastructure decision.

04

Case study in preparation

Repositioning a strong product sold as a commodity

Client
Client confidential
Industry
B2B software
Role
Strategic Advisor

A technically strong product losing deals on price because it was positioned inside a category it should never have competed in.

  • Analyzed the category the product was being compared against.
  • Rebuilt the positioning around the problem the product uniquely resolves.
  • Restructured the offer architecture to match the new position.

On confidential work

Most advisory work involves information clients would not want published, so most of it will never appear here in full. What is written here is accurate or it is absent.

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