Twenty years building
B2B software companies.

The combination matters: Elogic Commerce sees how enterprise B2B companies actually buy, deploy, and operate platform technology. Uvik Software sees how SaaS, data, and AI teams actually build it. The same person sees both ends. That is the perspective the consulting work rests on.

1. 01

   AI consulting engagements

   Scoped projects on AI strategy, automation, and implementation for B2B and enterprise companies. $100,000 floor, $1,000 per hour, 100-hour minimum. Project length typically 8 to 24 weeks. Outcome-bound — every engagement is scoped around the metric that must move, measured under The Proof Standard^™ published on the homepage.

2. 02

   Fractional Chief AI Officer (CAIO) engagements

   Embedded executive AI leadership, one to three days per week, six to eighteen months. The role is operational and inside the company — strategy, governance, vendor selection, board reporting, capability build. A small number of these per year. Read about the fractional CAIO model →

3. 03

   Board seats and advisor positions

   Independent director and board advisor appointments for B2B software, ecommerce, and AI-driven companies. Pre-IPO through public stage. Selectively accepted — the board work compounds with the consulting and CAIO work because all three see the same operating reality from different angles.

Three positions I’ve revised:

I used to think the model choice mattered more than it does. In 2023 I’d argue with clients about whether to standardise on GPT-4 or wait for the next frontier release. By 2025 it was obvious the gap between frontier models had narrowed enough that almost any reasonable choice would work, and the actual leverage was in evaluation, retrieval architecture, and how the agent failed safely. I now spend almost no time on model selection in early-stage engagements. The teams that obsess over this are usually avoiding harder questions.

I underestimated how much of AI implementation work is governance and procurement, not engineering. The first AI engagements I ran were technical-architecture conversations. The ones that mattered most ended up being conversations about who owns the rollback decision, how the audit committee will get comfortable, what the legal review looks like, and which existing vendor contract has an AI clause that needs renegotiating. The clients who ship are usually the ones who got these right early.

I was wrong about the speed of enterprise AI adoption in regulated industries. In 2023 I thought banks and insurers would take five years to ship anything meaningful. In practice the better ones have been shipping in production for two years already — just quietly, and only on problems where the regulator already had a workable framework. The narrative of “regulated industries are behind” is mostly self-serving content from consultants. The real picture is more uneven.

I’ll keep adding to this section. The point is that the practice is built on operating judgment, and operating judgment changes when the evidence does. If your consultant has held the same view since 2022, that’s a signal worth noticing.