Vixul Inc

We help tech services founders stop trading time and start building equity.

Vixul installs the positioning, pipeline, and AI-first systems that turn your firm into a stronger, more valuable business.

09/18/2026

AI deployments have a data readiness problem, and it's one of the biggest predictors of whether the project will survive.

Gartner predicts that through 2026, organizations will abandon 60% of AI projects that lack AI-ready data. Turns out, data that is fragmented, ungoverned, and hard to trust isn't a great starting point for a system. (Yes, we know. What a shocker.)

Informatica's 2025 CDO survey echoed this as well: data quality and readiness was cited as the number-one obstacle to AI adoption, named by 43% of data leaders.

But getting data ready for an AI system isn't just a cleanup task. It's a governance practice. Someone has to own it, define what a given use case actually needs, and build the accountability before a pipeline can use it.

Which is the good news for tech services firms. Data governance needs, systems integration, and organizational discipline are the kind of landscape where tech services firms already shine.

What's your organization doing to help clients get their data AI-ready?

09/11/2026

ROI has to show up on both sides of the equation before an engagement counts as successful and sustainable. The pattern we keep seeing in services firms early in their AI transition is signals tracked on one side only, either theirs or the client's.

When your clients' time-to-value collapses thanks to AI, your effort per deliverable should be falling too. When clients get a number they can defend internally, your gross margin on that account should hold or rise too. And when AI-native delivery enables them to expand a scope without opening a new procurement cycle, your revenue on that account should also be able to grow faster than your headcount.

Proving value shouldn't cost you value.

We made a version of this argument back in 2023 when we said the same measurement that proves value to the client is what earns the next engagement.

What makes the Service-as-Software model real is when one mechanism does both jobs: the thing that makes delivery cheaper for you should be the thing that makes the outcome better for them.

On your last engagement, did both sides move?

09/09/2026

Your enterprise clients' new primary ROI metric is P&L impact.

Futurum's survey of 830 IT decision makers found that direct financial impact, combining revenue growth and profitability, is now the leading ROI metric. Clients are no longer as interested in hours saved, unless you can also show them dollars saved.

When you think about it, that makes sense. This shift is the client-side equivalent of what we've already talked about on the delivery side, where hours and revenue no longer neatly line up. When AI makes speed virtually a given, what still remains unclear (and what your clients still need to justify internally) is whether this speed actually raises the bottom line or not.

Which means if you're still building your case studies and testimonials around hours, you may no longer be on the same page as your clients. To make sure you're not blindsided by that, agree on a financial number or ROI metric to measure before you build or deploy.

When ROI is a financial metric, who do you think should own it at kickoff?

09/08/2026

9 months into the year that Service-as-Software (SaS) went from idea to reality, we're ready to take a look at the evidence. This month's theme is Proof Over Promise: Case studies, ROI, and the Data Behind the Thesis.

We're focusing on what ROI looks like for customers who invest in AI, success stories in SaS, lessons to learn from failures, and which trends hold true across deployments.

So: what's the strongest data point you have on an AI-native engagement?

Don't forget to sign up for this month's roundtable! 📅 RSVP now open 👇
https://www.linkedin.com/events/7496651967864205313

09/03/2026

Saying you bootstrapped your own company definitely feeds your ego as an entrepreneur, but it doesn't necessarily feed your company. Every ambitious play waits for margins to catch up before you can risk it. You may end up saving for years to make the decisions you need to make *right now*.

Yet, taking a check doesn't solve all your problems either. It can buy you a faster timeline, but it also buys someone else a seat at the table. And let's admit it: as founders, that pinches us. We're used to running our own show, our own way, right?

Wrong. Maturity as an entrepreneur doesn't come from resisting change even at the cost of doing good business. It comes from understanding what your boundaries are.

For Bilal Zafar, Co-founder & CEO of 10xEngineers, that boundary looks like this:

"We told our investors: 'Here's the purpose, here's why we're building this. We did not promise, and we will not change, the purpose of the company.'"

Founders who raise equity and manage that transition successfully do one unglamorous thing early: they write down what won't change, and put it in front of the investor before signing.

At the end of the day, there's no one right call to make regarding bootstrapping vs raising investment. The thing that makes sense is the one that makes sense for the business, and what gets you there is the ability to have a hard but honest conversation with your investors, and maybe with yourself.

What would you choose?

09/02/2026

"Invest in AI, or preserve cash?" If you're asking yourself that question, you're asking yourself the wrong question.

For most tech services firms, the AI investment already exists. It's not rolling back. But what matters is what it buys.

Bilal Zafar, co-founder and CEO of 10xEngineers, plans AI investment based on its outcome, not category:

"Will we invest in AI?" is too broad. It's like saying, "Will we invest in people?" Of course we'll invest in people. Of course we'll invest in better automation...I'm more focused on what exactly will we do with those tools that essentially helps us de-risk our core business, as this flood wipes out a lot of service work. It's not a matter of taking the revenue and investing it back into AI. It's taking that revenue and building deeper, larger moats that help us stay immune and hopefully become even more profitable."

Preserving cash keeps your options open. But the right kind of investment plugs leaks and deepens your moat, protecting your business from the competition.

08/27/2026

...That's a lotta zeros. A digital engineering firm already posted over $105 million in AI-native work in a single quarter, with a target of $600 million-plus for 2026.

Back in April, on the VixulCon stage we shared how all signs point to a new era in tech services. One where speed stops being a differentiator, and the real premium goes to whoever can prove they can be trusted with what gets built.

The category is growing alongside the agentic AI market itself. Four months later, AI-first tech services firms are showing us the prediction still holds true. And then some.

08/19/2026

There are two different conversations happening these days. In one, a client asks why a project that takes less time than it used to still costs the same. In the other, a client has a project they couldn't afford to get done a few years ago but now think might be possible now with your help (and that of AI).

The first is an example of the perception tax we've talked about before. Since clients can't assess AI with the same degree of experience, they tend to underestimate the value of AI-powered work.

But the second scenario is where an opportunity exists: when a technology is becomes cheaper and faster to deliver, demand for it explodes and so does the money spent on it. It expands to potentially power everything that used to be out of reach, and in doing so it creates new market demand.

Join us tomorrow for The Money Conversation, a roundtable where we'll do a deep dive into the pricing, margin, and unit economics of Service-as-Software. 10am Central, online.

08/14/2026

Hourly billing puts a hard limit on margin. But when fees are tied to outcomes, margin scales with value instead of time.

The behemoths of the consulting industry already know that. About 25% of McKinsey's global fees now come from outcome-based arrangements instead of billable hours and its global AI and technology leader, Kate Smaje, has said outcome-based pricing suits the kind of AI-driven transformation work clients are asking for now.

That means McKinsey is restructuring its own revenue around exactly the kind of shift Vixul is talking about.

Aater Suleman, PhD. describes it this way:

"In the old model, a custom request was a cost. Every deviation from standard ate margin. In the AI-native model, customization is the leverage point: the system absorbs the repeatable part, your best people get paid for the judgment call it can't make."

That's the AI margin case in one sentence: decouple the price from the hour, and cheaper delivery costs for routine work can translate into bigger margins for the work that requires judgment.

08/13/2026

A 2026 SegmentOS pricing test found that renaming the exact same product "AI-powered" cut buyers' willingness to pay by roughly 25%. While the research focused on a consumer product, there's still an invisible perception tax to AI-powered work. This can hold founders back despite the margins AI offers on the delivery side.

As Vixul's Aater Suleman, PhD. puts it:

"Buyers don't announce their assumptions, they just act on them. The same instinct that makes a prospect ask 'can you just sell me the tool' is the instinct that caps what they'll pay for judgment. If they think AI did the work, they think the work was cheap."

How do you get a client to sign on to your pricing when the moment they hear "AI" they assume it should be cheaper? That's one of the questions we'll tackle at this month's roundtable, happening August 20th at 10 AM Central.

RSVP: 📌 https://www.linkedin.com/events/7488956472786108416

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