AI is a journey

There’s a view I come across often, usually shared with a half-smile or raised eyebrow, that when an AI company starts offering consulting, it must be a sign the product didn’t quite land. That the tech fell short, so now it’s teams of people being sent in to pick up the slack.

I understand where that perception comes from. Some platforms have promised more than they could deliver. In a race to be first, products shipped before they were ready. What was meant to be transformative ends up looking like a consulting service in disguise: slide decks, workshops, endless hand-holding. It’s frustrating. But in healthcare, I think that interpretation misses something essential.

At VISFO, we don’t offer consulting because our tech is weak. We offer it because the systems our partners work within are strong. And the stakes are high. These are people navigating complex regulatory environments, designing evidence strategies, and making decisions that shape real-world outcomes for patients. The work isn’t easy, and that’s exactly why it deserves something better than an off-the-shelf solution.

AI doesn’t plug into complexity. It needs to understand it

There’s a persistent idea in tech that you can drop a model into any business and expect results, like flipping a switch. But in pharma and health tech, that rarely works.

Our clients aren’t looking for quick fixes. They’re deep domain experts, operating in layered, audited, legacy-rich ecosystems where every change has a ripple effect. These workflows aren’t broken. They’re shaped by years of expertise, regulation, and necessary caution.

So no, you can’t just plug in a model and expect magic. Not because the technology isn’t powerful, but because the context it’s entering is deliberate, specialised, and rightly sceptical of change for change’s sake.

That’s why we co-design. Always. We don’t show up with a pre-built solution and hope it fits. We start by understanding the lived realities of the teams we work with. How they make decisions. Where friction really lies. What good looks like in practice, not just in theory. We don’t build around people. We build with them.

This approach isn’t something we tack on. It is the product strategy.

The work before the work is what makes the product stick

We’ve taken this approach consistently, from SAIV, where we collaborated with critical care teams to build a predictive tool they could trust at the bedside, to HelixAI, where we embedded ourselves in the daily reality of evidence teams. When we sit beside users, running reviews together, observing how people filter, align, and structure their outputs, we’re not just helping them get through the work.

We’re shaping what the future version of that work could be. One that is less fragmented, less repetitive, more aligned.

I was talking about this recently with a colleague, and I appreciated his perspective. He said, “AI can be anything. That’s a blessing and a curse. Transformation, by its nature, is getting people aligned to do the right things in the right way. That was already hard before AI gave us limitless possibilities. AI made this harder, and that’s exactly what created the need for consulting.”

He’s right. The more powerful the tool, the more responsibility we have to make sure it lands well. That people can use it, trust it, shape it. That it fits into the systems that already support good work, and helps lift them, not replace them.

What we build has to stick, not just ship

Avoiding consulting might look cleaner on paper. But if it means ignoring what teams really need to make progress, that’s a bigger failure.

When we run literature reviews or evidence extractions alongside our clients, we’re not just helping them meet a deadline. We’re learning. We’re testing what works, surfacing edge cases, and designing for scale. That shared experience becomes a reusable knowledge asset, one that feeds directly into the product.

So by the time we deliver the software version, it already reflects the way our clients think. The filters, the templates, the outputs, they’re not just user-friendly, they’re user-shaped. Because the people who use the tools helped shape the logic behind them.

There’s nothing wrong with building tools that work out of the box. But in healthcare, speed without context leads to rework. AI without alignment adds noise. And that’s not the future we’re building toward.

The transformation our clients want, faster insights, consistent outputs, stronger collaboration across portfolios, doesn’t come from a single clever tool. It comes from systems that reflect how people actually work, and support them in doing it better.

So yes, we consult. Not to patch gaps in the tech, but to build something meaningful from the start. Real change takes time, trust, and care.

And in healthcare, that’s not a weakness. That’s how things move forward.