Key Takeaways:
- 97% of life sciences companies are using or planning to use generative AI, but 74% struggle to turn it into real business value.
- Success depends on partners who stay involved, understand complex challenges, and keep supporting projects long-term.
- Custom tech that fits real needs and ongoing support are what keep things running in life sciences.
97% of life sciences companies are using or planning to use generative AI, according to SAS. Yet 74% admit they’re struggling to translate that into real business value, based on research from Boston Consulting Group.
That disconnect is pushing more companies to seek outside help.
When internal teams don’t have the time or specific expertise, custom tech can keep innovation moving.
In our interview, Clynt Taylor, General Manager of Kanda Software’s Healthcare and Life Sciences Division, shares how life sciences companies are turning to tailored solutions to solve complex problems and drive real growth.
Who Is Clynt Taylor?
Clynt Taylor is General Manager of Kanda Software’s Healthcare and Life Sciences Division, with over 35 years in healthcare technology. He’s led startups and growth-stage companies, driving innovation from early roles to executive leadership. He was CEO of Trapelo Health, an oncology decision support company acquired by NeoGenomics in 2021. He then served as president of NeoGenomics’ Informatics Division until 2023. Clynt co-founded and led Galvanon Healthcare Solutions, later acquired by NCR. He also held senior roles at NextGen, HealthVision, Eviti, and NantHealth. At NantHealth, he helped launch GPS Cancer — a first-of-its-kind test combining genome and transcriptome sequencing with proteomics for precision oncology. He began his career at IBM and has remained focused on using technology to solve complex healthcare challenges.
Editor's Note: This is a sponsored article created in partnership with Kanda Software.
Life sciences companies are sitting on mountains of data. And while there are off-the-shelf platforms to help store and manage it, the insatiable demand to extract its value requires sophisticated teams and innovative approaches. Clynt has seen this firsthand.
“Virtually every life sciences company is engaged in some data management initiative, and most are focused on leveraging the enormous capabilities of AI.
The business challenges may be different for each company, however, the sheer volume of data these companies must deal with across such large and diverse organizations creates a set of consistent and complex data challenges for all of them,” he says.
That is why Clynt has seen most leaders grappling with challenges like preprocessing, scalability, and accessibility that usually require custom software tools to solve.
AI Is Changing the Game, and Fast
One such tool is AI. Off-the-shelf systems often don’t meet the specific demands of regulated industries like life sciences, so to position themselves to realize the maximum long-term value of AI, companies are building custom-fit solutions.
For example, when Clynt’s team at Kanda helped one of the world’s largest pharma companies design and develop an innovative, ChatGPT-like AI solution for internal use, custom-fit was the way to go.
“The system quickly gained support and approval and is in the process of being rolled out company-wide,” he says.
That kind of success story doesn’t usually start with a fully equipped internal team.
Instead, Clynt notes that life sciences companies often turn to custom tech solutions when they need more manpower to take on new development projects or don’t have the needed specialized skill sets in-house.
That was the case when Kanda helped a global life sciences firm design an AI solution to automate the engineering requirements for a draft-to-finished-design process.
“The company’s own internal innovations team had spent several months grappling with the problem and trying to apply AI to solve it, but decided to reach out to Kanda for assistance,” Clynt explains.
Competency Isn’t a Buzzword. It’s the Difference.
As those real-world examples show, delivering custom AI solutions in life sciences isn’t just about technology.
According to Clynt, the defining factor in establishing long-term, trusted partnerships with life sciences companies is competency. Can the teams quickly understand complex problems, align with customers’ business goals, and deliver results on time and on budget?
“Although difficult to turn into a metric, it is certainly the most important quality needed to differentiate and to drive customer satisfaction,” he says.
“The ROI that can be realized by successfully delivering highly adoptable solutions on budget and on time is all part of competency. Miss just one of these areas and the project can stumble.”
Of course, competency isn’t just about meeting requirements. It’s what keeps projects from falling apart after launch, especially when it comes to custom software.
Custom software, particularly in life sciences, requires an ongoing process involving compliance, training, and system updates.
Because of this ongoing process, establishing a true partnership with your agency matters.
“Kanda has assembled a highly experienced team of software development leaders and technologists, led by former CEOs and CTOs who were once customers of Kanda and who bring very relevant perspectives to each client relationship,” Clynt explains.
On top of that, Kanda structured its organization and contracts to provide continuous support to projects before, during, and after software development. Doing so builds trust and helps establish long-term relationships.
Why Long-Term Partnership Beats One-and-Done Deals
As Clynt puts it, long-term involvement, experience, competency, and costs separate trusted partners from vendors.
When outsourcing software development, he cautions against some major red flags:
- Vendors who over-promise results to win business
- Vendors who submit low bids to attract customers
This often leads to project failure and wasted time and resources for the customer.
The real challenge isn’t just delivering a solution, it’s maintaining momentum. Projects need partners who can adapt and support changing requirements over time.
“I admire any company that does great work, becomes a trusted extension of the company’s own team, and holds itself accountable for its actions, and we strive for that at Kanda,” Clynt says.
In life sciences, success means more than just delivery. Compliance, training, and updates never stop.
If your partner can’t handle the full lifecycle, you’re already behind.