In the age of rapidly advancing AI and a job market increasingly impacted by technology, innovation is the baseline to compete.
And it’s not just the market that is hungry for innovation; employees are eager to be on innovative teams, too. Being a part of a team where employees can see the impact of their work directly supports employee satisfaction and well-being — which is why Built In spoke with six tech professionals who were eager to share how the innovation at their company has impacted their team’s — and their customers’ — well-being.
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The Farmer’s Dog is a pet health and nutrition company that delivers healthy food options for pet owners.
How does innovation show up in your company culture?
Innovation at The Farmer’s Dog starts with a low barrier to putting ideas on the table. If you have something to propose, the path is simple: Write it up and share it. We have a public engineering channel where design docs and proposals flow constantly. The goal is fast calibration and getting feedback from people you might not naturally talk to, so decisions don’t happen in silos.
What I’m most proud of is that technical alignment doesn’t depend on hierarchy. With a clear, shared vision, our teams align pragmatically and refine ideas in the open.
On the AI front, we’re intentional. We use AI for code generation, automated code review and design briefs. We’ve also enabled our product and design teams to generate prototypes with AI tools, creating a tighter partnership between engineering and the rest of the org. The expectation isn’t just “use AI.” The goal is for people to understand its capabilities and make informed decisions about where it adds value. That intentionality is what makes it stick.
What’s one recent innovation that improved user or employee experience?
We’ve invested in developer experience this year and it shows. Our CI/CD pipeline supports 300 to 400 deploys a week, with more than 100 on a busy day. That speed isn’t chaos — it’s the result of a reliable, well-managed system that lets engineers ship quickly and confidently.
We’ve also overhauled onboarding. Getting a new engineer’s local environment up and running used to take eight separate setup commands and a lot of documentation-hunting. We collapsed that down to a single command. We streamlined the supporting docs and built tooling that pulls directly from our internal knowledge base to get new hires productive faster, including onboarding to our AI workflows.
We believe that when engineers spend less time fighting tooling and more time building, the customer benefits downstream. Fast, reliable deploys mean we can iterate quickly and ship fixes the same day we find them.
How do you balance experimentation with stability?
We set ourselves up to move quickly, which means investing just as much in guardrails as we do in velocity. Our releases ship with monitoring that alerts our on-call engineers directly. Major changes go through release documents, ship behind feature flags and often run in shadow mode so we can validate consistency before customers see anything. If something goes wrong, we can roll back fast.
After incidents, we run reviews to understand what happened. The goal is to close the loop every time, turning what we learn from launches, bugs and code review into process improvements. We apply the same thinking to our AI workflows, rolling learnings back into our agents and tooling to catch similar issues going forward.
The piece that ties it together is making sure our people are growing alongside the tools. As we adopt AI across engineering, we want engineers actively engaging with their work, understanding the changes being made and using AI as a way to learn, not just to produce output. Experimentation works when the team is equipped to learn from what it ships.
AKASA leverages generative AI to make managing the healthcare revenue cycle more efficient.
How does innovation show up in your company culture?
Innovation shows up in how quickly we test ideas and how closely we work with our users, every day. We move quickly, but we don’t innovate in isolation. We prototype, test and get feedback on new ideas, which makes us able to constantly innovate and try new things. That feedback loop with our internal experts and customers is constant and shows how iteration is also a big part of our culture and supports innovation. We also don’t sit on concepts for months trying to perfect them in isolation. If we see an opportunity to improve a workflow or apply AI in a smarter way, we prototype it, put it in front of internal subject matter experts first, then customers. Their feedback shapes what happens next. Our AI models are continuously improving based on real-world usage and customer input. Since our AI models evolve based on real-world usage, our product experience improves because we’re listening closely to the people who use it. Users often notice the changes and they appreciate that we’re responsive.
While we’re pushing forward with automation and AI, we’re always thinking about how technology supports humans and enhances their expertise instead of trying to replace them.
What’s one recent innovation that improved user or employee experience?
One example I’m really proud of is our Clinical Documentation Dashboard.
Clinical documentation specialists traditionally have to navigate across multiple parts of the EHR to piece together the information they need. It’s time-consuming and cognitively heavy. We reimagined that workflow by consolidating relevant patient data into a single, intuitive view.
But the real innovation wasn’t just the dashboard itself, it was how we built it. We stepped back and asked: What would this look like if it were designed around how specialists naturally think and work? We studied how users review cases, created prototypes before writing production code and incorporated feedback early and often. By the time it launched, it reflected real user workflows.
The response has been strong because users immediately recognize that it was designed around their needs. It reduces friction, saves time and makes their work more efficient, which is ultimately what good AI-powered design should do.
How do you balance experimentation with stability?
In healthcare, we can’t build from assumptions and trust is everything. Our work has real-world consequences and we’re working in high-stakes environments, so experimentation has to be responsible.
For new features, we start with tools like Figma to test ideas and gather feedback before engineering invests heavily in them, then build in layers of validation before anything goes live broadly. We also use those validations to test concepts before they reach production, which allows us to iterate quickly without disrupting live workflows. We maintain a rapid release cadence but ground those releases in testing and validation.
We’re very deliberate in training models on historical data, validating performance and rolling new capabilities out through pilot programs with a small group of customers before scaling more broadly. That gives us the opportunity to identify edge cases and refine the system.
For me, it’s not about slowing down innovation, but building the right guardrails so we can move fast with confidence. Experimentation and stability aren’t opposites and when done well, they reinforce each other.
Grow Therapy is a healthtech company that helps independent therapists launch and grow in-network private practices through software that assists with credentialing, referrals, billing, insurance claims and more.
How does innovation show up in your company culture?
At Grow, innovation starts with imagination — but it’s grounded in data, research and real-world outcomes.
Each year, we build our “concept car” — a bold, future-state prototype of where our product and experience should be 12 to 18 months from now. It’s not incremental. It’s intentionally boundary-pushing. We synthesize provider and client research, marketplace data, behavioral insights and category trends. Then we ask: If we were building this from scratch today, what would “best in the world” look like? Not just best in health tech, but the best, period.
That vision sets our strategy. We don’t want to be compared to other healthcare platforms; we hold ourselves to the standard of the most loved consumer brands.
Innovation also shows up in how we execute. Engineers shape strategy. Designers influence systems architecture. Product pushes for craft. We all shape strategy and outcomes. We challenge the status quo in how we build, not just what we build — constantly evolving our operating model to move faster, raise the bar and deliver experiences that feel modern, intuitive and trustworthy.
In healthcare, that kind of ambition matters. Access to care deserves nothing less.
What’s one recent innovation that improved user or employee experience?
One recent innovation I’m especially proud of is how we reimagined our marketplace experience.
Mental healthcare is deeply personal. Choosing a provider isn’t a transactional decision. We asked ourselves: How do we make it genuinely easy to book, while also honoring the human connection at the center of care? And how do we showcase providers in a way that reflects who they really are and not just a list of credentials?
We started with bold end-state concepts: What would it look like if finding a therapist felt as intuitive and confidence-building as the best consumer booking experiences? Then we worked backwards. Product, design and engineering partnered closely to bring that vision to life — elevating provider profiles, improving discovery and matching logic and streamlining the path to booking.
It’s an early step toward a much bigger vision for our marketplace, but it stands out because it lets us show, not tell, how Grow works: transparent, human-centered and built with intention.
How do you balance experimentation with stability?
Healthcare demands trust, so stability is non-negotiable. But standing still isn’t an option either.
We balance this by separating where we experiment from what must remain resilient. Core infrastructure and compliance-sensitive systems have high reliability standards, clear ownership and strong observability. Around that foundation, we create room for experimentation in defined surfaces: new matching logic, workflow optimizations, AI-assisted tooling and experience enhancements.
We also anchor experiments to outcomes. We’re not experimenting for novelty — we’re testing hypotheses tied to access, quality and provider efficiency. Small bets, fast feedback loops and clear success metrics.
The key is alignment. When teams understand the long-term vision and the quality bar, experimentation becomes easier. That allows us to move quickly without eroding the trust our providers and clients depend on.
Maybern is a fintech company that aims to modernize fund operations and help investment managers improve efficiency and accuracy.
How does innovation show up in your company culture?
Innovation at Maybern shows up in the expectation that everyone, especially engineers, is deeply product-minded. We’re building a highly configurable accounting system that has to be fast, efficient and work across an entire industry, so good ideas don’t come from isolated technical decisions.
Engineers are expected to understand the ins and outs of accounting and how customers use the platform. That shared context leads to better system design, smarter abstractions and fewer one-off solutions. Innovation shows up in those everyday decisions — choosing scalable primitives over custom fixes and building flexibility into the platform in a disciplined way.
What’s one recent innovation that improved user or employee experience?
A recent innovation was MXL, an Excel-like DSL we built into the platform.
We saw early that supporting a wide range of accounting, performance and business calculations through bespoke implementations would slow us down and create long-term risk. The real challenge wasn’t the calculations themselves — it was how to safely expose configurability at scale.
MXL gives users expressive power where they need it, while preserving consistency, correctness and velocity on our side. It’s improved customer experience by reducing dependency on us for changes and improved employee experience by eliminating repetitive custom work.
How do you balance experimentation with stability?
We’re very deliberate about how we balance experimentation with stability. Because we’re building a system of record, stability and correctness are non-negotiable — the numbers always have to be right.
That constraint shapes how we experiment. We place heavy emphasis on automated testing and validation infrastructure, which gives us a high degree of confidence in the core of the platform. With those guardrails in place, teams can move quickly and experiment without putting correctness at risk.
In practice, that means we’re conservative about changes to the accounting engine itself, but much more flexible in how we iterate on configuration, user workflows and new product surfaces. The result is that we can ship quickly while still maintaining the reliability you’d expect from a system of record.
Bilt Rewards is a fintech company that created a loyalty program and payments platform, allowing renters to earn points on rent and daily purchases.
How does innovation show up in your company culture?
When a company is growing quickly and launching new products, it’s tempting to equate the breadth of offerings with innovation. But we believe innovation comes from doing things the hard way when it leads to a better customer experience. That mindset comes from a culture of constantly questioning every user interaction: Is this step necessary? Can it be automated? How can we meet users where they are instead of forcing them to change their behavior? This approach is what creates truly seamless experiences and builds lasting brand loyalty.
Innovation also shows up in our culture through ownership. We’re a team of builders, not managers, which reduces friction between ideas and execution. When no task is above or below someone, teams move quickly because the people closest to the work make decisions and own outcomes end to end. Ownership means individuals don’t just suggest ideas. They build, test and stand behind them. This creates a culture of fast iteration, accountability and continuous improvement, where innovation is part of everyday execution rather than occasional breakthroughs.
What’s one recent innovation that improved user or employee experience?
Dining was the first category we added when expanding our rewards and benefits program beyond the home and into the neighborhood. Dining loyalty is crowded and fragmented, from punch cards at coffee shops to card-linked offers and restaurant-specific CRM systems and it would have been easy to become another rewards player focused on spend and repeat visits.
Instead, starting from the home allowed us to use our existing loyalty and payments platform to unify the experience across our restaurant network. Members are treated like regulars wherever they dine and receive rewards that go beyond points, such as a courtesy Lyft ride home from your dinner or a complimentary dish that doesn’t have to be “redeemed” but just shows up at the table because we’re integrated directly into booking and POS systems. These deep integrations also enable new experiences, like charging a restaurant bill to your home, similar to billing a meal to your room at a hotel.
How do you balance experimentation with stability?
This is the perennial challenge for fast-paced startups. We balance it by experimenting with a dedicated group of highly engaged customers who want early access to new features. These members understand that what they’re trying may not yet be fully polished, which allows us to shorten feedback loops, iterate quickly and validate ideas with real users before broader release.
At Bilt, this program is called Close Friends. Unlike typical beta channels that skew toward highly technical early adopters, we’ve built it as a community. Early access to features is just one of the benefits our Close Friends receive, along with behind-the-scenes access to our culture, invite-only events and partner experiences. This attracts a more diverse audience, which in turn leads to better feedback, helping us refine products while protecting the stability of the core experience for our broader member base.
Fora Travel is a travel tech company that offers a comprehensive platform designed to empower individuals passionate about travel to build successful businesses.
How does innovation show up in your company culture?
Innovation at Fora isn’t something we have to force — it’s built into our mission as a company. We’re rethinking how the travel advisory industry works and giving entrepreneurs a smarter, more modern way to build their own travel businesses. That naturally creates a culture where questioning the status quo is encouraged, not avoided.
There’s a lot of trust from leadership to try new things and see what sticks. We’re encouraged to experiment with AI, explore new design approaches and even rethink how teams collaborate to get work done. It’s not unusual for design or engineering to lead an initiative if that’s what makes the most sense, which keeps things flexible and fast-moving.
On the design side, innovation shows up as the freedom to imagine what should exist, not just what already does. Instead of copying what’s been done in travel tech before, we’re pushed to create tools that feel intuitive, thoughtful and genuinely enjoyable to use. Having the support to experiment and take creative risks makes it possible for us to build something that feels truly new and sets a higher bar for the industry.
What’s one recent innovation that improved user or employee experience?
Funnily enough, an “innovation” that’s made a big impact is Fora is our in-office culture. So many startups are choosing to go with the streamlined work-from-home approach, but being together four days a week is a core part of our identity at Fora. The difference is clear: We’re working faster, creating better products and having more fun doing it.
As I’ve grown my team, I’ve talked to candidates who were hesitant about being in the office that often. What’s been really rewarding is seeing those same people a few months later saying things like, “I can’t believe I’m sick. I miss coming into the office!” That shift says a lot about the culture we’ve created and the impact it has on our employees.
That human connection is also a big part of what makes Fora’s product special too. We’re not building for abstract users or metrics — we’re building for real people. Being together reinforces that mindset and shows up in everything we do, from how we work internally to the thoughtful, people-first experiences we create for our advisors and travelers.
How do you balance experimentation with stability?
With the rise of AI, I think now more than ever, you need to be willing to experiment continuously. Just the other day I had to remind myself that instead of diving into Figma like I normally would, I could quickly prototype a proof of concept.
That being said, I think at a fast moving startup, it’s absolutely critical to remember what you actually have built alongside where you want to go. Experimentation and future states can be more fun to work on, but we have thousands of actual people using our product every day. It’s critical to remember that providing stable improvements to those users is just as valuable as a fancy new feature.
At Fora, I think we find this balance by leaning into our different core strengths. Our founders might be inspiring us to push boundaries or build the next great thing, while our product managers and product designers are laser-focused on the day to day user experience. I think that blend is actually what creates great technology products.
