Lessen LLC Innovation & Technology Culture

How do your teams stay ahead of emerging technologies or frameworks?

We’ve designed both our platform and our culture to support continuous evolution.
From a technology standpoint, our modular, service-oriented architecture allows engineers to experiment with new tools, frameworks and AI models in isolation, validate them quickly and scale successful approaches into production without disrupting core systems. Just as important, we intentionally create space for learning. Engineers are encouraged to build depth in their domain while exploring adjacent areas, take on new challenges and grow into emerging problem spaces like AI, data and platform engineering. That flexibility helps our teams stay current while building skills that remain relevant as the technology landscape changes.

Can you share a recent example of an innovative project or tech adoption?

One of our most impactful innovations has been Aiden, our AI-powered platform that applies generative AI and agent-based systems across the entire facilities maintenance lifecycle.
Rather than building a single assistant, our engineering teams designed Aiden as a multi-agent system that can reason over structured and unstructured data, coordinate across workflows and take action when appropriate. It combines retrieval-augmented generation using our proprietary maintenance dataset with workflow-aware agents that support intake, triage, proposal review, invoicing and ongoing asset intelligence. Aiden has already driven significant business impact from more than ten percent improvement in first time fix rates via better work intake to three times faster time to process invoices via Aiden invoice assistant and a nearly 40 percent decrease in rejected proposals through Aiden proposal assistant for vendors.

How does your culture support experimentation and learning?

Experimentation is deeply embedded in how we operate. We intentionally create safe spaces for engineers to try, fail and iterate whether that’s through hackathons, proof-of-concept work or controlled pilots inside production workflows. Our AI hackathon is a standout example where engineers work side by side with product, design and operations counterparts to prototype new agents, workflows and user experiences in a short, focused window and present them to real customers for judging. Several ideas that started as hackathon experiments are now live in production, delivering measurable efficiency gains and reducing manual work across our platform. It’s a great example of how we move from experimentation to real-world impact quickly.