Aktana:
Orchestrating AI for Life Science
Estimated read time: 2 minutes
ADOPTION
↑20%
ARR
5
RX IMPACT
AI Products
↑50%
↑30%
Aktana focused on helping commercial teams in life sciences run their Go-to-Market strategy more effectively. The idea was straightforward: give each rep a daily plan; a “Next Best Action” (NBA), showing who to engage, when, through which channel, and with what message. The challenge was that these suggestions were based on strategies that often took 6 - 12 months to develop, so by the time they reached the field, they were already outdated and no longer connected to what was happening in real time.
When I joined, Aktana had about 35 employees globally, with R&D based in the Bay Area. The product didn’t yet use AI or machine learning, and my role was to modernize the platform, shifting it from a static rule engine to one powered by live data, ML models, and real-time context. The goal was to make suggestions more relevant, more timely, and more aligned with what was actually happening across the commercial ecosystem.
To tackle this, I broke the work into two pillars:
-
The carriers: the commercial reps responsible for delivering the strategy.
-
The receivers: the healthcare providers (HCPs) and healthcare organizations (HCOs) the strategy was meant to reach.
Improving Rep Engagement (“The Carriers”)
Reps are independent and often rely on familiar habits, so getting them to follow suggestions was the first challenge. We created two AI modules to support this:
-
Rep Location predicted where a rep would be the next day, so suggestions matched their actual movement.
-
Rep Engagement learned each rep’s behavioral patterns across channels and introduced small, gradual changes: timing, phrasing, context, and justification, to make suggestions feel more relevant and easier to act on.
The idea wasn’t to force behavior change; it was to meet reps where they were and move them toward the strategy one step at a time. This approach led to a meaningful increase in suggestion uptake, with reps engaging more consistently in ways aligned with the brand’s goals.
Improving HCP/HCO Engagement (“The Receivers”)
The second challenge was to make sure HCPs and HCOs actually engaged with the brand’s outreach. We broke down each strategy into its core components: message, channel, and timing, and introduced a patented method to measure HCP engagement. That data fed our ML models, which helped optimize how and when outreach should happen.
Once those pieces were in place, we built an orchestration layer that chose the best combination of message, channel, timing, and rep for each situation. The result was a more adaptive, responsive plan that reflected what was actually happening in the field.
Impact & Growth
This work helped shift Aktana from a rules-based system to an AI-driven platform that aligned better with how reps work and how HCPs respond. It helped increase ARR by roughly 20%, boosted HCP engagement by about 30%, and increased rep adoption of suggestions by 50%.
During my time there, the company grew from 35 to around 500 employees worldwide. That level of growth brought new expectations for the product and required a clearer strategy, stronger cross-team alignment, and a more scalable approach to how we delivered value, which I brought to the table as Senior Director of Product Strategy.