KaizenAI is the pharma-native platform transforming commercial data into high-impact decisions—from ML-driven call plans to bottom-up forecasting.
Platform Approach
Each module is independently valuable but designed to compound — insights from your performance audit feed the tactical plan, which informs sizing and deployment, which calibrates targets.
Omnichannel effectiveness assessment
Analyse how your current omnichannel tactics — face-to-face calls, virtual, phone, approved emails, events — are driving incremental sales for each HCP specialty. Generate ML-powered productive frequency curves with 95% confidence intervals to identify the optimal call window.
From Overview to Rep Fine-Tuning
Deploy an ML-based call plan across four layers: sales projections and channel contribution overview; account opportunities ranked by promotional sensitivity; recommended promotional mix by specialty, channel and tier; and rep fine-tuning with field knowledge feeding back into the model.
Optimal headcount and territory alignment
Use ML-driven promotional saturation curves and profit optimisation to determine the ideal number of reps. Then deploy them with mathematical optimisation across IQVIA® bricks or account-based territories — balancing potential, sales, workload and travel distance across cross-functional teams (Rep, FLM, KAM, MSL).
Territory-centric product prioritisation
Each territory has different sales, potential and market share dynamics. KaizenAI runs product-level ML models for each promoted brand and combines them in a Portfolio Recommender that optimises call allocation across products per territory — capturing incremental growth that uniform call plans miss.
Bottom-up ML forecasting with guardrails
Generate bottom-up ML forecasts integrating account purchasing patterns, tactical plans and seasonal adjustments — with configurable horizons and confidence intervals. Then cascade national targets to territory level using weighted variables (potential, sales, forecast, rep tenure, market share) and guardrails to prevent unfair targets.
Integrated data management & quality
A centralised data management UI lets you upload, inspect and validate all commercial data sources — structures, sales, potential, HCP file, multichannel engagement, events, RTEs and commercial agreements. Over 120 critical errors and warning checks based on pharma business knowledge surface data quality issues before they affect your models.
Case Studies
Each use case is a concrete business question that can be answered with ML. Explore how KaizenAI applies its models in real commercial scenarios.
"How will field force resizing impact sales and market share?"
Effort-Sales Model using Sales + CRM data to generate promotional saturation curves and profit optimisation for each FTE scenario.
"Where should we place reps in an equitable way to achieve a more efficient outcome?"
Evaluate account and brick-level sensitivity and workload, then optimize deployment to maximize balance while minimizing disruption and travel.
"Which HCP specialties are most sensitive to promoting a product?"
Use Effort-Sales modeling to identify productive frequency windows and refine frequency ranges by HCP specialty and tier.
"How should we allocate promotional effort to maximise results?"
Promotional sensitivity curve per covered HCP target combined with effort return by product chart enables data-driven optimal frequency assignment per tactic and channel.
"How to optimise call plans to maximise sales growth and attain the sales target?"
Recommended call plan per account based on promotional sensitivity, growth opportunity and call capacity per rep/cycle — with rep fine-tuning and reason tagging.
"How to distribute the promotional effort in customer engagement channels?"
Channel-Result Execution Model: Constrained optimization to model sales impact, refine call frequency per rep, and drive targeted HCP-level engagement.
"Which products and incentives should be prioritized by territory to maximize consolidated sales results?"
Analyse market share divergence across products and territories. Use opportunity detection maps and variable importance charts to customise the action plan per territory.
"What is the commercial agreements impact by region, territory & hospital?"
ML model analyses discount on sale impact to quantify to what extent pricing agreements are decisive in the sale and the sensitivity of each account.
"How do we make a sales boost to capture a greater business opportunity?"
Optimize sizing, deployment, and call plans: scale effort toward saturation and focus on high-growth, sensitive accounts.
"Can we quantify contribution by indication and team for multi-indication brands?"
ML models can estimate territory-level incremental sales by indication. Visualize indication balance across territories using penetration bubble charts.
"How can we segment our centres to focus and adapt the account action plans?"
ML clustering allows account archetyping and micro-segmentation based on multiple variables: potential, access type, regional authorisation, promotional sensitivity, #HCPs by specialty.
Customer Success Stories
All metrics reflect live deployments with pharma clients.
Territories using KaizenAI ML-based call plan vs. BAU across Oncology & Hematology products in Spain.
Incremental sales uplift in Oncology 2 territories using the ML call plan vs. Business-as-usual.
Hematology 1 territories showed +15% penetration index growth compared to non-KaizenAI territories.
ML-based portfolio recommender generated +12.7% incremental sales uplift vs. BAU in a multi-product deployment.
Fine-tuned ML tactical plan consistently drives target attainment above 100% in deployed territories.
In the Spain pilot, 25% of territories used the ML-based call plan — all outperformed BAU territories across all disease areas.
Benefits
Who We Are
We combine deep pharma domain knowledge with cutting-edge machine learning to build and deploy solutions that directly impact commercial performance.
Over 15 years developing and deploying analytics platforms for commercial pharma — from strategy to production-grade ML models.
Competition-proven machine learning expertise in deploying production-ready ML models that actually move the needle on sales performance.
Trusted by a broad range of pharmaceutical companies — from Top 20 global players to innovative mid-size firms — across multiple countries.
Our Clients
From Top 20 global pharma to focused specialty companies — across oncology, rare diseases, institutional, and retail portfolios.
Book a personalised demo and see how KaizenAI's ML models can be applied to your portfolio, territories and commercial teams — with results visible within weeks.