| Regulated Next-Best-Action Orchestration | Deterministic and AI system to orchestrate compliant communication sequences across sales, marketing, and medical environments. | CRM, SFE, segmentation, engagement history, channel permissions, compliance rules | Human: next action plus rationale. M2M: JSON workflows, agent tasks, execution payloads. | Multi-parameter decision engine, constraint layer, scenario-based sequencing, audit trail | Eliminates guesswork, enforces compliance, improves timing and channel precision | Higher engagement ROI, reduced compliance risk, improved field efficiency | Very High (EUR 75K to 250K) | Medium | Full | Critical | CRM integration, compliance rules, segmentation model |
| Decision Intelligence (BI / SFE) | Transforms BI and SFE data into auditable decision systems using weighted matrices. | BI dashboards, sales data, geo data, profiles, behavioral signals | Human: decision briefs. M2M: ranked matrices, API outputs, orchestration inputs. | Pyramidal knowledge, weighted scoring, deterministic logic, AI pattern detection | Moves from dashboards to decisions with traceable logic | Faster decisions, optimized resource allocation, consistent prioritization | High (EUR 75K to 200K) | Medium | Full | Critical | Data pipelines, BI tools, data quality |
| Pharma Commercial AI | Compliant commercial intelligence with segmentation and next-best-action sequencing. | HCP data, prescriptions, engagement, segmentation, tiering, adoption signals | Human: targeting strategy. M2M: action plans, CRM-ready outputs, sequences. | Segmentation engine, adoption modeling, next-best-action orchestration, compliance constraints | Tailored to pharma complexity and aligned with field and governance limitations | Increased adoption, optimized field-force impact, better campaign ROI | Very High (EUR 100K to 300K) | Medium to High | Full | Critical | CRM, regulatory framework, segmentation models |
| Scenario Intelligence (3DT) | Probabilistic scenario modeling using three-dimensional time and Bayesian inference. | Market data, internal metrics, external signals, strategic assumptions | Human: scenario narratives. M2M: scenario trees, probability-weighted outputs. | 3DT model, Bayesian inference, multi-variable simulation, decision-path modeling | Moves from forecasting to decision-ready futures | Better strategic decisions, risk reduction, improved investment allocation | High (EUR 100K to 250K) | Medium | Full | High | Data aggregation, modeling assumptions, scenario design |