Baseline Synthetic agents understand 867/852 distributor data, chargebacks, claims, GTN waterfalls, and 340B mechanics the way a senior pharma analyst does. They run continuously in your cloud. No implementation project. No team behind them.
Patient funnel tracking, GTN reconciliation, 340B compliance, channel performance, market access diagnostics — the work is data-intensive, domain-specific, and the same questions get asked every month at every brand at every company. The answer has always required expensive teams.
The domain knowledge required to do this work well takes a decade to develop. The people who have it command premium salaries. The work that depends on them keeps growing.
Every commercial function triangulates across 867/852 distributor data, claims (IQVIA, Symphony), payer invoices and chargebacks, HRSA, and CRM. Each arrives on a different schema, cadence, and quality standard.
Repetitive, expert, systematic, schedule-driven — everything modern AI does well, applied to one of the few remaining knowledge industries that has barely been automated.
Every pharma commercial company uses the same underlying data types — 867, 852, chargebacks, claims, HRSA, government pricing. The schemas vary; the semantic model does not. Baseline Synthetic agents are trained on that common semantic model. Onboarding is schema mapping, not implementation. The agent normalizes your data and begins operating — in your cloud, without a data science team behind it.
Purpose-built for one pharma commercial function — its data, logic, calculations, edge cases. Trained deep, not broad.
Coordinates specialists across cross-functional workflows. Answers questions no single agent could handle alone.
The semantic backbone. Maintained at the velocity the business actually changes — not on a quarterly software release cycle.
Runs entirely in the client's cloud — AWS, Azure, GCP. Data never leaves their environment. CISO-friendly from day one.
The first agent is the one with the cleanest economics, the tightest data scope, and the fastest path to a design partner. The next agent extends the platform into the analytics layer.
Automates gross-to-net reconciliation and 340B covered entity compliance. Triangulates product movement, chargebacks, eligibility, and exclusion data with expert matching logic. Surfaces compliance exposure before it becomes audit risk — and recovers revenue that manual offshore processes systematically miss.
See the full product →Tracks patients from diagnosis through prescription, payer access, dispense, and persistence — continuously, across claims, SP/hub, and CRM data. What a dedicated analytics team produces monthly, running in real time with on-demand querying. Begins development after the first product has design partner traction.
See the roadmap →The transition from AI-as-reporting to AI-as-action arrived in pharma commercial during the 2025–2026 cycle. The platform players have moved first — with horizontal, CRM-adjacent agents. The deeply expert, function-specific agent layer for analytics and operations is open. The pharma commercial domain expertise required to build it is genuinely scarce, and that's the entry barrier Baseline Synthetic is built around.
We're building in stealth. If you run commercial analytics, market access, or government pricing at a specialty pharma company — or you invest at the earliest stage and want a closer look — reach out directly.
sukhin@b-synth.net →Direct contact only. We'll respond personally.