Brand cycle, HCP engagement, MLR, samples, speaker programs, IDN accounts — one view of your commercial operation, alive and complete.
The commercial operation as one operating model — HCP at center, every surface connected.
Brand cycle drops. Reps start detailing. Approved emails deploy. Samples ship. MLR clears the next campaign. Speakers book the quarter. Six systems. Four agencies. Three time zones. AI-BOS sees it as one operation.
The brand team launches the cycle plan two months before the rep can speak to it. By the time the field has the detail aid in their tablet and the MSL has been briefed on the new clinical data, half the cycle window is gone. The campaign moves at the speed of headquarters; the field moves at the speed of CLM training and Vault approval. Most field forces work the previous cycle's plan in the current cycle's market.
Same physician, three different identifiers across CRM, marketing automation, and sample accountability. One reconciliation job runs nightly and fails when affiliation changes. The KAM sees a different account name than the rep. The brand sees a different engagement score than the field. Reconciliation is everyone's problem and no one's job.
Every promotional asset goes through MLR — medical, legal, regulatory review. Average review cycle: four to twelve weeks per asset, depending on therapeutic area and asset type. The campaign window the brand team budgeted for assumes the lower end. The actual review consumes the upper end. The detail aid the rep was supposed to use in week one lands in Vault week six. The asset ships late and gets used short.
PDMA compliance requires signature for every sample drop. The rep records the signature on tablet, the sample is debited from inventory, the field accountability system reconciles against the warehouse. Variance opens between any pair of those three systems and stays open until someone investigates. Real variance is usually a workflow gap — a sample-drop that didn't sync, a returned-to-warehouse that wasn't logged. Compliance has to assume the worst until proven otherwise.
A typical integrated delivery network gets touched by the rep, the KAM, the MSL, the market access lead, the speaker programs team, the patient access team, and medical communications. Each function holds its account plan in its own system or spreadsheet. The KAM tries to coordinate without authority over MSL or market access. The IDN sees a parade of separate visitors from one brand, with one set of conflicting promises.
Now imagine asking the right side a question.
Once the picture is one operation, you can ask it questions. The brand-field timing gap your team feels every quarter — AI-BOS sees which detail aids cleared MLR late and which territories worked the previous cycle's plan into week six, and quantifies what that cost in reach. The master data drift you have eight people reconciling — AI-BOS holds one HCP record across CRM, sample, formulary, and engagement systems, and surfaces the affiliation change that broke last Tuesday's reconciliation. The IDN parade no one coordinated — AI-BOS shows the account plan as the brand sees it, as the KAM sees it, as the MSL sees it, and where the promises overlap or contradict. The model that gave you credibility in Act 1 becomes the model that gives you advice in Act 2.
You have the data. It lives in twelve systems. The cycle plan your brand team launched eight weeks ago — that's in the brand cycle tool, the MLR queue, CLM, the approved email platform, and the field performance system, but the question of which territories ran the plan as designed and which ran the previous cycle's plan because their training lagged — that question has to be reconstructed manually for the quarterly business review. The sample accountability variance that opened Monday — that's in two systems, neither of which agrees with the third. The IDN account plan — that's seven spreadsheets shared in chains of emails. You don't lack data. You lack the mind that sees it.
AI-BOS surfaces the answer in operator language, drawn from systems that don't talk to each other. The brand cycle launched on schedule, but MLR held the lead detail aid an extra fifteen business days due to a label-update routing escalation. Three Northeast territories had a rep restructure midway through, and four reps haven't yet completed CLM training on the new aid. The approved email serving the same key message deployed on time, but engagement scores in tier-1 endocrinology are running 18% below the previous cycle because the email lacked the chart that lives in the held detail aid. Recovery path: route the held detail aid for expedited final approval; accelerate training in the three impacted territories; deploy the chart as a standalone Vault asset to the email pool. AI-BOS does this against your live operating model, in real time, drawing from systems that don't talk to each other.
AI-BOS sits above Veeva CRM, Veeva Vault PromoMats, the marketing automation platform, the sample accountability system, and the speaker program platform. Each system holds part of the truth about each HCP — same physician, different identifiers, reconciled never. AI-BOS reads them as one HCP graph. When the rep records a tier-2 oncologist's interest in a publication and the publication is not yet MLR-cleared, AI-BOS surfaces this to the MSL queue without manual handoff. When the KAM's IDN account plan shows the same HCP under a different account-name spelling, AI-BOS resolves it as one identity. The reconciliation that took your team forty hours a month happens continuously, in the background. Field, brand, MSL, and KAM see the same HCP, in real time, because there is only one HCP record.
Cycle to cycle, brand teams discover what worked in retrospect — the territories that hit reach, the channels that lifted engagement, the speaker programs that converted. AI-BOS watches as the cycle runs: which detail aids fire in which territories, which approved emails open in which segments, which speakers carry which IDN affiliations. Three weeks into the cycle, AI-BOS surfaces a pattern: tier-2 cardiologists in the South region open the lead approved email at 47% but click through at 8% — the email's call-to-action routes to a video the segment does not open. Nobody saw the pattern; everyone felt it. Now you can fix the email mid-cycle, not after.
Today, AI-BOS surfaces patterns and answers questions and reconciles systems and runs rules you can edit in plain English. Your CCO, your brand director, your KAM, your compliance officer each get the same operational truth in their language, in real time, while your existing Veeva and Reltio and IQVIA stack keeps running. When you're ready — vertical by vertical, on your timeline — AI-BOS can do more than advise. The off-label escalation rule AI-BOS surfaces and your brand lead edits can become the off-label routing AI-BOS executes. The cycle pattern AI-BOS spots can become the cycle adjustment AI-BOS recommends and the field accepts. The picture becomes the system, one vertical at a time.
Imagine the off-label routing rule your brand lead edited in Act 2 — AI-BOS doesn't just surface it, it executes it. The brand-field timing gap your operating model sees forming — AI-BOS deploys the supporting standalone email or pre-launch field briefing before the cycle starts losing reach. The HCP master data drift that took eight people a week — gone, because AI-BOS holds one HCP record and reconciles continuously. Worker screens aren't built once and used everywhere; they generate per role and per moment, showing the rep what the rep needs for this HCP today, the MSL what the MSL needs for this account plan, the brand lead what the brand lead needs for cycle three readiness, the compliance officer what the compliance officer needs for this quarter's audit prep. Business logic isn't buried in code that takes IT three quarters to change; it's text the brand lead, the compliance officer, the chief commercial officer can each edit, deploy, and adjust as the cycle evolves. The translation chain — brand strategy to advisory firm to systems vendor to development sprint to deployment to training — collapses to a single editable rule.
Commercial analytics typically goes first for most life-sciences operators — lowest-risk migration, highest immediate insight on cycle performance and reach against plan, the cycle-over-cycle improvement story funds the rest. Sample accountability follows when warehouse, mobile signature capture, and reconciliation feeds can run as one orchestrated flow rather than three coordinated systems. IDN account planning consolidates next as the integrated HCP view proves the cross-function advantage. Medical affairs and MSL coordination typically stay at Act 2's advisory layer rather than migrating to runtime — the relationship between medical and HCPs is one of the right places to keep human authority, not the right place for AI to act unilaterally. Promotional review (MLR) similarly stays advisory: AI-BOS accelerates and routes; humans decide what releases. Each vertical migrates on your timeline; the verticals you keep on legacy keep running through Veeva, Vault, OneKey, and the rest of your stack while AI-BOS reads from them and reconciles continuously.
The full picture of your operation — parties, processes, entities, deployment — rendered as a navigable graph you own. Under NDA. Accessible inside AI-BOS. Yours to read, edit, and use.
We'll build it through a Discovery process that combines public-source ingestion (your filings, your systems' external APIs, industry data) with stakeholder interviews (your CCO, your CFO, your CIO, your VP commercial excellence — the people who know the operation). You'll own the artifact; you'll decide what happens next.
The operating model is a complete value transaction in itself — ready for board reporting, AI-readiness preparation, M&A due diligence, or simply seeing your operation clearly for the first time. No obligation to move beyond Stage 1.