No model runs when a briefing is produced. A rule engine derives the facts and a fixed template renders them, so the same claims always produce the same briefing. The model runs upstream, before deployment, where a person reviews what it wrote before it ever runs.
AgentBrief turns the paid medical and pharmacy claims you already hold into a six-field, plain-language member briefing on your agent's screen in under 10 seconds — precomputed in batch inside your own AWS environment, so no inference sits in the call path.
Fragmented claims data means agents spend the first minutes of every call reconstructing a history the plan already holds.
Agents move between several disconnected systems to assemble a member's conditions, medications and recent care history before the conversation can start.
Missed refills, polypharmacy and adherence gaps sit in pharmacy data that member services and care management rarely have in front of them while the member is on the line.
Without a risk flag on the record, outreach is reactive: a high-acuity member is identified after a gap has opened rather than while it can still be closed.
PDC adherence, CDC composite and TRC follow-up windows can be missed for no better reason than that the person on the call did not have the information in front of them.
AgentBrief reads the claims extracts you already produce and returns a structured member briefing — no new integration code, and no model in the call path.
Removing the model from the briefing step did not remove it from the product. It moved to where its work can be checked: designing the rules and the template, before deployment, on a desk rather than on a call.
What was measured, and when. Phase 7 of ArtiSoft's JetStore agentic AI analysis (§8, read 2026-09-13) compared the deterministic template against a single 3-billion-parameter model over 22 curated member fact sets, in one comparison. That is strong evidence for a design decision and it is not a service level: your cohort, your feeds and your measures would have to be measured on your own data.
The same deterministic briefing serves member services, care management and the people who have to approve the deployment.
Handle time grows when an agent has to ask a member for a history the plan already holds. AgentBrief puts that history on the screen before the call connects — identically for every agent, on every call, because the renderer is deterministic.
Care managers are clinicians who spend a large part of the day assembling data. AgentBrief hands them the assembled version — conditions, adherence signals and open quality-measure gaps — before they dial.
The briefing is informational. It reports what the claims show, names the claim each line came from, and recommends no clinical action; the clinical judgement stays with your staff, where it belongs.
AgentBrief is deployed entirely within your AWS infrastructure. Producing a briefing calls no external service and no model at all; where the wider platform does run a model, it runs on compute inside your VPC. No patient data is transmitted to ArtiSoft or to any third party, so your compliance perimeter stays exactly where it is today.
AgentBrief's stack is deployed with AWS CloudFormation, so the whole footprint is reviewable as code before anything is provisioned.
AgentBrief never sees your patient data. It runs inside your AWS environment, produces a briefing without calling any external service, and writes its logs to your own account.
Book a 30-minute walkthrough. We will show you a briefing rendered from a synthetic cohort that mirrors your plan's demographics and condition mix — and the rules that produced every line of it.
Email us for more information about AgentBrief, deployment timelines, or to start a conversation with our team.
info@artisoft.io