Deep Insight Engine · Brekiya build
The number, and the belief to act on it — wired into the tools your teams already use.
Two engines running in parallel: Evidence Assembly constructing the ER-avoidance cost story that doesn't yet exist in usable form, and Bias Discovery diagnosing which belief is standing between that evidence and a decision. Value Translation combines them; Activation ships them inside the surfaces below.
Net cost avoided / patient / yr
$1,879
Current model assumptions
Addressable population
132,000
132K high-probability cohort
Patients flagged (match ≥ 85)
4
of 6 in current pull
Top bias signal, 30d
Budget-silo bias
Payers / medical directors · 128 detections
Start here · The intelligence layer
Everything downstream reasons from this. Open it before you open a tool.
Intelligence layer · Stakeholder & Bias Intel
Open →
7 decision-makers in Brekiya's path. Click any one to see what matters to them, how they think, and the specific heuristics driving their treatment and coverage behavior.
Bias & heuristic signals live inside each stakeholder — not on a separate map. A payer's silence, a fellow's hesitation, a PBM's step edit each read differently once you see the belief underneath.
7
Stakeholder profiles
6
Live heuristic signals
381
Field-data detections · 30d
How the engine runs
Four layers, two engines, one activation point.
Layer 1
Stakeholder Intel
Living profiles + the heuristics detected inside each — the layer every other tool reasons against.
Layer 2A
Evidence Assembly
Constructs the ER-avoidance number — matched cohorts, benchmarks, counterfactual modeling for the visit that didn't happen.
Layer 2B
Bias Discovery
Continuously reads advisory transcripts, call notes, PA denials against the Deep Insight bias taxonomy — surfaced inside the stakeholder profile.
Layer 3+4
Translate & Activate
One number + one reframe, delivered inside the tools each stakeholder-facing team already uses.
Activation surfaces
Open a tool to see it work.
Tool 01Open →
ER-Avoidance Cost Model
A defensible, tunable estimate of cost avoided per Brekiya patient — the number every other tool depends on.
$1,879 / patient / yr
Tool 02Open →
Right-Patient Segmentation
Flags which of a provider's patients match the target profile — with the rationale attached, not a vague 'who's eligible?'
4 of 6 patients flagged
Tool 03Open →
Rep Economic Story Co-Pilot
A patient snapshot in, a bias-aware and cost-grounded PA appeal / peer-to-peer argument out.
Grounded in the cost model, not a placeholder
Tool 04Open →
Payer Value Dossier Assistant
A living dossier that leads with the constructed cost data, framed to counter that segment's specific bias.
3 segments · MA · Commercial · PBM