Defend every AI-assisted
denialprior-auth rulingappealcoverage callmed-necessity ruling
FoxCommand turns every AI-assisted decision into a governed, replayable record — the inputs, the policy version, the routing, what changed — so you can defend it to an auditor, an appeals body, a client, or a court without re-running a black box.
Starting in RCM. Designed for consequential AI workflows.
Reproduce the decision. Don't reconstruct it.
Every capability is designed for one purpose: turning AI-assisted decisions into defensible records that can be inspected, compared, and replayed.
The record you hand a regulator, reproduced exactly — no new inference, no additional LLM cost. The execution contract guarantees the output is identical to what was originally served.
Run the same case under two configurations and see exactly what the policy change caused. Every other variable stays locked — so the delta is the answer, not a hypothesis.
Change a single policy variable and recompute its effect across historical decisions before you ship. Deterministic — no PHI exposure, no probabilistic drift.
Every governed decision lands in a standing, queryable, attestable record — inputs, policy version, routing, and output. The durable artifact your auditor, appeals body, or counsel pulls when it matters.
Starting with denials, prior authorization, and appeals. Built as a decision-record layer for any workflow where AI decisions need to be replayed, audited, and defended.
One substrate. Aimed where the exposure is.
FoxCommand governs any consequential AI decision. We're starting with the workflows under the most legal and regulatory pressure — and expanding from there.
Healthcare RCM
Driven by California SB 1120, the multi-state human-review wave, and the Lokken discovery order.
The pre-built denial-defensibility template. Plug in your AI outputs and produce a replayable, attested record for every coverage decision — the one you hand an auditor, an appeals body, or a court.
Insurance
NAIC's AI model bulletin and state insurance-department adoptions.
Show which model version and which policy drove a rate or a claim outcome — and prove it was applied consistently.
Lending & Credit
ECOA / Reg B adverse-action requirements and scrutiny of AI credit models.
Reconstruct the exact basis for an adverse-action decision — the inputs, the cutoffs, the version — when a regulator or an applicant asks.
Fraud & Risk
Wrongful-hold and wrongful-denial disputes.
Defend why a transaction was held or an account was actioned — replayed under the policy that was live at the time.
…and any workflow you'll have to answer for.
See the record you'd hand a regulator.
20 minutes. We'll walk through a live denial-evaluation scenario and show you controlled replay and policy simulation on a real decision.