AI Decision Risk Management

Your AI decided.
Can you prove
it was right?

Praxius captures the rules, the decision, and the outcome across rules engines, AI agents, and human reviewers, then connects all three statistically. Because when regulators ask why your system denied 40,000 claims last quarter, "the model said so" isn't an answer.

Request a demo
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Drop-in SDK — any agent framework
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No model access required
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Works with rules, AI, and humans
Decision Trace
trace-a4f8b291
Denied
Confidence: 64%
Policy: MGP-EXP-2025 v2.2 · Meridian Expense Policy
Receipt Compliance Pass
Business Purpose Adequacy Fail
Purpose too vague: "team lunch" — no business context provided
Category Limit Compliance Fail
$284 exceeds $75 meal limit for standard market
Pre-Approval Compliance Pass
Pattern Intelligence
High Risk
Decisions missing business purpose documentation were 3.2× more likely to be overturned on review. This pattern is worsening.
3.2×
Odds Ratio
p<.01
Significance
2,165
Decisions
⚠
HITL Complacency Signal: Average reviewer time dropped from 3m 58s → 47s over 90 days. Override rate collapsed from 38% → 3%. Reviewers may be rubber-stamping.
Decision Forensics
Pattern Intelligence
Outcome Attribution
HITL Complacency Detection
Policy Versioning
Temporal Accountability
Evidence Gap Analysis
Regulatory Compliance
Decision Forensics
Pattern Intelligence
Outcome Attribution
HITL Complacency Detection
Policy Versioning
Temporal Accountability
Evidence Gap Analysis
Regulatory Compliance

Designed to support compliance with CMS WISeR prior auth requirements, the Treasury AI Risk Management Framework, and EU AI Act high-risk decision obligations.

The Problem

AI decisions
are a black box.

Your AI makes thousands of decisions daily — approvals, denials, escalations. You can see the outcomes. You can't see why, whether the evidence was adequate, or whether the pattern is getting worse.

01 / 04
"Our denial rate is up 15%. Is the AI wrong, or did the policy change?"
Without connecting the policy rules, the decision evidence, and the downstream outcome, you can't distinguish between a working system and a broken one. You're flying blind.
→ Decision Forensics
02 / 04
"We have a 97% approval rate. That means it's working, right?"
High approval rates can mask silent quality degradation. If your human reviewers are rubber-stamping AI decisions in 45 seconds instead of 4 minutes, your safety net has a hole in it.
→ HITL Complacency Detection
03 / 04
"Which evidence gaps actually cause bad outcomes?"
Missing a receipt is annoying. Missing clinical documentation correlates with 3.2× more adverse outcomes. Without statistical proof, every gap looks the same. You can't prioritize what matters.
→ Pattern Intelligence
04 / 04
"We updated the policy in March. Did things get better or worse?"
Policy changes ripple through thousands of decisions. Without before-and-after statistical comparison tied to specific policy versions, you'll never know whether the change helped or hurt.
→ Temporal Accountability
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Every monitoring tool captures the decision. None of them close the loop.
Observability platforms tell you what your AI did. They never ask: did that decision produce a good outcome 30 days later? Without that feedback arc (from decision to outcome, measured statistically), you're flying blind with better instrumentation. And it's not just AI. Decisions flow through rules engines, ML models, and human approvers, often all three in sequence. If you can only see one link, you can't find the failure. Praxius sees the full chain.
How It Works

Three sides of
every AI decision.

Praxius captures the rules the AI was following, what it decided and why, and what happened as a result. Then it runs the math to show you where things are breaking. No other platform does this.

01 / 03
📐
Capture the Rules
Upload your policies, business rules, or compliance requirements. Praxius versions them with effective dates so every decision is evaluated against the rules that were active at the time.
policy: "MGP-EXP-2025"
version: "2.2"
effective: 2026-01-31
gates: [receipt, purpose,
  limits, pre_approval...]
02 / 03
📡
Record Every Decision
Add a few lines to your agent's post-processing step. Praxius captures the outcome, confidence, gate evaluations, evidence gaps, and reasoning for every decision. Rules-based, AI, or hybrid.
praxius.recordDecision({
  outcome: "DENIED",
  confidence: 0.64,
  gates: [...],
  gaps: ["business_purpose"]
})
First decision trace in < 1 hour
03 / 03
🔬
See What's Going Wrong
Praxius links evidence gaps and gate failures to adverse outcomes using chi-square tests, odds ratios, and confidence intervals. Drift, HITL complacency, policy impact. Proven, not assumed.
finding: "business_purpose"
odds_ratio: 3.2
p_value: 0.003
ci_95: [2.1, 4.8]
trend: worsening
Same statistical methods used in clinical research (chi-square, Fisher's exact, Welch's t-test) with minimum sample enforcement and 95% confidence intervals. Findings are defensible, not directional.
Where Praxius Fits

Built for decisions where
getting it wrong has consequences.

Enterprise Operations
Expense & Procurement AI Monitoring
Automated expense and procurement workflows blend rules, AI judgment, and human approvers. Praxius monitors the full chain: policy drift, reviewer inconsistency, and cost leakage across thousands of decisions.
✓ Cross-method monitoring · Reviewer comparison · Cost impact quantification
Financial Services
Suitability & Recommendation Oversight
AI recommendation engines must demonstrate every suggestion had a policy-compliant evidence basis. Praxius tracks which suitability checks are being missed and whether those gaps correlate with compliance exceptions.
✓ Per-decision evidence trail · Treasury AI framework alignment · Drift detection
Insurance · Underwriting
Underwriting Decision Quality
AI underwriting decisions get challenged, but model drift goes undetected for months. Praxius detects when confidence scores rise without outcome improvement — the signature of a system that thinks it's getting better while it isn't.
✓ Confidence drift detection · Temporal policy analysis · Outcome attribution
Healthcare · Utilization Management
Prior Authorization Risk Intelligence
AI prior auth agents deny thousands of claims daily. Praxius shows which denials are linked to missing clinical documentation and which ones get overturned on appeal at 3× the normal rate.
✓ Gap-to-outcome attribution · Appeal pattern detection · CMS WISeR compliance

In our reference deployment, Praxius detected that a policy change increased receipt-related evidence gaps from 0% to 46% of cases (p < 0.001), while reviewer decision times simultaneously decreased 74% — a pattern invisible to every other tool in the stack.

Where This Is Going

The decision audit is
becoming inevitable.

Today
See what went wrong — with proof
Praxius captures every decision, links it to the policy in effect and the outcome that followed, and runs the statistics. You get forensic-grade attribution: which evidence gaps actually cause bad outcomes, which reviewers are rubber-stamping, which policy changes made things worse.
Next
Flag risk before the decision is finalized
With enough decision history, Praxius can score risk in real time. Before an agent finalizes a denial or an approver clicks "accept," Praxius surfaces the pattern: decisions with this evidence profile have historically gone sideways. Escalate, don't rubber-stamp.
Eventually
Map entire decision chains end to end
When the triage agent's output feeds the authorization agent, and a denial surfaces three steps downstream as an overturned appeal, you need to trace the full chain. Praxius maps decision supply chains across agents, teams, and systems — so when something breaks, you know exactly where the risk originated.
Every AI decision will need the same accountability as a financial transaction. That world is coming whether the tooling is ready or not.
Design Partner Program

See what your
decisions can't tell you.

We're working with a small number of teams deploying AI in regulated decision workflows — healthcare, financial services, insurance, enterprise operations. If your system is making decisions that matter and you can't fully explain why, we should talk.

No sales pitch. We'll share a 10-minute walkthrough and see if there's a fit.

We respect your data. No sales outreach without a clear fit.

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We got your message.
We'll review your inquiry and get back to you soon. In the meantime, keep building — we'll catch up.