A multi-agent AI solution that automates prior authorization for health plan payers. Four specialized Foundry Hosted Agents — Compliance, Clinical Reviewer, Coverage, and Synthesis — evaluate PA requests against coverage policies and produce auditable approve/pend recommendations in under 2 minutes. Built with Microsoft Foundry, the Microsoft Agent Framework (MAF), Azure Container Apps, and MCP healthcare data servers.
The solution supports two runtime modes:
| Mode | How to start | What happens |
|---|---|---|
| Foundry Hosted Agent (recommended) | azd up |
Agents are registered with Microsoft Foundry Hosted Agents; Foundry manages container lifecycle. Backend dispatches through the Foundry project endpoint using agent_reference routing and DefaultAzureCredential. |
| Local / Docker Compose | docker compose up |
All 4 agent containers + backend + frontend run locally — no Azure deployment needed. |
Decision policy and evaluation methodology adapted from the Anthropic prior-auth-review-skill: LENIENT mode decision policy, per-criterion MET/NOT_MET/INSUFFICIENT evaluation, confidence scoring, progressive gate evaluation, structured audit trails, NCCI bundling risk flagging, service-type classification, and provider specialty-procedure appropriateness as an auditable criterion.
Note
With any AI solutions you create using these templates, you are responsible for assessing all associated risks and for complying with all applicable laws and safety standards. Learn more in the transparency documents for Agent Service and Agent Framework.
- Multi-agent parallel execution — Four specialized agents complete a full PA review in under 2 minutes; Compliance and Clinical agents run concurrently via
asyncio.gather - Foundry Hosted Agents — Each specialist agent is independently containerized and deployed on Microsoft Foundry; Foundry manages the container lifecycle
- Gate-based decision rubric — Three sequential gates (Provider → Codes → Medical Necessity) with per-criterion MET/NOT_MET/INSUFFICIENT scoring and confidence weighting
- MCP-powered data access — Five remote MCP healthcare data servers: NPI Registry, ICD-10 Codes, CMS Coverage, Clinical Trials (DeepSense), and PubMed
- Human-in-the-loop — AI produces draft recommendations; clinicians Accept or Override with documented rationale; override traceability flows to audit PDF and notification letters
- Keyless authentication — All Azure resource access via
DefaultAzureCredential; no API keys, passwords, or connection strings stored or rotated - Full audit trail — 10-item compliance checklist, per-criterion confidence scoring, and an 8-section audit justification document (Markdown + color-coded PDF)
- Real-time progress streaming — SSE-based live updates with a phase timeline and per-agent status cards across all four agent phases
- OpenTelemetry observability — Native Application Insights integration with custom phase spans and semantic attributes
- Skills-based architecture — Agent behaviors defined in
SKILL.mdfiles; domain experts can update clinical rules without code changes - Two runtime modes — Deploy to Azure with
azd up(Foundry Hosted Agents) or run everything locally withdocker compose up
See the Deployment Guide for full prerequisites and step-by-step instructions.
Prerequisites: Azure subscription · azd ≥ 1.18.0 · Docker · GPT-5.4 access request
# Deploy to Azure (recommended — Foundry Hosted Agent mode)
azd auth login
azd up
# Or run everything locally (no Azure required)
docker compose upImportant
Model access required: GPT-5.4 requires a separate access request before it can be deployed. Apply for access here. Deployment will fail if access has not been granted to your subscription.
This solution uses a stateless dispatcher pattern: the FastAPI backend has no local AI runtime — all specialist reasoning runs in four independent Foundry Hosted Agent containers. The orchestrator dispatches through the Foundry project endpoint using agent_reference routing and DefaultAzureCredential. See Architecture for the full design.
- Keyless by design — all Azure resource access uses
DefaultAzureCredential; no API keys or connection strings are stored anywhere - Managed Identity — each Container App has a system-assigned managed identity with least-privilege Bicep-assigned role assignments (
CognitiveServicesOpenAIUser,Azure AI User) - Local auth disabled — the Azure AI Foundry account has
disableLocalAuth: true, enforcing Entra ID-only access - See Security guidelines below for additional hardening recommendations for production deployments handling PHI
This is an AI-assisted triage tool — all recommendations are drafts that require human clinical review before any authorization decision is finalized. Coverage policies reflect Medicare LCDs/NCDs only; commercial and Medicare Advantage plans may differ. See TRANSPARENCY_FAQ.md for full responsible AI transparency details.
| Document | Description |
|---|---|
| Deployment Guide | Step-by-step deployment — Docker Compose, azd up, prerequisites, environment configuration, troubleshooting |
| Architecture | Hosted-agent architecture, runtime modes, MCP integration, agent details, decision rubric, confidence scoring |
| API Reference | Full REST API documentation — endpoints, request/response schemas, SSE events, error codes |
| Extending | Add agents, MCP servers, change the decision rubric, customize notification letters |
| Technical Notes | SDK patches, MCP header injection, hosted-agent dispatch, structured output, known limitations |
| Troubleshooting | Common issues and fixes — CLI failures, auth problems, connection errors, Foundry trace issues |
| Production Migration | PostgreSQL schema, Azure Blob Storage layout, migration steps |
| TRANSPARENCY_FAQ.md | Responsible AI transparency details |
This solution leverages Microsoft Foundry, the Microsoft Agent Framework (MAF), Azure Application Insights, and MCP healthcare data servers to create an intelligent prior authorization review pipeline where four specialized AI agents work together to validate, assess, and synthesize PA decisions with full audit transparency and native OpenTelemetry tracing. Each specialist agent is independently containerized and deployed as a Foundry Hosted Agent, while the FastAPI orchestrator and Next.js frontend run in Azure Container Apps.
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The orchestrator coordinates four phases with four specialized agents:
| Resource | Description |
|---|---|
| Azure OpenAI GPT-5.4 in Microsoft Foundry | GPT-5.4 model announcement and capabilities |
| Microsoft Agent Framework Documentation | Official MAF documentation and getting started guides |
| Anthropic Healthcare MCP Marketplace | MCP healthcare data tools (MCP data tools, not the AI model) |
| Prior Auth Review Skill | Original methodology reference for decision policy and evaluation criteria |
| Model Context Protocol (MCP) | MCP specification and tooling |
Multi-agent parallel execution
- Compliance and Clinical agents run concurrently via
asyncio.gather, reducing wall-clock time from 20+ minutes to under 2 minutes per case - Coverage Agent runs sequentially after clinical findings are available
- Synthesis Agent executes the gate-based rubric to generate the final recommendation and confidence
- Four-phase pipeline: Pre-flight → Parallel → Sequential → Synthesis → Audit
Foundry Hosted Agent architecture
- Each of the 4 specialist agents has its own
main.py,schemas.py,Dockerfile,agent.yaml, andskills/directory underagents/<name>/ - Agents use the native MAF
from_agent_frameworkpattern withdefault_options={"response_format": PydanticModel}for token-level structured output — no JSON fence parsing - The FastAPI backend is a pure HTTP dispatcher — it has no local AI runtime; all specialist reasoning runs in the four independent agent containers
- Each agent container exposes
POST /responses(Foundry Responses API protocol) and is independently versioned, deployable, and scalable hosted_agents.pyis a two-mode dispatcher: direct HTTP to agent containers (Docker Compose), oragent_referencerouting through{AZURE_AI_PROJECT_ENDPOINT}/responseswithDefaultAzureCredential(Foundry Hosted Agents)- Agents are registered with Foundry via
scripts/register_agents.py(postprovision hook inazure.yaml) — Foundry manages the ACA container lifecycle; no self-managed ACA modules in Bicep scripts/check_agents.pyruns automatically after registration to verify all agents, App Insights, MCP connections, backend, and frontend are healthy before the deployment completes
Skills-based architecture
- Agent behaviors defined in SKILL.md files — domain experts can update clinical rules without code changes
- SKILL.md files live alongside each agent container under
agents/<name>/skills/<skill-name>/SKILL.md - Loaded at agent startup via MAF
SkillsProvider— no backend code changes needed to update clinical rules - Compliance skill: 10-item checklist (NCCI bundling + service type classification added as items 9 and 10)
- Coverage skill: Provider Specialty-Procedure Appropriateness is now a required explicit criterion (Step 1.4)
- Clinical skill: low-confidence extraction banner when
extraction_confidence < 60%surfaces directly in the frontend Clinical tab - Synthesis skill: emits
synthesis_audit_trail(gate results + weighted confidence breakdown) visible in the frontend Synthesis tab
MCP-powered data access
- Five remote MCP servers: NPI Registry, ICD-10 Codes, CMS Coverage, Clinical Trials (DeepSense), PubMed (Anthropic Healthcare MCP)
- Each agent container calls MCP servers directly via
MCPStreamableHTTPTool(configured viaMCP_*env vars) - DeepSense servers use Key-based auth with
User-Agent: claude-code/1.0header (handled by a sharedhttpx.AsyncClientin each agent container); PubMed uses unauthenticated access - PubMed uses
_ReconnectingMCPToolto auto-reconnect on idle session expiry (~10 min TTL) - All agents use
AzureOpenAIResponsesClientwith gpt-5.4 on Microsoft Foundry - MCP tools visible in Foundry portal under Build → Tools
Gate-based decision rubric
- Three sequential gates: Provider → Codes → Medical Necessity
- LENIENT mode: only APPROVE or PEND — never DENY
- Per-criterion MET/NOT_MET/INSUFFICIENT assessment with confidence scoring
- Configurable: switch to STRICT mode (adds DENY) via configuration toggle
Human-in-the-loop decision panel
- Accept or Override the AI recommendation with documented rationale
- Override traceability: flows to notification letters, audit PDF, and API response
- Authorization number generation (PA-YYYYMMDD-XXXXX)
- PDF notification letters (approval and pend) with clinical justification data
- All four agents visible in tabbed Agent Details: Compliance checklist, Clinical extraction (with low-confidence banner), Coverage criteria (including specialty-procedure match), and Synthesis gate pipeline + weighted confidence breakdown + disclaimer
Audit and compliance
- 10-item compliance checklist with blocking/non-blocking classification; items 9 (NCCI bundling risk) and 10 (service type classification) are new domain-aware improvements over the baseline Anthropic skill
- Provider Specialty-Procedure Appropriateness as a required, auditable
criteria_assessmententry in the Coverage Agent — sourced from NPI Registry taxonomy - Per-criterion confidence scoring with weighted formula (40% criteria + 30% extraction + 20% compliance + 10% policy)
synthesis_audit_trailwithgate_resultsandconfidence_componentssurfaced in the frontend Synthesis tab- 8-section audit justification document (Markdown + color-coded PDF)
- Diagnosis-Policy Alignment as a required auditable criterion
- Complete data source attribution and timestamp tracking
- Section 9 added on clinician override with full override record
Real-time progress streaming
- SSE (Server-Sent Events) for live progress updates
- Phase timeline with per-agent status cards and elapsed timer
- 9 progress events across 5 phases (preflight → phase_1 → phase_2 → phase_3 → phase_4)
Observability
- Azure Application Insights integration via OpenTelemetry
- Custom phase spans with semantic attributes (recommendation, confidence, agent status)
- Microsoft Foundry hosted agents provide native runtime and evaluation visibility when hosted mode is enabled
- Application Map, Transaction Search, Live Metrics, and Performance views
Follow the quick deploy steps on the deployment guide to deploy this solution to your own Azure subscription.
Important
Model access required: GPT-5.4 requires a separate access request before it can be deployed. Apply for access here. Deployment will fail if access has not been granted to your subscription.
This solution accelerator requires Azure Developer CLI (azd) version 1.18.0 or higher for Azure deployment. Please ensure you have the latest version installed before proceeding. Download azd here.
Click here to launch the deployment guide
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Tip
All buttons open the same dev environment (devcontainer) with azd, Azure CLI, Docker, and Node pre-installed. Once inside, you choose your runtime mode:
| Goal | Command | Runtime mode |
|---|---|---|
| Deploy to Azure (recommended) | azd up |
Foundry Hosted Agent mode — agents run as Foundry-managed containers; only the backend + frontend land in your Azure Container Apps |
| Run everything locally | docker compose up |
Docker Compose mode — all 4 agent containers + backend + frontend run on your local machine; no Azure deployment needed |
The Quick Deploy path described below uses azd up → Foundry Hosted Agent mode.
To deploy this solution accelerator, ensure you have access to an Azure subscription with the necessary permissions to create resource groups and resources. The Microsoft Foundry Resource and Project are automatically provisioned by azd up. The solution uses the Azure OpenAI gpt-5.4 model, which is automatically deployed as part of azd up — see Azure OpenAI model availability for details.
Warning
Region and deployment type: gpt-5.4 is available in East US 2 (eastus2) and Sweden Central (swedencentral).
| Deployment Type | Data Residency | Regions |
|---|---|---|
| GlobalStandard (default) | No guarantee — data may be processed in any region | East US 2, Sweden Central |
| DataZoneStandard | Data stays within geographic zone (US/EU) | East US 2 only |
- Sweden Central automatically uses GlobalStandard (the only supported type for that region) — no prompt is shown.
- East US 2 prompts you to choose between GlobalStandard and DataZoneStandard during
azd up.
If you need data residency, select East US 2 and choose DataZoneStandard. See Azure OpenAI model availability for the latest availability.
Pricing varies per region and usage, so it isn't possible to predict exact costs for your usage. The majority of the Azure resources used in this infrastructure are on usage-based pricing tiers. Use the Azure pricing calculator to estimate costs for your subscription.
| Azure Service | Purpose | Pricing |
|---|---|---|
| Microsoft Foundry | Foundry Resource + Project (auto-provisioned) + Azure OpenAI gpt-5.4 inference | Pricing |
| Azure Container Apps | Backend (2 CPU / 4Gi, min 1 replica) + frontend hosting | Pricing |
| Azure Container Registry | Docker image storage | Pricing |
| Azure Application Insights | Observability and tracing (optional) | Pricing |
Important
To avoid unnecessary costs, remember to take down your deployment if it's no longer in use, either by running azd down, deleting the resource group in the Portal, or running docker compose down for local deployments.
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Healthcare organizations processing prior authorization (PA) requests face significant challenges in coordinating complex clinical reviews across multiple departments. They must evaluate medical necessity, verify coverage policies, and produce auditable decisions — often under strict regulatory timelines. Some of the challenges they face include:
- High volume — U.S. providers submit ~300 million PA requests per year (CAQH Index)
- Manual, time-consuming reviews — each request takes 15–20 minutes of clinician and staff time (AMA, 2024)
- Slow turnaround — average PA decision takes 5–14 business days
- Inconsistent assessments — manual reviews are subject to reviewer variability
- Regulatory pressure — CMS mandates electronic PA by 2026–2027 with 72-hour urgent and 7-day standard response limits (CMS-0057-F)
By using the Prior Authorization Review — Multi-Agent Solution Accelerator, organizations can automate these processes, ensuring that all clinical reviews are accurately coordinated, auditable, and executed efficiently.
Click to learn more about what value this solution provides
-
Reduce review time from 20+ minutes to under 2 minutes
Compliance and Clinical agents run concurrently via parallel execution, dramatically reducing wall-clock time per case. -
Ensure consistency and auditability
Gate-based decision rubric with per-criterion MET/NOT_MET/INSUFFICIENT scoring eliminates reviewer variability and produces complete audit trails. -
Maintain human oversight
AI produces draft recommendations; human reviewers Accept or Override with documented rationale — every decision is traceable. -
Scale without proportional staffing
Stateless API design enables horizontal scaling behind a load balancer. Skills-based architecture lets domain experts update clinical rules without code changes. -
Meet regulatory requirements
Automated documentation generation (notification letters, audit PDFs) supports CMS compliance and payer reporting obligations.
Click to learn more about the prior authorization use case
| Scenario | Persona | Challenges | Solution Approach |
|---|---|---|---|
| PA intake triage | Utilization Review Nurse | Manually checking demographics, provider credentials, codes, and clinical notes quality for completeness is time-consuming and error-prone. | Compliance Agent validates all required documentation in seconds with a 10-item checklist: items 1-7 are blocking; item 9 flags NCCI CPT bundling risk; item 10 classifies service type (Procedure/Medication/Imaging/Device/Therapy/Facility) for downstream routing. |
| Clinical evidence review | Medical Director | Extracting structured clinical data, validating ICD-10 codes, and searching PubMed for supporting evidence takes 15–30 minutes per case. | Clinical Reviewer Agent automates clinical data extraction, code validation, and literature/trial search using MCP-connected healthcare data sources. |
| Coverage policy evaluation | PA Coordinator | Looking up Medicare NCDs/LCDs, mapping each policy criterion to clinical evidence, and documenting medical necessity assessments is manual and inconsistent. | Coverage Agent searches CMS coverage databases, verifies provider credentials, and produces auditable MET/NOT_MET/INSUFFICIENT criterion mappings. |
| Final decision synthesis | Clinical Reviewer | Combining findings from multiple reviewers into a consistent, auditable recommendation with confidence scoring requires significant coordination. | Orchestrator + Synthesis evaluates a gate-based rubric (Provider → Codes → Medical Necessity), produces a recommendation with confidence scores, and generates notification letters and audit PDFs. |
| Document | Description |
|---|---|
| Deployment Guide | Step-by-step deployment instructions — Docker Compose, local development, Azure Container Apps, prerequisites, environment configuration, troubleshooting |
| Architecture | Detailed hosted-agent-ready architecture, runtime modes, MCP integration, agent details, decision rubric, confidence scoring, and audit justification |
| API Reference | Full REST API documentation — review, decision, per-agent endpoints, request/response schemas, SSE events, error codes |
| Foundry Hosted Agents Plan | Saved migration plan for the lower-risk Foundry hosted-agent architecture (frontend ACA + backend/orchestrator ACA + 4 hosted agents) |
| Extending the Application | Step-by-step guides for adding new agents, MCP servers, changing the decision rubric, customizing notification letters |
| Technical Notes | Windows SDK patches, MCP header injection, hosted-agent dispatch, structured output, observability, and known limitations |
| Troubleshooting | Common issues and fixes — CLI failures, hosted-agent config/auth problems, connection errors, truncated responses, and Foundry trace issues |
| Production Migration | PostgreSQL schema, Azure Blob Storage layout, migration steps, environment variables, what not to change |
This solution accelerator is designed to be extended:
| Area | What to customize | Guide |
|---|---|---|
| Data persistence | Replace in-memory store with PostgreSQL / Cosmos DB | Production Migration |
| Authentication | Add identity management and RBAC | Custom implementation |
| Payer-specific policies | Extend with commercial and MA plan rules | Extending |
| EHR/EMR integration | Connect via FHIR or HL7 interfaces | Custom implementation |
| New agents | Add Pharmacy Benefits, Financial Review, etc. | Extending |
| New MCP servers | Add CPT validator, drug formulary, etc. | Extending |
| Decision rubric | Switch from LENIENT to STRICT mode | Extending |
| Notification letters | Match your organization's letterhead format | Extending |
| Compliance & security | HIPAA-compliant infrastructure, encryption | Custom implementation |
| Scalability | Azure Container Apps, Kubernetes | Deployment Guide |
This solution accelerator handles Protected Health Information (PHI) and clinical data. Security best practices are critical for any deployment.
This project uses keyless authentication throughout — no API keys, passwords, or connection strings are stored anywhere. All Azure resource access (Microsoft Foundry, Azure Container Registry, Azure Monitor) is authenticated via DefaultAzureCredential:
| Environment | Credential used | How it's granted |
|---|---|---|
| Azure (production) | System-assigned Managed Identity on each Container App; deployer user identity | Bicep role assignments at deploy time (CognitiveServicesOpenAIUser for backend, CognitiveServicesOpenAIContributor + Azure AI User for Foundry project MI, Azure AI User for deployer) |
| Local / Codespaces | Azure Developer CLI token (azd auth login) or Azure CLI token (az login) |
Developer's own authenticated session |
Because there are no API keys, there is nothing to rotate, leak, or accidentally commit. To ensure continued best practices in your own repository, we recommend enabling GitHub secret scanning to catch any credentials that might be inadvertently introduced.
You may want to consider additional security measures, such as:
- Enabling Microsoft Defender for Cloud to secure your Azure resources.
- Protecting the Azure Container Apps instance with a firewall and/or Virtual Network.
- Enabling encryption at rest for all data stores containing PHI.
- Implementing role-based access control (RBAC) to restrict who can submit, review, and override prior authorization decisions.
- Ensuring HIPAA compliance by signing a Business Associate Agreement (BAA) with Microsoft for production workloads.
Check out related solution accelerators from Microsoft
| Solution Accelerator | Description |
|---|---|
| Multi-Agent Custom Automation Engine | Build AI-driven orchestration systems that coordinate multiple specialized agents for complex business process automation |
| AutoAuth | Streamlining prior authorization with the AutoAuth Framework and Azure AI |
| Document Knowledge Mining | Extract structured information from unstructured documents using AI — applicable to clinical notes and medical records |
| Conversation Knowledge Mining | Derive insights from volumes of conversational data using generative AI — applicable to patient-provider interactions |
Want to get familiar with Microsoft's AI and Data Engineering best practices? Check out our playbooks to learn more:
| Playbook | Description |
|---|---|
| AI playbook | The Artificial Intelligence (AI) Playbook provides enterprise software engineers with solutions, capabilities, and code developed to solve real-world AI problems. |
| Data playbook | The data playbook provides enterprise software engineers with solutions which contain code developed to solve real-world problems. |
Have questions, find a bug, or want to request a feature? Submit a new issue on this repo and we'll connect.
Please refer to Transparency FAQ for responsible AI transparency details of this solution accelerator.
Caution
This is an AI-assisted triage tool. All recommendations are drafts that require human clinical review before any authorization decision is finalized. Coverage policies reflect Medicare LCDs/NCDs only — commercial and Medicare Advantage plans may differ.
This release is an artificial intelligence (AI) system that generates text based on user input. The text generated by this system may include ungrounded content, meaning that it is not verified by any reliable source or based on any factual data. The data included in this release is synthetic, meaning that it is artificially created by the system and may contain factual errors or inconsistencies. Users of this release are responsible for determining the accuracy, validity, and suitability of any content generated by the system for their intended purposes. Users should not rely on the system output as a source of truth or as a substitute for human judgment or expertise.
This release only supports English language input and output. Users should not attempt to use the system with any other language or format. The system output may not be compatible with any translation tools or services, and may lose its meaning or coherence if translated.
This release does not reflect the opinions, views, or values of Microsoft Corporation or any of its affiliates, subsidiaries, or partners. The system output is solely based on the system's own logic and algorithms, and does not represent any endorsement, recommendation, or advice from Microsoft or any other entity. Microsoft disclaims any liability or responsibility for any damages, losses, or harms arising from the use of this release or its output by any user or third party.
This release does not provide any financial advice, legal advice and is not designed to replace the role of qualified client advisors in appropriately advising clients. Users should not use the system output for any financial decisions, legal guidance or transactions, and should consult with a professional financial advisor and or legal advisor as appropriate before taking any action based on the system output. Microsoft is not a financial institution or a fiduciary, and does not offer any financial products or services through this release or its output.
This release is intended as a proof of concept only, and is not a finished or polished product. It is not intended for commercial use or distribution, and is subject to change or discontinuation without notice. Any planned deployment of this release or its output should include comprehensive testing and evaluation to ensure it is fit for purpose and meets the user's requirements and expectations. Microsoft does not guarantee the quality, performance, reliability, or availability of this release or its output, and does not provide any warranty or support for it.
This Software requires the use of third-party components which are governed by separate proprietary or open-source licenses as identified below, and you must comply with the terms of each applicable license in order to use the Software. You acknowledge and agree that this license does not grant you a license or other right to use any such third-party proprietary or open-source components.
To the extent that the Software includes components or code used in or derived from Microsoft products or services, including without limitation Microsoft Azure Services (collectively, "Microsoft Products and Services"), you must also comply with the Product Terms applicable to such Microsoft Products and Services. You acknowledge and agree that the license governing the Software does not grant you a license or other right to use Microsoft Products and Services. Nothing in the license or this ReadMe file will serve to supersede, amend, terminate or modify any terms in the Product Terms for any Microsoft Products and Services.
You must also comply with all domestic and international export laws and regulations that apply to the Software, which include restrictions on destinations, end users, and end use. For further information on export restrictions, visit https://aka.ms/exporting.
You acknowledge that the Software and Microsoft Products and Services (1) are not designed, intended or made available as a medical device(s), and (2) are not designed or intended to be a substitute for professional medical advice, diagnosis, treatment, or judgment and should not be used to replace or as a substitute for professional medical advice, diagnosis, treatment, or judgment. Customer is solely responsible for displaying and/or obtaining appropriate consents, warnings, disclaimers, and acknowledgements to end users of Customer's implementation of the Online Services.
You acknowledge the Software is not subject to SOC 1 and SOC 2 compliance audits. No Microsoft technology, nor any of its component technologies, including the Software, is intended or made available as a substitute for the professional advice, opinion, or judgment of a certified financial services professional. Do not use the Software to replace, substitute, or provide professional financial advice or judgment.
BY ACCESSING OR USING THE SOFTWARE, YOU ACKNOWLEDGE THAT THE SOFTWARE IS NOT DESIGNED OR INTENDED TO SUPPORT ANY USE IN WHICH A SERVICE INTERRUPTION, DEFECT, ERROR, OR OTHER FAILURE OF THE SOFTWARE COULD RESULT IN THE DEATH OR SERIOUS BODILY INJURY OF ANY PERSON OR IN PHYSICAL OR ENVIRONMENTAL DAMAGE (COLLECTIVELY, "HIGH-RISK USE"), AND THAT YOU WILL ENSURE THAT, IN THE EVENT OF ANY INTERRUPTION, DEFECT, ERROR, OR OTHER FAILURE OF THE SOFTWARE, THE SAFETY OF PEOPLE, PROPERTY, AND THE ENVIRONMENT ARE NOT REDUCED BELOW A LEVEL THAT IS REASONABLY, APPROPRIATE, AND LEGAL, WHETHER IN GENERAL OR IN A SPECIFIC INDUSTRY. BY ACCESSING THE SOFTWARE, YOU FURTHER ACKNOWLEDGE THAT YOUR HIGH-RISK USE OF THE SOFTWARE IS AT YOUR OWN RISK.
