Qualifying Questions

Discovery questions to identify prospect needs, pain points, and alignment with OpenRails capabilities. Use these during initial conversations to qualify opportunities.

Current AI Usage & Pain Points

Are you currently using any AI or machine learning tools in your organization?

If so, which tools, and what tasks do they handle? What is working well, and what is not?

Why ask: Establishes baseline and identifies gaps OpenRails can fill.

What are the biggest manual or repetitive processes that consume your team's time?

Think about report generation, data entry, document processing, ticket routing, or information lookup.

Why ask: Identifies automation opportunities for agent orchestration.

How do your employees currently access institutional knowledge?

Do they search a wiki, ask colleagues, dig through file shares, or rely on tribal knowledge?

Why ask: Reveals the value proposition for RAG and knowledge management.

Have you encountered challenges with AI accuracy, hallucination, or trustworthiness?

How do you currently validate AI-generated outputs?

Why ask: Positions OpenRails' sourced answers, evaluation framework, and HITL capabilities.

Are you concerned about vendor lock-in with your current AI provider?

Have you experienced pricing changes, feature deprecations, or API instability?

Why ask: Highlights the multi-LLM advantage and provider flexibility.

Data & Compliance

What types of sensitive data does your organization handle?

PII, PHI, financial records, legal documents, intellectual property, classified information?

Why ask: Determines the need for security levels, PII pipelines, and encryption.

Are you subject to specific regulatory frameworks?

HIPAA, SOX, GDPR, FedRAMP, ITAR, or industry-specific regulations?

Why ask: Identifies compliance requirements that drive on-premise and governance features.

What are your requirements for data residency and sovereignty?

Must data remain in a specific country, on specific infrastructure, or within a specific network boundary?

Why ask: Positions on-premise deployment and air-gap capability.

Do you have an existing data classification policy?

How do you currently classify and label documents by sensitivity? How many classification levels do you use?

Why ask: Maps to OpenRails' tiered security controls and governance framework.

Integration Landscape

What are the primary systems and platforms your teams use daily?

Project management, CRM, ERP, file storage, communication, databases?

Why ask: Identifies connector requirements and integration scope.

Do you have internal APIs or services that you would want to connect to an AI platform?

REST APIs, internal microservices, legacy SOAP services, database direct access?

Why ask: Assesses custom integration needs via MCP and the REST API connector.

Are there internal portals or applications where embedded AI assistance would be valuable?

Intranets, customer portals, helpdesk interfaces, operational dashboards?

Why ask: Positions the widget embedding capability.

What identity and authentication systems do you use?

Active Directory, Azure AD, Okta, custom SSO, LDAP?

Why ask: Determines authentication integration requirements for the OpenRails platform.

Scale & Requirements

How many users would need access to the AI platform?

Consider both active power users and occasional users. Are there external users (customers, partners) who would use embedded widgets?

Why ask: Sizes the deployment and licensing requirements.

What is the volume of documents and data you would want to ingest?

Thousands of documents? Terabytes of data? Growing at what rate?

Why ask: Determines infrastructure sizing and data lake architecture needs.

What does your current infrastructure look like?

On-premise data centers, cloud (AWS/Azure/GCP), hybrid? Do you have GPU-equipped servers available?

Why ask: Determines deployment model and local LLM feasibility.

Budget & Timeline

Is there an allocated budget for AI/automation initiatives this fiscal year?

Has the organization already approved spending, or is this an exploratory conversation?

Why ask: Gauges buying stage and urgency.

What is your target timeline for deploying an AI solution?

Are you looking to pilot within weeks, deploy within a quarter, or planning for next fiscal year?

Why ask: Aligns engagement approach (quick POC vs. extended evaluation).

Who are the key stakeholders and decision-makers for this initiative?

IT leadership, business unit heads, procurement, compliance/legal, executive sponsor?

Why ask: Maps the buying committee and identifies which benefit pages to share.

Next Steps After Discovery

Based on responses, share the most relevant resources:

Technical buyer: CTO Benefits + Multi-LLM White Paper
Ops-focused: Operations Benefits + Agent Orchestration Demo
Compliance-driven: Compliance Benefits + Governance White Paper
Business user champion: Business User Benefits + Chat & RAG Demo