The Stakes: Why Platform Selection Matters

Selecting the wrong AI platform can cost enterprises millions in:

❌ Costly Mistakes

• 6-12 month failed implementations ($500K-2M lost)
• Vendor lock-in with expensive licensing
• Brittle systems requiring constant maintenance
• Poor ROI from limited capabilities
• Team burnout from overly complex platforms

✅ Smart Selection Benefits

• Rapid deployment (weeks not months)
• 3-4x ROI in year 1
• 60-75% productivity gains
• Scalable to 10,000+ users
• Business user adoption without coding

10 Critical Evaluation Criteria

1. Intelligence Level: AI vs Automation

Why It Matters: Traditional automation follows rules. True AI understands context, handles ambiguity, and makes autonomous decisions.

Key Questions to Ask:

✓ Can the platform process unstructured data (emails, documents, conversations)?
✓ Does it make autonomous decisions or just follow if-then rules?
✓ Can it handle exceptions without breaking workflows?
✓ Does it learn and improve from interactions?
✓ Can users interact via natural language vs building flows?

🏆 Lumay Advantage: True agentic AI with autonomous decision-making, RAG-powered knowledge processing, and natural language interface—not rule-based automation.

2. Integration Capabilities

Why It Matters: AI platform must connect seamlessly with your existing tech stack (CRM, ERP, communication tools, databases).

Key Questions to Ask:

✓ Does it integrate natively with Microsoft 365 / Dynamics 365 / Salesforce?
✓ What APIs and connectors are available?
✓ Can it access on-premise systems securely?
✓ Does it support custom integrations via REST APIs?
✓ What about legacy system connectivity?

🏆 Lumay Advantage: Native Microsoft 365/Dynamics 365 integration, pre-built connectors for major systems, REST API for custom integrations.

3. Enterprise Scalability

Why It Matters: Platform must scale from pilot (10 users) to enterprise-wide deployment (10,000+ users) without performance degradation.

Key Questions to Ask:

✓ What's the largest customer deployment? (Users & transaction volume)
✓ Are there usage limits or throttling?
✓ Does pricing scale linearly or exponentially?
✓ What's the platform's uptime SLA?
✓ Can it handle peak loads (month-end, year-end)?

🏆 Lumay Advantage: Proven at 10,000+ user deployments, 99.9% uptime SLA, no usage throttling, linear pricing.

4. Pricing Transparency & TCO

Why It Matters: Hidden costs (implementation, premium features, support, API calls) can triple your budget.

Key Questions to Ask:

✓ What's the all-in per-user cost including support?
✓ Are there extra charges for AI features, connectors, or API calls?
✓ What are typical implementation costs?
✓ What's included in base price vs premium tiers?
✓ Are there annual minimum commitments?

🏆 Lumay Advantage: Simple $50/user/month all-inclusive pricing. No hidden fees, premium connectors, or API charges. Support included.

5. Implementation Speed & Complexity

Why It Matters: 6-month implementations delay ROI and frustrate stakeholders. Faster deployment = faster value realization.

Key Questions to Ask:

✓ What's typical pilot-to-production timeline?
✓ Do we need developers or can business users configure?
✓ What's the learning curve for administrators?
✓ Are pre-built templates available for common use cases?
✓ What implementation support is provided?

🏆 Lumay Advantage: Deploy in days (not months). Business-user friendly. Pre-built agents for common workflows. Dedicated implementation support.

6. Security & Compliance

Why It Matters: AI platforms access sensitive data. Non-compliant solutions risk regulatory fines and data breaches.

Key Questions to Ask:

✓ What certifications does the vendor hold? (SOC 2, ISO 27001, HIPAA, GDPR)
✓ Where is data stored and processed?
✓ Is on-premise/private cloud deployment available?
✓ How is data encrypted (in transit and at rest)?
✓ What's the data retention policy?

🏆 Lumay Advantage: SOC 2 Type II, HIPAA, GDPR, ISO 27001 compliant. On-premise deployment available. End-to-end encryption.

7. Support Quality & SLAs

Why It Matters: When AI agents fail in production, you need responsive support—not email-only tickets with 48-hour response times.

Key Questions to Ask:

✓ What support channels are available? (Phone, chat, email)
✓ What are response time SLAs for critical issues?
✓ Is 24/7 support included or extra cost?
✓ Who provides implementation support?
✓ What training resources are available?

🏆 Lumay Advantage: 24/7 support included. Phone + chat + email. <1hr response for critical issues. Dedicated success manager.

8. Vendor Stability & Roadmap

Why It Matters: AI is rapidly evolving. Your vendor must invest in R&D and have a clear vision for the future.

Key Questions to Ask:

✓ How long has the company been in business?
✓ What's the customer count and retention rate?
✓ Is the company profitable or VC-funded?
✓ What's the product roadmap for next 12-24 months?
✓ How often are new features released?

🏆 Lumay Advantage: Founded 2020, 95%+ customer retention, profitable, quarterly feature releases, clear roadmap with multi-agent orchestration.

9. Customization vs Out-of-Box

Why It Matters: Balance is key. Too rigid = limited use cases. Too flexible = complexity and long implementations.

Key Questions to Ask:

✓ What pre-built agents/templates are available?
✓ Can we customize workflows without coding?
✓ Is custom AI model training required?
✓ Can we extend with custom code if needed?
✓ How much configuration is typical for common use cases?

🏆 Lumay Advantage: 8 pre-built Smart products for instant deployment. Low-code customization. API for advanced extensions when needed.

10. References & Proof Points

Why It Matters: Vendor claims mean nothing. Customer references and case studies provide real-world validation.

Key Questions to Ask:

✓ Can you provide 3 customer references in our industry?
✓ What ROI have similar customers achieved?
✓ Are there published case studies with metrics?
✓ Can we visit a customer site or do a reference call?
✓ What's the typical implementation success rate?

🏆 Lumay Advantage: Customer references available. Published case studies showing 3-4x ROI, 60-75% productivity gains, 95%+ satisfaction.

Evaluation Framework: Scorecard

Use this scorecard to objectively compare platforms (1-5 scale, 5 = best):

Criteria	Weight	Platform A	Platform B	Platform C
Intelligence Level	15%	___	___	___
Integration Capabilities	12%	___	___	___
Enterprise Scalability	10%	___	___	___
Pricing Transparency & TCO	12%	___	___	___
Implementation Speed	10%	___	___	___
Security & Compliance	12%	___	___	___
Support Quality & SLAs	10%	___	___	___
Vendor Stability & Roadmap	8%	___	___	___
Customization vs OOTB	6%	___	___	___
References & Proof Points	5%	___	___	___
TOTAL SCORE	100%	___	___	___

Calculate weighted score: (Score × Weight) for each criterion, then sum for total score out of 5.0

Common Pitfalls to Avoid

❌ Choosing Based on Brand Name Only

Big brands don't always mean best fit. Evaluate actual capabilities, not marketing.

❌ Focusing Only on Price

Cheap upfront costs hide expensive implementation, maintenance, and licensing complexity. Evaluate TCO.

❌ Skipping the Pilot Phase

Always run a 2-4 week pilot before enterprise commitment. Validate claims with real workflows.

❌ Ignoring User Adoption

Complex platforms require extensive training, leading to poor adoption. Prioritize usability.

❌ Not Planning for Scale

Platform that works for 10 users may fail at 1,000 users. Validate scalability early.

Next Steps: Evaluation Process

1
Define Requirements: Document must-have vs nice-to-have features, budget constraints, timeline expectations
2
Shortlist Vendors: Research 3-5 platforms that match your core requirements
3
Demo & Evaluate: Use the 10-criteria scorecard to objectively compare platforms
4
Check References: Speak with 2-3 customers in similar industries and company sizes
5
Run Pilot: 2-4 week proof-of-concept with 1-2 use cases and 10-20 users
6
Measure Results: Evaluate pilot ROI, user satisfaction, implementation ease
7
Negotiate & Deploy: Finalize pricing, SLAs, support terms, then roll out enterprise-wide

How to Choose an AI Platform for Enterprise

Quick Summary

The Stakes: Why Platform Selection Matters

❌ Costly Mistakes

✅ Smart Selection Benefits

10 Critical Evaluation Criteria

1. Intelligence Level: AI vs Automation

Key Questions to Ask:

2. Integration Capabilities

Key Questions to Ask:

3. Enterprise Scalability

Key Questions to Ask:

4. Pricing Transparency & TCO

Key Questions to Ask:

5. Implementation Speed & Complexity

Key Questions to Ask:

6. Security & Compliance

Key Questions to Ask:

7. Support Quality & SLAs

Key Questions to Ask:

8. Vendor Stability & Roadmap

Key Questions to Ask:

9. Customization vs Out-of-Box

Key Questions to Ask:

10. References & Proof Points

Key Questions to Ask:

Evaluation Framework: Scorecard

Common Pitfalls to Avoid

❌ Choosing Based on Brand Name Only

❌ Focusing Only on Price

❌ Skipping the Pilot Phase

❌ Ignoring User Adoption

❌ Not Planning for Scale

Next Steps: Evaluation Process

Ready to Evaluate Lumay?

FAQs

How long should the evaluation process take?

Should we hire a consultant to help with selection?

What if we choose the wrong platform?