According to MIT, 95% of AI Projects fail.
Trusted by Global Leaders
The big 'reliability' problem
MIT Challenge Program
Our promise to you $50,000
If your Lyzr agent doesn't make it to production within 90 days, we'll pay you $50,000. The Lyzr Guarantee.
- Apply and Get Qualified
1
- You must be from a Fortune 5000 Organization & a decision maker with an approved budget.
- Discuss Scope
2
- Brainstorm with us & sign off on the scope and success metrics.
- Sign MSA
3
- We will sign a $0 service agreement to initiate the partnership
- Build with our Lyzr Solution Specialists
4
- We will deliver over the next 3 months with bi-weekly sprint cycles & weekly cadence calls.
- Go live or Get Paid
5
- On a successful outcome convert to an annual enterprise plan & become a reference able customer. Otherwise we pay you $50,000 for time and effort.
Why Lyzr ? Your
enterprise AI advantage.
Here’s why leading organizations choose Lyzr for their most critical AI initiatives, transforming challenges into tangible business.
Get to production fast
Agents go live in days, not quarters
Fully Private
Own your data & IP
Your data stays where it belongs – with you.
Safe & Responsible AI
Compliance, guardrails, full traceability baked in.
Flexible deployment
LLM-agnostic, any cloud or on-prem, plug-and-play with your stack.
What Can You Build With Lyzr? (Pre-Built Agents)
See what industry leaders are building on Lyzr
95% of AI projects fail. Yours won't.
Be the 5% with Lyzr's MIT Challenge program
Frequently asked questions
Everything you need to know about the MIT Challenge program and deploying AI agents with Lyzr
To qualify for the MIT Guarantee program, you must meet the following criteria:
- Decision-making authority: You must be a decision maker with budget approval within your organization
- Company size: Your organization must be a Fortune 5000 company
- Commitment level: You must be able to define clear outcomes and decide on project scope
- Pilot participation: Willingness to engage in a 3-month pilot program with bi-weekly sprints
- Success commitment: If we meet the agreed outcomes, you must be prepared to convert the pilot into either a success story case study and/or an annual contract
The program is designed for enterprise leaders who are serious about implementing AI agents in production and have the authority to make strategic technology decisions.
Our standard deployment follows a structured 90-day timeline:
Month 1 (Days 1-30): Foundation & Planning
- Requirements gathering and outcome definition
- Technical architecture planning with your team
- Initial agent design and workflow mapping
- Integration planning with existing systems
Month 2 (Days 31-60): Development & Testing
- Agent development using our pre-built components
- Bi-weekly sprint reviews and iterations
- Integration with your existing AI/CRM stacks
- Initial testing and refinement
Month 3 (Days 61-90): Production Deployment
- Final testing and quality assurance
- Production deployment and monitoring
- Performance optimization
- Success metrics validation
Our Forward Deployment Engineers work alongside your team throughout this process to ensure rapid, successful implementation.
Data privacy and compliance are core to our platform design:
Built-in Guardrails
- PII (Personally Identifiable Information) protection by design
- Toxicity filtering and fairness controls
- Automated compliance monitoring
Deployment Flexibility
- SaaS: Secure cloud deployment with enterprise-grade security
- On-premises: Complete data control within your infrastructure
- Hybrid: Combine cloud convenience with on-prem security for sensitive data
Compliance Standards
- SOC 2 Type II compliance
- GDPR and CCPA ready
- Industry-specific compliance support (HIPAA, PCI-DSS, etc.)
- Regular security audits and penetration testing
Data Governance
- Your data remains your data - we don't train on your proprietary information
- Transparent data usage policies
- Option for air-gapped deployments for maximum security
The $50,000 guarantee amount is strategically calculated based on:
Industry Investment Recovery
- Represents the typical cost of a failed AI pilot project
- Covers internal resource allocation and opportunity cost
- Compensates for time-to-market delays
Risk Mitigation
- Demonstrates our confidence in successful deployment
- Provides meaningful financial protection for your investment
- Encourages serious commitment from both parties
Market Positioning
- Reflects the value of crossing from the 95% who fail to the 5% who succeed
- Covers the cost of exploring alternative solutions if we don't deliver
- Substantial enough to ensure we're fully committed to your success
This amount strikes the right balance between meaningful compensation and responsible business practice, ensuring both parties are invested in achieving production deployment.
Absolutely! Agent interoperability is one of our core strengths:
Native Integrations
- Salesforce: Full integration with Agentforce and Einstein
- Microsoft: Seamless connection with Dynamics 365 and Copilot
- HubSpot: Marketing and sales automation integration
- CrewAI: Multi-agent workflow orchestration
- Dify: Low-code AI application development
API-First Architecture
- RESTful APIs for custom integrations
- Webhook support for real-time data sync
- GraphQL endpoints for flexible data queries
- Standard authentication protocols (OAuth, SAML, API keys)
Data Flow Management
- Bi-directional data synchronization
- Real-time updates and notifications
- Batch processing for large data sets
- Error handling and retry mechanisms
Existing Workflow Enhancement
- Augment current processes without disruption
- Leverage existing user permissions and roles
- Maintain current reporting and analytics
- Preserve established business logic
Our satisfaction guarantee is comprehensive and straightforward:
Performance Evaluation
- Success metrics are clearly defined upfront during the planning phase
- Bi-weekly sprint reviews allow for continuous adjustment and improvement
- Objective performance measurements against agreed KPIs
If We Don't Meet Agreed Outcomes
- You receive the full $50,000 compensation
- All development work and intellectual property transfers to you
- No additional fees or penalties
- Complete project documentation provided
Before We Reach That Point
- Our Forward Deployment Engineers work closely with your team to ensure success
- Regular check-ins and course corrections throughout the 90-day period
- Access to our full technical support and optimization services
- Flexibility to adjust scope and approach based on learnings
Success Definition
- Clear, measurable outcomes established at project start
- Production deployment with active user adoption
- Achievement of defined ROI or efficiency metrics
- Stakeholder satisfaction with agent performance
Yes, we provide comprehensive multi-language and global deployment support:
Language Capabilities
- Support for 50+ languages including English, Spanish, French, German, Japanese, Mandarin, Hindi, and more
- Native language processing for region-specific nuances
- Multi-language conversation handling within the same agent
- Localized UI and user experience
Global Infrastructure
- Multi-region cloud deployment options
- Local data residency compliance
- Regional security and privacy law adherence
- Low-latency deployment in major global markets
Cultural Adaptation
- Region-specific business logic and workflows
- Local compliance and regulatory requirements
- Cultural sensitivity in agent interactions
- Time zone aware scheduling and operations
International Support
- 24/7 global support coverage
- Regional Forward Deployment Engineers
- Local partnership and integration support
- Multi-currency and multi-timezone operations
While LLM providers offer powerful models, Lyzr provides the complete production-ready infrastructure:
Beyond Just Models
- LLM Providers: Raw language models requiring extensive custom development
- Lyzr: Complete agent platform with pre-built production capabilities
Production Readiness
- LLM Providers: No built-in guardrails, monitoring, or enterprise features
- Lyzr: Responsible AI by design, hallucination management, memory systems
Integration Complexity
- LLM Providers: Custom integration work for each business system
- Lyzr: Pre-built integrations with major enterprise platforms
Reliability & Trust
- LLM Providers: No fact-checking or output validation systems
- Lyzr: Built-in hallucination manager with fact-checking and reflection
Speed to Market
- LLM Providers: 6-12 months typical development cycle
- Lyzr: 90-day production deployment with our Forward Deployment Engineers
Ongoing Optimization
- LLM Providers: Static implementation requiring manual updates
- Lyzr: Memory and feedback loops for continuous improvement
Enterprise Features
- LLM Providers: Basic API access
- Lyzr: Complete enterprise stack with security, compliance, and governance
Forward Deployment Engineer support is comprehensive and hands-on throughout your journey:
Pre-Deployment Phase
- Requirements analysis and solution architecture
- Technical feasibility assessment
- Integration planning with existing systems
- Custom workflow design and optimization
Development Phase
- Dedicated engineer assigned to your project
- Bi-weekly sprint planning and review sessions
- Real-time development collaboration
- Custom agent training and fine-tuning
Implementation Support
- On-site or remote deployment assistance
- System integration and testing
- User training and change management support
- Performance optimization and tuning
Post-Deployment
- 30-day production monitoring and support
- Performance analysis and optimization recommendations
- Issue resolution and troubleshooting
- Knowledge transfer to your internal team
Ongoing Partnership
- Best practices sharing and recommendations
- Future enhancement planning
- Scale-up guidance and support
- Access to latest platform updates and features
Yes, we offer flexible engagement models to meet your comfort level:
Proof of Concept (2-4 weeks)
- Limited scope demonstration of specific use case
- Small-scale testing with sample data
- Basic integration with one primary system
- Evaluation criteria and success metrics definition
Mini-Pilot (4-6 weeks)
- Focused on single department or workflow
- Limited user group testing
- Basic production simulation
- Foundation for larger implementation
Standard Pilot (90-day MIT Guarantee)
- Full production deployment
- Complete integration across relevant systems
- Comprehensive user adoption
- Maximum risk mitigation with guarantee
Pilot Benefits
- Lower initial investment and risk
- Proof of value before larger commitment
- Learning and refinement opportunity
- Foundation for scaling across organization
Transition Path
- Successful pilots can seamlessly scale to full production
- Learnings from smaller engagements inform larger deployments
- Investment in pilot phases counts toward larger program costs
- No penalty for starting smaller and scaling up
ROI and success metrics vary by use case, but here are typical outcomes:
Quantitative ROI Examples
- Sales Productivity: 40% increase in SDR efficiency (documented case)
- Compliance Cost Reduction: $1M annual savings in compliance operations
- Processing Speed: 70% reduction in document processing time
- Customer Response Time: 85% improvement in first response times
Success Measurement Framework
- Efficiency Metrics: Task completion time, throughput improvement, error reduction
- Cost Savings: Labor cost reduction, operational expense optimization, compliance cost savings
- Revenue Impact: Sales conversion improvement, customer satisfaction increase, new revenue opportunities
- User Adoption: Active user percentage, daily/weekly usage rates, user satisfaction scores
Typical ROI Timeline
- Month 1-3: Baseline establishment and initial gains
- Month 4-6: 150-300% ROI typically achieved
- Month 7-12: 300-500% ROI with optimization and scaling
- Year 2+: Continued improvement through agent learning and expansion
Custom Success Metrics
- Defined collaboratively during planning phase
- Aligned with your business objectives
- Measurable and time-bound targets
- Regular monitoring and reporting
Risk Mitigation
- Clear success criteria established upfront
- Regular checkpoint reviews and adjustments
- Guarantee protection if targets aren't met
- Continuous optimization for sustained ROI growth
Our approach to agent training and knowledge management is comprehensive and adaptive:
Initial Knowledge Setup
- Import existing knowledge bases and documentation
- Connect to current systems and databases
- Custom training on your specific business processes
- Industry-specific pre-trained models and workflows
Continuous Learning Architecture
- Memory Systems: Agents remember past interactions and improve over time
- Feedback Loops: User corrections and ratings continuously refine responses
- Performance Monitoring: Real-time tracking of accuracy and effectiveness
- Automated Optimization: Regular model updates based on usage patterns
Knowledge Management Features
- Version Control: Track changes and updates to knowledge base
- Source Attribution: Transparent citation of information sources
- Confidence Scoring: Agents indicate certainty levels in responses
- Knowledge Gaps Identification: System identifies areas needing additional training
Training Methodologies
- Supervised Learning: Expert-guided training for specific domains
- Reinforcement Learning: Reward-based improvement from user interactions
- Transfer Learning: Leverage pre-trained models for faster deployment
- Active Learning: Intelligent identification of high-value training opportunities
Governance and Quality Control
- Human-in-the-Loop: Expert review for critical decisions
- Bias Detection: Ongoing monitoring for fairness and accuracy
- Compliance Training: Ensure adherence to regulatory requirements
- Performance Benchmarking: Regular evaluation against industry standards
Knowledge Maintenance
- Regular knowledge base updates and refreshes
- Automated detection of outdated information
- Collaborative editing and review processes
- Integration with existing knowledge management systems
