A Proven Methodology for AI Success
Our 6-step process ensures AI projects deliver real business value—not just impressive models.
Discover
Understand your business, challenges, and objectives
Timeline
1-2 weeks
Key Activities:
- Stakeholder interviews
- Current state assessment
- Success criteria definition
- Technical landscape review
Assess
Evaluate data readiness and technical feasibility
Timeline
1-2 weeks
Key Activities:
- Data quality audit
- Infrastructure assessment
- AI/ML opportunity identification
- ROI modeling and business case
Design
Create solution architecture and implementation roadmap
Timeline
2-3 weeks
Key Activities:
- Solution architecture design
- Technology stack selection
- Data pipeline design
- Risk assessment and mitigation
Build
Develop, train, and test AI/ML models and systems
Timeline
4-8 weeks
Key Activities:
- Data engineering and preparation
- Model development and training
- Integration with existing systems
- Unit and integration testing
Deploy
Launch solution to production with monitoring
Timeline
1-2 weeks
Key Activities:
- Production deployment
- User training and documentation
- Monitoring setup
- Performance validation
Optimize
Continuously improve performance and outcomes
Timeline
Ongoing
Key Activities:
- Performance monitoring
- Model retraining and tuning
- Feature enhancements
- Impact measurement
What to Expect
Most projects move from Discover to Deploy in 8-16 weeks. Simpler engagements can be faster; complex enterprise implementations may take longer. We'll provide a detailed timeline during the Assess phase.
The key to success? Start with a focused use case, prove value, then scale. We'd rather deliver one high-impact solution than overpromise on ten.
Common Questions
How long does a typical project take?
Most project-based engagements take 8-16 weeks from kickoff to deployment. Timeline varies based on scope, complexity, and data readiness.
What if our data isn't ready?
We'll identify data gaps during the Assess phase and can include data preparation as part of the project scope. Many clients need help with data infrastructure before jumping into AI/ML.
How involved do we need to be?
We need access to key stakeholders for the Discover phase (4-8 hours) and periodic check-ins throughout the project. We handle the heavy lifting but need your domain expertise and feedback.
What happens after deployment?
All projects include 30 days of post-launch support. For ongoing monitoring, optimization, and enhancements, we offer retainer-based support agreements.