Flexible Engagement Models
From dedicated teams to project-based pods, we adapt to your needs - delivering AI solutions that scale with your business.
Dedicated FDE Teams
Full-time embedded engineering teams that become an extension of your in-house capabilities.
- Outcome-Driven AI Execution
- Full-Lifecycle Ownership
- Secure Enterprise Integration
- Stakeholder-Aligned Collaboration
- Ongoing Performance Optimization
Best for: Companies needing sustained AI engineering capacity without permanent hires.
Project-Based Pods
Scoped deliverables with fixed timelines and clear milestones for predictable outcomes.
- Sprint-based delivery cycles
- Fixed-scope contracts & pricing
- Milestone tracking & reporting
- Dedicated project manager
- Quality assurance reviews
Best for: Organizations with well-defined projects needing reliable delivery on time and budget.
Startup Accelerator
Rapid prototyping and MVP delivery for AI startups that need to move from idea to market quickly.
- MVP scoping & architecture
- Rapid prototyping sprints
- Investor-ready demos
- Scalable cloud infrastructure
- Go-to-market technical support
Best for: AI startups scaling from seed to Series A and beyond.
Enterprise Integration Pods
Connect your AI capabilities to existing enterprise systems with robust, scalable API architectures.
- API design & development
- Legacy system modernization
- Real-time data streaming
- Security & compliance hardening
- Performance optimization
Best for: Organizations needing AI woven into complex existing infrastructure.
AI Implementation Pods
End-to-end AI solution delivery with dedicated cross-functional teams that embed into your organization.
- Custom model development & fine-tuning
- Production-grade ML pipeline setup
- Data engineering & feature stores
- MLOps & monitoring infrastructure
- Knowledge transfer & documentation
Best for: Enterprises launching new AI products or modernizing legacy systems.
LLM Foundry
Custom model training, fine-tuning, and prompt engineering to build AI tailored to your domain.
- Custom model training & fine-tuning
- Advanced prompt engineering
- Fine-tuning pipeline automation
- Model evaluation frameworks
- Deployment & inference optimization
Best for: Enterprises needing domain-specific AI models that outperform generic solutions.