What We Build
Four service lines. One philosophy: build what works, skip what doesn't.
AI Readiness Assessment
Know before you build.
We audit your data, infrastructure, and workflows to find where AI actually adds value — and where it doesn't. No sales pitch, just an honest roadmap.
- Data quality & availability audit
- Infrastructure readiness review
- Use case prioritization matrix
- Build vs. buy analysis
- 12-week implementation roadmap
Best for
Best for teams exploring AI for the first time or recovering from a failed initiative.
AI Integration & Development
From prototype to production.
We design, build, and integrate AI and ML systems into your existing stack. RAG pipelines, fine-tuned models, custom ML models, agent workflows — whatever the use case demands.
- Custom RAG pipeline development
- Model fine-tuning & optimization
- Custom ML & predictive pipelines
- Agent workflow orchestration
- API & system integration
- Testing & evaluation frameworks
Best for
Best for teams with a clear use case ready for production-grade implementation.
AI Operations & Monitoring
Ship it. Keep it running.
Production AI breaks in ways traditional software doesn't. We build the observability, evaluation, and incident response systems that keep your AI reliable.
- Model performance monitoring
- Drift detection & alerting
- ML pipeline orchestration
- A/B testing infrastructure
- Cost optimization & scaling
- Incident response playbooks
Best for
Best for teams with AI in production that need reliability and observability.
AI Infrastructure
Bare metal to cloud.
GPU clusters, training pipelines, inference optimization — we build the foundation that makes everything else possible. On-prem, cloud, or hybrid.
- GPU cluster provisioning
- Training pipeline architecture
- Inference optimization & caching
- Multi-cloud deployment
- Cost modeling & capacity planning
Best for
Best for teams running large-scale AI workloads that need infrastructure expertise.