Engineered agentic AI systems
We help engineering teams design and operationalize AI agents that behave predictably under real conditions.
Focus
- Agent workflow architecture
- Structured memory (local, team, project)
- Skill codification inside your stack
- Model tradeoff evaluation under real workloads
- Slop loop prevention
- Cost and token discipline
Code-first. Production-minded.
Engagements
- Executive Briefing - capabilities and limits of agentic systems.
- Engineering Workshop - live design of workflows and memory models.
- Hands-On Lab - implement inside existing infrastructure.
- Advisory - production-grade AI system design.
Approach
AI systems fail when tasks are underspecified, memory is implicit, orchestration is nondeterministic, or cost is ignored.
We design for explicit decomposition, deterministic control, clear memory boundaries, and reproducibility.
Contact
Email: chirayu@corantor.com