The path to super-aligned agents starts with System Two thinking.
We build safer, structured agents using knowledge graphs, model testing, and grounding pipelines — ensuring AI systems reason before they act.
We build safer, structured agents using knowledge graphs, model testing, and grounding pipelines — ensuring AI systems reason before they act.
We build agentic systems that think before they act — guided by structured context, memory, and goal-awareness.
From hallucination stress-tests to alignment audits, our benchmarks surface failure modes others miss.
We integrate with enterprise knowledge graphs, refine assistant workflows, and help you deploy safe AI at scale.
We test retrieval-augmented generation agents for factual consistency, grounding, and knowledge drift — especially under long or ambiguous queries.
We simulate complex goal conditions and assess how agents perform multi-step planning, tool use, and intent alignment across time.
We help clients inject enterprise knowledge into LLM workflows using structured context graphs, enabling safe and accurate assistant responses.
System Two AI helps the world build safer, more deliberate AI systems. Inspired by the psychology of reflective reasoning, we focus on agent alignment through structured knowledge, goal-grounding, and robust model evaluation. We aim to reduce hallucinations, improve trustworthiness, and help organizations deploy intelligent agents that actually understand their goals.
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