01
Understand the request
Use an LLM to interpret intent and turn a conversation into proposed structured inputs.
AI & research / Governed AI & automation
Flexible intelligence.
Accountable execution.
Combining language-model reasoning with deterministic workflows, validation, permissions and operational evidence.
Product engineering & research
The question
A practical starting point.
A useful AI system needs more than a fluent answer. It needs an understood scope, a controlled way to act and a result that people can check.
The approach
What we’re exploring.
02
Validate and execute
Use defined code, workflows and policy checks to validate parameters and carry out permitted actions.
03
Explain the result
Let a model help communicate the outcome, grounded in the actual execution record rather than an assumed success.
04
Keep the evidence
Retain the context, decisions, run status and outputs needed to investigate the work and review the result.
Work with Gala Arch
Let’s explore the question.
Interested in a practical AI use case, a research collaboration or an evaluation? Tell us what you want to learn.