Talos
The AI Control Plane for Data Platforms
Talos allows teams to interact with DataForge through natural language while operating entirely within the constraints defined by Alloy and Ember.
It lowers the barrier to building and operating data pipelines without introducing new patterns, risks, or ambiguity into the platform.
Talos is not an autonomous system making decisions on its own. Instead, it translates intent into structured actions that must pass the same validation and enforcement applied to every change in the platform.
This makes Talos practical in large, complex data environments where predictability and correctness matter more than novelty.
When Automation Is Almost Right
AI works well when tasks are low risk or easily reversible.
Data platforms are neither.
When an AI system is correct most of the time but wrong often enough, teams either ignore it entirely or over-trust it. In data systems, that gap creates silent errors, compounding complexity, and outcomes that are expensive to unwind.
“In data platforms, being wrong twenty percent of the time is not acceptable.”
The problem is not the AI.
The problem is asking automation to operate inside systems that were never designed to be understood or constrained.
When structure, intent, and execution are implicit, automation has no choice but to guess. That is what turns useful assistance into chaos.
Unconstrained Platforms
Automation infers structure
Errors propagate quietly
DataForge Platforms
Structure is enforced
Errors are caught immediately
Talos works because it operates inside these constraints.
Natural language becomes a safe interface only when the system underneath is deterministic, explicit, and enforced by design.
Talos in Action
Talos allows users to express requirements in natural language while the platform enforces structure, validation, and execution.
This short demo shows how intent is translated into Ember definitions and executed through Alloy without introducing new patterns or bypassing constraints.
Talos succeeds because it operates inside the same system that keeps large teams aligned.
Built on Structure, Not Guesswork
Talos works because the platform underneath it was designed to scale safely.
Alloy enforces a single execution architecture.
Ember defines logic in explicit, prescriptive structures.
Talos builds on that foundation by lowering the interface cost, not the standards. It allows teams to express intent in natural language while relying on the same constraints that keep large, complex data platforms aligned.
This is what makes AI usable in environments where correctness matters more than novelty.
When logic is declarative and structure is enforced, automation becomes reliable.
Talos is designed for platforms built on that foundation.