L0 — Token I/O Inference Core

Precision control over AI output behavior.

Fine-Tuned Generation Control

Decoding Parameters control how AI models generate text — the balance between creativity and consistency, the length and structure of outputs, and the sampling strategies used during generation. Different enterprise tasks require different generation profiles: legal document review demands high consistency while brainstorming sessions benefit from more creative exploration.

What Decoding Params delivers

01

Task-Tuned Profiles

Pre-configured parameter sets for different task types. Analytical tasks use low temperature for consistency. Creative tasks use higher temperature for diversity.

02

Output Structuring

Control output format through structured generation — JSON schemas, specific formatting requirements, and length constraints that ensure AI outputs meet downstream processing expectations.

03

Sampling Strategies

Select from multiple sampling approaches — greedy, top-k, nucleus sampling — each suited to different quality and diversity requirements.

04

Reproducibility

For audit-critical operations, decoding parameters can enforce deterministic generation. Same input, same parameters, same output — every time.

How it connects across the stack

Decoding Params works in concert with other layers in the intelligence stack — each connection amplifying the capability of both components.

Prompt TemplatesChat FormattingToken StreamingGovernance (Evals)

Why it matters

Get exactly the AI output behavior your task requires. Eliminate the trial-and-error of tuning generation parameters by using validated profiles that match enterprise task requirements — consistent where consistency matters, creative where creativity adds value.

See Decoding Params in action

Discover how Decoding Params fits into your enterprise intelligence strategy.

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