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Open-source inference for agents.

Superlinked
@superlinked
Oct 27
AI that summarizes an accident report is easy. AI that never adds a claim the report doesn't make? That's the hard part, and it's the part that matters! The test case: the NTSB's East Palestine report. Three wayside detectors recorded the same railcar bearing running hotter and
Superlinked
@superlinked
Oct 20
Most healthcare document AI can't be validated. The claims data is locked behind privacy walls, and synthetic data proves nothing. CMS accidentally solved this: they published a documentation finding, complete with the answer. The rule required a face-to-face encounter within
Superlinked
@superlinked
Oct 16
SIE takes your JSON Schema and returns typed fields from a document using Qwen3.8 27B. The hard part isn’t generating braces. It's making `injured_people: 1` mean the source actually says someone was injured. Your parser won't catch a plausible lie.
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Superlinked
@superlinked
Oct 15
In SIE's extraction example, the source mentions a bruised passenger. Sonnet 5 returns `injured_people: 0`; Qwen3.8 27B on SIE returns `1`. Both outputs look tidy. Only one belongs in the database.
Superlinked
@superlinked
Oct 15
Qwen3Guard 4B on SIE returns a Safety verdict and harm categories. Your app decides whether to hold the request. No dramatic refusal monologue required. Just a specialist doing one job before the main model speaks.
Screen harmful prompts before your LLM answers | Superlinked
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