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More accurate at every setting, at a seventh of the cost.

At all eight of its settings, Duplex was more accurate than a semantic cache at any of its five, or GPT-5.5 alone at its one, on the same 3,000 decisions. Three more runs, on fresh streams, showed the same order.

Internal benchmarks. Every figure on this page comes from tests Vareon ran itself and has not been independently verified. Read the disclaimer

  • 94.1 to 94.8%*Duplex accuracy, at every one of eight settingsThe best a cache reached: 77.3%
  • 84 to 91%*On three fresh runs of 1,000 decisionsThe best a cache reached: about 73%

* Figures from Vareon’s internal benchmarks, not independently verified. Read the disclaimer

Every setting, on one chart.

GPT-5.5 alone has one setting: 59.8% accurate, at $0.82 per 1,000 decisions.*

Step 1 of 4: The model

Duplex at its worst beats a cache at its best.

The least accurate Duplex setting against the most accurate cache setting.

Step 1 of 2: Accuracy

At its least accurate setting, Duplex scored 94.1%. The cache, at its most accurate, scored 77.3%.*

Tuning a cache does not buy accuracy.

The same cache, from its loosest matching to its strictest.

Step 1 of 3: Stricter

Tightening a cache’s matching sends more requests to the model: from 4 calls to 212.*

The same order, run after run.

Three fresh runs of 1,000 decisions each, in a second, independent setup.

Step 1 of 2: Accuracy

Over three fresh runs in a second, independent setup, Duplex scored 87.7%, and the best cache 73.0%.*

How it was run.

The work
The same customer-operations stream as the cost result: one right action out of about nineteen, or a refusal, with five in-house rule changes.
Settings
Duplex at eight settings, from most willing to answer itself to most cautious; a semantic cache at five, from loosest to strictest matching; GPT-5.5 alone at its only one.
Scale
One 3,000-decision stream, then three independent runs of 1,000 decisions in a second setup.
Kept equal
The same recorded GPT-5.5 answers for every point, the same feedback and the same refusal rules.

What it means for your work.

  • Steady at every setting.

    All eight Duplex settings landed between 94.1% and 94.8% accurate.*

  • Accuracy a cache cannot reach.

    Across its settings, the cache topped out at 77.3%, and at 44.2% after a rule change.*

  • Cheaper than the model, everywhere.

    Even Duplex’s most cautious setting cost less than GPT-5.5 alone, and was 34 points more accurate.*

Next: Keeps learning without forgetting, going stale or growing.Read it →

See it on your own work.

From your own assistant to every agent your company runs, a pilot puts Duplex on your own work, with the measures agreed before it begins.

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