Company on Tuned Predictions

Investors

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A focused approach to useful AI

Tuned Predictions helps individuals, founders, and teams train models on their own examples, evaluate the results, and choose which version to use.

Investor inquiries

For information about the company and investor conversations, contact our team.

Explore the product

Start with the product resources and blog to understand how the product works. Our Trust Center outlines product transparency and questions to cover in a review.

Leadership

Mon, 01 Jan 0001 00:00:00 +0000

The company behind the product

Tuned Predictions is built by Redsnack Technologies Inc.

44 Montgomery Street, San Francisco, CA.

Start a conversation

For leadership introductions, company questions, or partnership conversations, contact our team.

How we think about the work

Make the inputs visible. Keep model outputs open to review. Give people the information they need to decide how to use the results.

Read our product guides or visit the Trust Center for practical details.

Trust Center

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Review the data before training

The workflow starts with connected data and prepared examples. Review the inputs and target outcomes before training. Use only information available at prediction time. See the product workflow and supported integrations.

Evaluate before deployment

Use held-out examples, per-question results, and available baseline comparisons to judge a candidate. Training does not guarantee an improvement. A scheduled retraining run creates a candidate; evaluation and deployment remain separate steps.

Follow a prediction back to its version

Versioned inference and traces help you inspect the inputs and model version behind a result. Keep the task and evaluation criteria clear when comparing versions.