Make reliable decisions with AI.

AI errors are costly. Checking every output is costly too. Themis helps you identify which predictions and proposed actions need attention, so you can automate more work and focus verification, expert review and model improvement where they matter.

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A decision layer to guide AI actions.

Themis connects model outputs with evidence and operating context to flag risky predictions before they’re acted on.

Your model’s output or proposed action
Themis Decision Layer

Outcomes inform the next decision

Illustrative workflow

Clear case. The output agrees with the available evidence, and the input looks like the cases the model handles well. A check would cost time without changing the result, so the action continues.

Conflicting information. The output disagrees with a record the decision depends on. Rather than act on either, the workflow gathers more evidence first, and what it finds informs the next decision.

Outside this model’s range. The input is unlike the cases this model handles well, but another model or tool is suited to it. The case goes there instead of to an expert.

Unresolved case. The evidence is still inconclusive after checking, and a mistake here would be costly. The case goes to an expert, so expert time goes where judgement is needed, not to every output.

Demonstration

Defect inspection on the NXP i.MX 8M Plus

A risk signal alongside each prediction lets an edge system act on familiar inputs and route the rest to human review. See the edge demonstration

Go beyond the output. Build reliability into the model.

Themis AI’s Capsa performs targeted model surgery, adding uncertainty-estimation capabilities to the models you run. Using signals from within models and across model predictions, it helps identify unfamiliar inputs and unreliable outputs.

Original model: prediction

A neural network with an input x, three layers and a single output, the prediction ŷ.

With Capsa: prediction + uncertainty

The same network with Capsa brackets around its layers, returning the prediction ŷ together with an uncertainty estimate σ.

Prediction + uncertainty estimate

A neural network with Capsa brackets around its layers, returning the prediction ŷ together with an uncertainty estimate σ.
Schematic. The modification depends on the model and the uncertainty method selected.

Themis uses these signals alongside operating context and decision policies to guide action and target model improvement.

Explore Capsa

Reliable decisions across engineering and operations.

  • Engineering and simulation

    Use model predictions to move engineering work forward, and focus higher-fidelity simulations, experiments and expert review where they improve the decision.

    Explore engineering workflows

  • Agent and operational workflows

    Improve extraction, matching and reconciliation by automating clear cases and directing conflicting records to additional evidence or expert review. Apply the same approach to an agent’s proposed next action.

    Explore operational workflows

A platform built for decisions. A team built to deliver.

Themis combines proprietary decision technology with deep technical expertise to help AI models and agents perform better, act reliably and improve as conditions change.

Themis AI was founded in 2021, originating from Dr. Daniela Rus’ lab at MIT Computer Science and Artificial Intelligence Laboratory. Our expertise spans decision theory, risk estimation, model adaptation and production AI engineering.

Meet Themis

Start with one repeated decision.

Tell us where errors, delays or unnecessary review hold your workflow back. We’ll explore how our technology can help.

Discuss your workflow