ExaktAI Validation

You ask in natural language (English, French, …, Chinese, …), with palettes of mathematical symbols, or in SymPy, Mathematica or Maple syntax. ExaktAI answers with the derivation steps and opens the validation document automatically: a Maple document, a Mathematica notebook, or an editable ExaktAI Workspace document computed with SymPy.

ExaktAI App showing the minimum distance to a plane solved using Lagrange multipliers, validated by Claude with the Mathematica notebook open alongside — ExaktAI running Mathematica as backend: problem validated step by step, with details collapsed. The Mathematica notebook was automatically generated and opened by ExaktAI.

Expanding any of the collapsed 'Details' shows, directly in the App, the computational instruction (CI) that represents the step in the Computer Algebra System (CAS), in this case Mathematica, the AI inferred result (AIR), and the result from the CAS. The CI and CAS are reproduced in the Mathematica notebook.

Expanded details for step 3 showing the computational instruction in Mathematica, the AI inferred result, and the Mathematica CAS result

ExaktAI App showing the osculating circle problem solved and validated in 4 steps by Codex with the Maple document open alongside — Codex (OpenAI) + Maple: the osculating circle problem validated in 4 steps, optionally showing Timelimit and Reasoning effort. The Maple document was automatically generated and opened by ExaktAI; it mirrors the steps and can be re-executed or edited.

ExaktAI validating a constrained-extremum problem with Gemini and SymPy: on the left the App, its AI and CAS chosen, the answer stamped Validated in 36 seconds with each step and its result; on the right the ExaktAI Workspace document it generated, the five steps as executable SymPy instructions from solving the constraint to the extreme value 36/5 — Gemini + SymPy. On the right, the ExaktAI Workspace document generated and opened automatically: five executable steps, each referencing the ones before it.

How it works

The problem is presented using natural language; ExaktAI guides the AI through a structured reasoning process that produces step-by-step computational instructions. Each instruction is executed in a CAS. ExaktAI applies a multi-stage strategy involving independent AIs, CAS executions, and mathematical equivalence checks in order to validate a step.

The document that opens is yours to audit, modify, experiment with and extend.

In summary: ExaktAI orchestrates, AI drives, CAS executes, and you stay in the loop.

AI consensus

Besides step-by-step validation, there is another mode: run several AIs on the same problem, then verify whether their answers are mathematically equivalent. ExaktAI uses computer algebra systems (CAS) to check equivalence and reports the agreement level, for example, Consensus 6/6 when six AIs independently converge on the same answer, and so on.

Consensus is not a substitute for full step-by-step validation. AI systems sharing the same training data can converge on the same wrong answer. What consensus adds is another way to assess an answer: disagreement is surfaced immediately, and convergence across independent AIs is a meaningful signal.

ExaktAI consensus mode: all six AIs (Claude, Codex, Gemini, DeepSeek, Mistral, Grok) independently produce the same answer for the osculating circle problem - Consensus (6/6) — Consensus (6/6) in 1'24": Claude, Codex, Gemini, DeepSeek, Mistral, and Grok all independently arrive at the same equation for the osculating circle. ExaktAI reports the shared answer and the agreement level.

When AIs disagree

Consensus is not guaranteed. When the AIs split, ExaktAI shows which ones agree and explains the difference - automatically, by comparing the actual answers.

ExaktAI Split (3/6) on a vector projection problem. — Split (3/6) on a vector projection problem. ExaktAI groups the answers. A correct, validated solution to this problem is shown here →

For a more challenging derivation, see ExaktAI vs CAS AI assistants on a problem by Euler.

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ExaktAI is up and running. Beta is scheduled for late summer or fall 2026. We can reach out when it's ready to try.

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