&Truth

Unknown

&Truth is building a universal verification machine that reads code in any language and mathematically proves it safe, secure, and correct, with proofs anyone can independently check. The technology addresses the growing need to verify software at scale as AI writes and attacks more of the world's code. The company's mission is to move the industry from hoping code works to proving it does.

Traction –/10

HQ unknown

Developer Tools
Cybersecurity
Software Only

Updated 2 days ago

Funding

Raised to date

$70MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

As AI writes and attacks more of the world's software, the volume and complexity of code have outpaced traditional testing and review methods. The industry currently relies on hoping code works rather than proving it does, leaving critical systems vulnerable to bugs, security flaws, and incorrect behavior that can have severe real-world consequences.

Solution

&Truth is building the universal verification machine: technology that reads code in any language and mathematically proves it safe, secure, and correct. The platform generates formal proofs that anyone can independently check, providing a higher standard of assurance than conventional testing. This approach enables organizations to verify code at scale, covering the growing volume of AI-generated and human-written software. By moving from probabilistic testing to mathematical certainty, &Truth aims to establish a new baseline for software reliability and security across the industry.

Target Audience

Primary customers are organizations that develop or deploy critical software systems, including enterprises, infrastructure providers, and government agencies that require the highest assurance of code correctness and security.

Features

Reads code in any programming language for universal applicability
Generates mathematical proofs of safety, security, and correctness
Produces independently checkable proofs, enabling third-party verification
Designed to operate at scale, accommodating the growing volume of AI-written code
Addresses both safety (correct behavior) and security (resistance to attacks) properties