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Spec27 is a validation platform for AI agents. It helps teams move beyond manual, vibes-based testing by using machine-readable specifications to generate broader test coverage, catch regressions earlier, and validate both in-house and third-party systems without needing SDK integration or code-level access.
Hello Product Hunt, excited to be here!
For the past three years, we’ve been working on formal verification of machine learning models and looking for ways to get deep, relevant test coverage. With language-model-based applications, this is particularly hard since the models and input spaces are massive, plus you often don’t have access to the underlying model. So the techniques from formal verification developed for vision and tabular data don’t translate well, even for tightly constrained use cases.
Thinking this through from first principles gave us the epiphany that what you really need for effective testing is a good way to specify the behavior of the agents you’re testing. So Spec27 was born to do this.
The platform allows you to create specs that specify behavior in various ways, capture what you want an agent to be robust to, and then automatically generate sets of test cases around this. The approach we’ve taken is also platform- and LLM-agnostic, so integrations can connect to pretty much any agent, no matter where it is hosted. There’s no SDK or AI gateway integration needed.
The product is free and in early access, and we’d love to get people on board and trying things out. The direct link to sign up is here: https://dashboard.spec27.ai/signup/
If you have a specific use case in mind, please also reach out and schedule a chat. Details are here: https://www.spec27.ai/
Made with ❤️ in London.
Looking forward to your thoughts!
Looking forward to try Spec27. The non-determinisim of agent results is ok if the result is an equivalent meaning, but when it goes off to hallucinate a different meaning the outcome can range from oops to a total disaster. The trust of the end users and of the company employees is difficult to repair once the agent has broken that trust. This looks like it can take us on that path to improve the quality of outcomes, and build better trust in the agents. Very nice!
Excited to be part of the team launching /Spec27 today! I care a lot about making AI safer in practice, so it’s really nice to share something we’ve been building around that. Happy to chat with anyone working on agents, evals, or validation :)
As the agent space is getting more structured we need better tooling.
Can’t wait to try s a S27!
Does it matter which framework I’m using?
About Spec27 on Product Hunt
“Spec-driven testing for AI agents and AI apps”
Spec27 was submitted on Product Hunt and earned 33 upvotes and 9 comments, placing #31 on the daily leaderboard. Spec27 is a validation platform for AI agents. It helps teams move beyond manual, vibes-based testing by using machine-readable specifications to generate broader test coverage, catch regressions earlier, and validate both in-house and third-party systems without needing SDK integration or code-level access.
Spec27 was featured in SaaS (41.7k followers), Developer Tools (511.7k followers) and Artificial Intelligence (467.3k followers) on Product Hunt. Together, these topics include over 198.7k products, making this a competitive space to launch in.
Who hunted Spec27?
Spec27 was hunted by Steven Willmott. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Steven Willmott