A compiler for verification intent
Stop hand-writing the machine code of verification.
Polaris writes and binds the general, mechanical assertions autonomously, so your engineers spend their hours on the hard, design-specific verification instead of the setup that gates every proof.
A result you can sign off on, not an accuracy percentage you have to trust.
Bound to RTL
not just generated
Solver-backed
every finding
Signable
not a percentage
Why now
The bottleneck was never the solver.
Formal isn't limited by the solver. It's limited by the human setup in front of it: reconstructing intent, binding a property to the right nets, before a proof can even start.
That setup tax is why most RTL never sees formal at all. Not because the cores are too hard, but because the translation is too manual.
Meanwhile RTL is being generated faster than any team can hand-bind properties to it. The setup wall is the one getting taller.
“The most dangerous phrase in the language is: we’ve always done it this way.”
Grace Hopper
What it does
The translation step, mechanized.
Grace Hopper's compiler didn't make computers faster. It stopped humans from writing machine code by hand. Polaris does the same for verification: it automates the manual translation from spec intent to a bound, checkable property, so the solver can run on RTL it never reached before.
It binds, then proves
Polaris takes arbitrary RTL and produces a property bound to the right structure. That's the translation step a verification engineer does by hand today. A finding it returns is the solver's, not a suggestion.
When unsure, it abstains
It never guesses a binding to look productive. If it can't establish the property soundly, it declines, out loud and with the reason, instead of shipping a confident maybe.
It clears the baseline, so your experts don't
The broad, general, protocol-and-structure assertions that eat verification hours but rarely need a senior mind: Polaris does those autonomously. Your engineers get their time back for the design-specific, creative verification that actually needs them.
Why trust it
Soundness is the whole bet.
The bar isn't whether a model can produce a plausible-looking assertion. The last two years are full of 88%-accurate generators, and 88% is unusable for signoff. The bar is zero escaped false positives: when we're not certain, we abstain rather than guess.
The abstention is the proof of trust
A tool you can catch bluffing once is dead in verification. Ours is built to say "I can't establish this," which is what makes the results it does return worth signing off on.
Built to live inside your IP
We assume you're working on sensitive silicon. Deployment shape and access boundaries are the first conversation, not a procurement afterthought.
A thesis, not a track record
We're a research team productizing a method, taking design partners in 2026. We'd rather tell you exactly where the method holds than sell you a number we can't defend.
Design partners · 2026
Point it at the RTL your team never got to.
We're taking a small number of design partners in 2026: verification teams who want to attack the setup wall on their own IP, and who'd rather pressure-test a method than watch a demo. If that's your problem, let's talk specifics.