Every citation real.
Every privilege held.Legal AI security with cited-authority certainty and privilege-isolation attestation.
RankShield is legal AI security: it proves an AI output's citations resolve to real authorities and attests that privileged material stayed isolated per matter — verifiable, confidential, quantum-safe. Not a promise the model never errs, but proof you can check where it counts.
A fake citation.
A leaked privilege.
Legal AI's two nightmares: an output citing authorities that don't exist, and privileged material bleeding between matters or into a model. Both can happen invisibly, and both carry consequences a firm can't absorb.
One matter,
one chamber.
Each matter's privileged context lives in its own sealed chamber — never crossing into another client's work or a shared model. RankShield attests the isolation held, so separation is provable, not just promised.
Prove the citation
is real.
RankShield verifies that the authorities an output relies on actually exist and resolve to real sources — and attests it. It doesn't claim the model never hallucinates; it makes the citation checkable and the check provable.
The duty you
cannot get wrong.
Privilege is sacred and fragile. RankShield's isolation attestation gives you checkable evidence that privileged material stayed contained — so if it's ever questioned, you have proof, not just an assurance.
Confidential.
And verifiable.
Every attestation is post-quantum-signed, so proofs about cited authority and privilege stay verifiable for the long life of a legal record. Verifiable, confidential, quantum-safe.
What is legal AI security?
Legal AI security is protecting the AI used in legal work — and proving its outputs are trustworthy — where the two things that matter most are cited authority and privilege. Legal practice runs on two commitments a language model can quietly break: that the authorities you cite are real and say what you claim, and that privileged material stays absolutely isolated. AI makes both easier to violate and harder to notice — a fabricated citation that looks perfectly formatted, privileged context bleeding between matters or into a shared model without anyone seeing it happen. RankShield addresses both with verifiable attestation rather than empty assurance. For citations, it provides cited-authority certainty: it verifies that the sources an output relies on actually exist and resolve, and attests that verification. For confidentiality, it provides privilege-isolation attestation: proof that each matter's privileged context stayed in its own chamber. Crucially, RankShield is honest about the boundary of what it can promise — it does not claim to make AI "hallucination-free," because no tool can. What it offers is checkable proof where the stakes are highest: real citations, held privilege, both verifiable and both quantum-safe for the long life of a legal record.
How does RankShield handle AI legal hallucinations honestly?
By refusing the dishonest promise and delivering the useful one. Since courts began sanctioning lawyers for briefs citing cases that AI invented, "hallucination-free legal AI" has become a common marketing claim — and it is not true, because no system can guarantee a language model will never produce a false statement. RankShield deliberately does not make that claim. Instead of promising the model never errs, it makes the errors that matter most catchable and the catch provable. Cited-authority certainty works by taking the authorities an AI output relies on and verifying, against real sources, that each one actually exists and resolves to a genuine, checkable reference — then attesting the result as a tamper-evident record. A fabricated citation doesn't get waved through on the strength of confident formatting; it fails verification and is flagged. This reframes the problem correctly: the danger was never that AI is imperfect — all tools are — it was that its errors were undetectable and unaccountable. By making citation-checking systematic and its outcome verifiable, RankShield converts an invisible liability into a visible, provable step in the workflow. That is a claim a firm can actually rely on, and it is honest about what it does and doesn't guarantee — the same discipline RankShield applies everywhere, applied where overclaiming has already cost lawyers their credibility.
How does RankShield protect attorney-client privilege with AI?
By isolating each matter and proving the isolation held. Privilege is among the most consequential duties in legal practice, and AI tooling threatens it in a specific, insidious way: when many matters share a model, a memory, or a context window, privileged material from one client can influence or surface in another's work, and it can happen without any visible event to flag. RankShield's design treats each matter as its own sealed chamber. Privileged context is kept within its boundary — never crossing into another client's work, and never absorbed into a shared model's training or persistent memory — and RankShield issues a verifiable privilege-isolation attestation that the separation was maintained. The difference from an ordinary assurance is that this is checkable: if privilege is ever challenged, there is tamper-evident evidence that isolation held, rather than a vendor's word or an untraceable log. This matters not only for the duty itself but for the professional-responsibility obligations around it — candor, competence and confidentiality under evolving guidance such as ABA Formal Opinion 512 — where being able to demonstrate diligence, not merely assert it, is increasingly what's expected. RankShield does not replace the lawyer's judgment or make a firm compliant by itself; it makes the hardest-to-verify duties provable. Explore the full legal platform at RankShield Legal ↗.
How does RankShield keep legal work confidential and quantum-safe?
By protecting the confidentiality of a matter both now and for as long as it must stay secret — which, in law, can be a very long time. Confidentiality in legal work is not only about keeping documents out of the wrong hands today; it is about ensuring that the record of what was done, and the proofs that privilege and citation obligations were met, remain both private and verifiable for the full life of the matter and beyond. RankShield approaches this the same way it approaches every domain: prove what must be proven, expose nothing more. Attestations of cited-authority verification and privilege isolation record the fact that a check passed or that separation held — not the privileged content itself — so the evidence a firm can rely on never becomes a new avenue of exposure. And because legal records and the proofs about them may need to withstand scrutiny decades later, RankShield signs those attestations with composite post-quantum cryptography. That matters for a specific reason: an adversary could capture protected material today and simply wait for cryptography to weaken — the "harvest now, decrypt later" threat — which is unacceptable for information that must stay confidential essentially forever. Post-quantum signing keeps the proofs unforgeable and the confidentiality durable as the cryptographic landscape shifts. As always, RankShield states the honest boundary: it is quantum-safe, not quantum-proof, and it supports a firm's confidentiality obligations rather than discharging them. The lawyer's duty remains the lawyer's; RankShield makes fulfilling it verifiable and lasting.
Where does RankShield fit in a law firm's AI workflow?
As the verification layer that sits alongside the AI tools a firm already uses — not a replacement for them, and not a legal-research product itself. Firms are adopting AI for drafting, review, discovery and research, and each of those tools produces outputs a lawyer is ultimately accountable for. RankShield's role is to make two specific properties of those outputs provable: that the authorities they cite are real, and that privilege was preserved. It doesn't do the legal work, doesn't offer legal advice, and doesn't decide anything — it attests. In practice, that means it can operate as a checkpoint around whatever AI a firm uses: when an output relies on cited authorities, cited-authority certainty verifies they resolve to genuine sources before the work product is relied upon; when AI touches matter material, privilege-isolation attestation records that separation held. Because these are verifiable, tamper-evident artifacts, they give a firm something it can show — to a court questioning a citation, to a client concerned about confidentiality, or to itself as part of a defensible AI-use policy. This positioning is deliberate and honest: the value of a verification layer comes precisely from its narrowness. A tool that stayed in its lane and proved a few things reliably is worth more, and is far safer, than one that overreaches into judgment it shouldn't make. RankShield gives lawyers confidence in the AI they choose to use, by making the two things they cannot afford to get wrong checkable rather than assumed.
Ask RankShield about legal AI security.
What is legal AI security?
Legal AI security is protecting the AI used in legal work — and proving its outputs are trustworthy — where the stakes are cited authority and privilege. Two risks dominate: an AI citing cases or authorities that don’t exist or don’t say what it claims, and privileged material leaking between matters or into a model. RankShield addresses both with verifiable attestation: it provides cited-authority certainty, proving citations resolve to real, verified sources, and privilege-isolation attestation, proving privileged context stayed isolated. Verifiable, confidential and quantum-safe.
Can RankShield stop AI legal hallucinations?
RankShield does not claim to make AI "hallucination-free" — that would be dishonest, because no system can guarantee a language model never generates a false statement. What it does is provide cited-authority certainty: it verifies that the authorities an AI output relies on actually exist and resolve to real, checkable sources, and attests that verification. So rather than promising the model never errs, RankShield makes the citations checkable and the check provable — catching the fabricated citation instead of pretending it can’t happen.
What is privilege-isolation attestation?
Privilege-isolation attestation is verifiable proof that privileged material was kept isolated — not cross-contaminated between clients or matters, and not absorbed into a shared model — with a tamper-evident record that the isolation held. Privilege is one of the most consequential duties in legal practice, and AI tooling that mixes contexts can breach it invisibly. RankShield attests that each matter’s privileged context stayed in its own chamber, so the protection isn’t just claimed, it’s provable.
How does RankShield protect attorney-client privilege with AI?
By isolating privileged context per matter and proving the isolation held. Each matter’s material is kept in its own boundary, never bleeding into another client’s work or into a shared model’s training or memory, and RankShield issues a verifiable attestation of that isolation. If privilege is ever questioned, there is checkable evidence — not just an assurance — that separation was maintained. It is the same verify-don’t-trust principle RankShield applies everywhere, aimed at the duty lawyers cannot afford to get wrong.
Does RankShield help with FRCP Rule 11 and legal ethics rules?
It supports the diligence those rules expect by making an AI output’s citations verifiable and its privilege handling provable — the kind of checkable evidence relevant to obligations like candor to the court, competence, and confidentiality under evolving guidance such as ABA Formal Opinion 512. To be precise: RankShield supports professional-responsibility compliance by generating verifiable evidence; it does not replace a lawyer’s judgment or make a firm compliant on its own. The duty stays with the attorney; RankShield makes meeting it checkable.
Cite with certainty. Keep privilege provable.
Cited-authority certainty and privilege-isolation attestation, verifiable and quantum-safe. See the full legal platform.