Let your team use AI. Without the leak.
Wardary is a governed chat client that sits between your people and cloud AI models. It redacts sensitive data before it ever reaches a provider, enforces which models are allowed, and logs every prompt — so you can say yes to AI, safely.
Bring your own keys · OpenAI · Anthropic · Google
Draft a demand letter for our client [NAME_1] regarding matter [MATTER_2]. Their SSN [SSN_1] is on file.
Sent via encrypted tunnel · sensitive spans never left your boundary
I've drafted the demand letter for your client. Real names and identifiers were restored only here in your view — the provider saw placeholders.
Built for teams under an “enable AI safely” mandate
The status quo is a leak
Your “no AI” policy is a Word doc. The data is already leaving.
Banning AI doesn't stop it — it just moves it to personal accounts you can't see. Three out of four employees have already pasted sensitive data into an AI tool. Leadership wants AI enabled; you're the one who has to make it safe.
Wardary gives your people an AI they're allowed to use — and gives you the evidence to tell leadership yes.
- of employees
- 77%
- AI DLP violations / yr
- 410M
- year over year
- +99%
How Wardary works
Protect. Govern. Record.
Every prompt your team sends passes through three controls before — and after — it reaches a provider.
Redact before it leaves
Detectors scan every prompt and uploaded file for PII, secrets, and custom patterns. Matches are redacted or the prompt is blocked — before anything reaches OpenAI, Anthropic, or Google.
Learn moreControl which models, with what context
Admins set an allow-list of approved providers and models, decide whether users can pick, and prepend standing org context to every outbound prompt — enforced server-side.
Learn moreAn audit trail for every prompt
Each prompt writes one append-only record — model used, redactions applied, tokens, cost. A complete, defensible compliance trail you fully own.
Learn moreWhy Wardary
A real redaction layer — not just another gateway
Routing and logging are commoditized. The hard, valuable part is keeping regulated data out of providers, with the audit trail to prove it.
Actual redaction
Enterprise AI tiers promise “we won’t train on your data.” Wardary makes sure the sensitive data never arrives in the first place.
Multi-provider by design
Don’t hand one vendor everything. Use OpenAI, Anthropic, and Google behind a single governed surface with one allow-list.
Reversible tokenization
Sensitive spans become placeholders before the call, then restore to real values in your view. The provider only ever sees tokens.
Files scanned too
PDFs, DOCX, TXT, and CSV uploads run through the same redaction pipeline before their contents are ever sent.
Usage you can see
Token and cost metering by user and by model — understand spend and prove governance to leadership.
Append-only audit
Immutability enforced at the database, not in middleware. Every prompt yields exactly one record that can’t be quietly changed.
Built for your industry
Designed for regulated teams first
We won't oversell it.
Today, Wardary is a sanctioned, governed alternative to shadow AI — not a blocker for personal accounts. It stops leakage through Wardaryand aims to displace the risky behavior by being good enough that your team actually prefers it. A browser/endpoint guard that also covers direct ChatGPT and Claude use is our committed next surface. We'd rather tell you that than pretend we stop a leak we can't yet see.
Questions
The things security teams ask first
No. Redaction and blocking run inline, in-process, before any outbound call. A value marked for redaction is replaced with a placeholder token; a blocked prompt is never sent. The provider only ever sees tokens — never the raw value.
Yours. Wardary is bring-your-own-key in v1: your traffic runs under your own provider contracts, and you pay providers directly. Our price is for governance and audit, not a token markup.
The model allow-list and prepend context are enforced server-side. A request for a disallowed model is rejected, not just hidden. When a routing rule enforces a destination, user selection can’t override it.
We fail closed on uncertain, high-risk spans — safety first. We’re candid that regex over-redacts ID-shaped text (docket and matter numbers), and a human review/override queue is on our near-term roadmap to fix exactly that.
Every prompt writes exactly one append-only record, with immutability enforced at the database layer. No prompt is ever un-logged — that’s the compliance guarantee.