What we build, in one place.

Available as a service

AgenticTestari — authorized security testing

What it does: tests your AI systems, agents and digital services against realistic attack scenarios in controlled environments, turns findings into practical fixes and verifies them through independent retesting.

Who it is for: organizations that run AI systems or digital services and need to know, before an attacker shows them, where the weaknesses are.

Use case: before a launch, an authorized test of a new AI-assisted customer service finds that the agent leaks internal data through a seemingly harmless feature. The flaw is fixed and the fix retested — before anyone outside the team could exploit it.

In development

Sentinel + ParviDefenders — AI-powered defense (in development)

What it does: Sentinel researches how AI-powered attacks work and validates defenses against them. ParviDefenders is the next step being developed on that research: agents that watch, recognize and respond to AI-driven threats. This is the honest state — a research and development track, not a deployed service.

Who it is for: organizations that expect AI-powered attacks against their systems and want defenses built from evidence rather than fear.

Use case: a research engagement studies how AI-generated phishing adapts to a company's public information; the lessons feed the defenders being developed, so the future response is tested against the real attack shape, not a guess.

Available as a service

ParviSight — QA agents across the whole stack

UI · Frontend · Backend · Database · Code

What it does: designs and runs tests against your specifications at every layer — the user interface, the frontend, the backend, the database and the code — and reports results as evidence a human can verify.

Who it is for: development teams and product owners who need real test coverage — not a demo — before a release, and organizations that must show auditors or customers how quality was verified.

Use case: a team prepares a release with strict data rules. The QA agents write and run tests from the specification through the UI to the database, catch that a boundary case deletes data it should keep, and hand over the failing test as evidence. The fix is retested before release.

In development

ParviGov — sealed actions, gates and audit

What it does: puts approval gates in front of important agent actions and seals the record of what was done, who did it and what a person authorized — so any change to the record is detectable.

Who it is for: organizations that let agents touch customers, money, compliance or company decisions, and need to prove afterwards what happened and who was responsible.

Use case: an agent drafts customer refunds within limits a person set. ParviGov records each draft, the human approval that released it, and seals the chain of records. When a refund is later questioned, the complete history is replayed and verified — not reconstructed from memory.

In development

Graph Files — knowledge with a sealed, replayable history

What it does: builds documents from templates and research with verifiable sources, then records every creation, modification and authorization — including what AI agents did and who authorized them — and seals the whole history cryptographically so it can be replayed and audited by anyone, independently.

Who it is for: law firms and institutions — anywhere documentation is the work product and the question “who changed this, and on whose authority?” must have a real answer.

Use case: a law firm builds contracts from its own templates. Graph Files records the research behind each clause with its verifiable sources, every AI-assisted modification, and the lawyer who authorized each version. The full history is sealed — and when a dispute arises years later, it is replayed and verified as it happened.