AI in a security product usually means your findings become someone else's traffic. Here you choose the provider and hold the key, and your own database sends each request to it, so neither the key nor the text passes through Pental. Or run the model yourself and let nothing leave.
Your provider's own token price, with no mark-up and no AI fee from Pental.
Paste a key from your own account. Each request goes from your own database to the provider, under your account, your agreement, your data-handling terms and your billing: on Supabase the database sends it itself, and behind a Pental gateway the gateway does. The key is added there as the request leaves, so neither it nor the text passes through Pental, and there is no account of ours in the way, so no pooled quota to queue behind. Where your database cannot send yet (a gateway older than 1.4.0), Pental relays the request and keeps neither, and Settings, AI says which route you are on. Choose any model the key can use, or Recommended, which moves to each newer model Pental recommends.
Point the platform at an Ollama instance inside your environment and no engagement data leaves your network for any AI provider, full stop. For the firms whose clients ask that question first, this is the answer that ends the conversation.
Any OpenAI-compatible or Anthropic-compatible URL works: a gateway you run, a regional provider, a fine-tuned deployment. Model name, request format and token ceiling are all yours to set.
An AI key is a credential to your provider account and your spend. Here is its entire life, start to finish.
The AI key is one of nine secret columns handled this way, alongside SMTP passwords and integration tokens. The mechanism is described in full on the security page.
The local route is not a degraded mode. In one important way it is the better one: with no per-token bill and no provider rate limits to design around, the platform can afford slower, more careful passes over your engagement when drafting, which shows in the output.

Paste your rough notes as you captured them, screenshots, code, requests, output and tables alike, and one button turns them into a finished finding. It explains each piece first, with a caption under every screenshot, rewrites the words you typed as report prose without changing a value in them, leaving out the to-dos and side issues that belong elsewhere, names the finding and brings in your library's own wording where you have written the weakness up before, then drafts the rest: the description and remediation, the CVSS vector, the CWE and category, the affected assets, your own custom fields and the references, in that order, each step using what the ones before it produced. Anything you have already written is left alone.
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Paste Your Rough Notes
Notes, tool output, tables and screenshots go into the evidence as rough as they were taken mid-test. Nothing else on the finding is written yet.
Calderwood SecurityTheir team, writing a findingEvery prompt is yours to edit, and it runs on your own key or a local model.Demonstration portals. The four firms are invented; every screen is the real software.
Product demo
This is in the demo as “Writing a Finding with AI and the Library”, from 1:42, with the rest of the platform a chapter away.
Each generated field has its own prompt, visible and editable in settings. House style, structure rules, banned phrases, the level of detail your clients expect: put it in the prompt once and every draft follows it. A reset returns any prompt to the shipped default, so experimenting is safe.
A fixed, hidden prompt produces the same beige paragraph for every firm in the industry. Your wording is part of your product. The prompts being yours is what makes the drafts sound like you rather than like everyone.
Upload the Word report you already send. The platform reads its structure and maps your placeholders, tables and sections to live engagement data. From then on, rendering is deterministic: the same engagement produces the same document, byte for byte, with no AI in the loop at render time.
Configure no provider and the AI is simply absent: no buttons, no nags, no degraded mode. Engagements, findings, QA, reports, retests and the client portal all work completely without it, because the platform was built to run a firm first and to draft prose second. Turn it on later, or never, and change routes whenever you like.
Only to a provider you choose, under your own key: OpenAI, Anthropic, Groq, or an OpenAI- or Anthropic-compatible endpoint. With a local model running through Ollama on hardware you control, nothing goes to an AI provider at all, and AI can also be switched off entirely.
Yes. As well as drafting a finding’s fields from the evidence your tester captured, the AI can explain the screenshots in it, using whichever provider or local model you have connected. What it writes is a draft for your tester to review like any other text.
Yes. When you upload your own Word template, the Document Builder maps the platform’s fields into it, and AI can help build that mapping. Once it is in place, reports are generated as Word and PDF, and a report edited in Word can be uploaded again so the changes are read back in.
Yes. Every feature is included, AI-assisted writing with it, in the Portal and in our free reporting tool alike. Because the AI runs on your own key or on hardware you run, any usage cost sits between you and your provider.
Either way it is configured in minutes from your portal, and either way the key material and the findings stay on your side of the boundary. Free trial, no card required.