Zohal
Summary
Dropping a confidential PDF into a generic AI chat tool and hoping the vendor's data handling policy holds up is a bet most legal, HR, and finance teams cannot afford to take. Zohal is built for that exact moment — a private AI chat layer designed to keep sensitive documents from leaking into shared model training pipelines.
Zohal creates temporary, isolated sessions before any document interaction begins, so your files are handled in an ephemeral context rather than persisted in a shared environment. The vendor's positioning targets teams that need to query protected PDFs — think contracts, personnel files, or compliance reports — without routing content through a standard API endpoint that logs everything. Audit evidence generation is listed as a supported use case, which suggests session activity is logged in a way you can export for compliance purposes. The scrape data is thin on architectural specifics, so claims about encryption depth, data residency, and zero-retention guarantees should be verified directly with the vendor before any production deployment. Teams with strict data governance requirements will need written confirmation — marketing copy is not a compliance control.
Bottom line: Zohal fits the team that needs a documented, isolated environment for one-off document queries against sensitive material — it is a harder sell for organizations that need to verify zero-retention guarantees through a third-party audit report before procurement.
Pricing Plans
SubscriptionLast verified 2 weeks ago- Price
- $39/mo
- Free Tier
- 1 seat, 100 protected interactions/month, 50,000 AI credits, 100 indexed document pages, 10 saved document indexes
Free
A focused trial of protected AI work with strict limits and no payment required.
- 1 seat
- 100 protected interactions/month
- 50,000 AI credits
- 100 indexed document pages
- 10 saved document indexes
Solo Pro
Protected AI for one operator who needs safe prompts, PDF checks, and browser guard coverage.
- 1 seat
- 1,000 protected interactions/month
- 100,000 AI credits
- 250 indexed document pages
- Standard model access
Team
Shared policy controls, team workspace protection, and practical audit evidence for growing teams.
- 10 seats
- 10,000 protected interactions/month
- 1,250,000 AI credits
- 2,500 indexed document pages
- Team policy controls
Business & Enterprise
Higher-volume protected AI operations, advanced evidence, custom model routing, and governance support.
- Custom protected AI capacity
- Advanced evidence and reporting
- Provider and model governance
- Enterprise workflows and support
View full pricing on zohal.ai →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Ephemeral session model means uploaded documents are not persisted in a shared environment, so teams querying contracts or HR files avoid the data retention risk that comes with general-purpose AI assistants.
- Audit evidence generation is listed as a supported output, so compliance-conscious teams can produce a record of AI document interactions without building a separate logging layer.
- Purpose-built for PDF privacy workflows, which means you are not adapting a generic chat tool and hoping the fine print on data handling covers your use case.
- Freemium entry point lets a team validate the session isolation behavior against a real sensitive document before committing budget — skipping the prototype phase that generic tools require.
Cons
Sign in to edit- No self-hosted deployment option exists, so any organization under strict data residency requirements — GDPR jurisdiction enforcement, FedRAMP scope, or internal data sovereignty policy — cannot place this tool in a compliant environment without written contractual guarantees from the vendor, which the public page does not provide.
- Architectural specifics for team-based workflows — role permissions, admin dashboards, identity provider integration — are absent from available documentation; teams evaluating this for more than a single-user context will stall at the IT security review stage and typically default to a competitor with published security documentation.
- The scrape content is sparse enough that claims about encryption standards, data retention windows, and model training opt-outs cannot be independently verified from public sources; a team that reaches the security questionnaire stage of procurement and cannot get answers switches to a tool with a published trust and security page.
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About
- API Available
- No
- Self-Hosted
- No
- Last Updated
- 2026-06-22T10:22:43.257Z
Best For
Who it's for
- Teams handling confidential documents
- Users needing prompt and PDF privacy layers
- Organizations requiring audit evidence
What it does well
- Sanitizing sensitive documents for AI analysis
- Private chat with protected PDFs
- Team-based secure AI document workflows
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Frequently Asked Questions
- Is Zohal free?
- Zohal has a permanent free tier alongside paid upgrades (paid plans from $39/mo). You can keep using a baseline version indefinitely without paying.
- Is Zohal open source?
- No — Zohal is a closed-source tool. Source code is not publicly available.
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Curated lists that include this category
Zohal provides a private AI chat interface where users can upload and query sensitive documents — PDFs in particular — without the session persisting beyond the interaction. The core workflow, as described on the vendor page, starts by generating a secure temporary session before any content is loaded, isolating each interaction from shared infrastructure. From there, users chat against their documents and receive AI-generated responses scoped to that session’s content.
The differentiating claim is the ephemeral session model: rather than storing uploaded documents or query history in a persistent workspace tied to a shared environment, Zohal creates a sandboxed context per session. For teams handling documents under NDA, attorney-client privilege, or HR confidentiality requirements, this architecture matters more than feature count — the question is not what the tool can do but what it does with the data afterward.
Zohal is best positioned for teams that need audit-ready evidence of document handling practices, or for individuals who regularly work with PDFs they cannot send through a general-purpose AI assistant. Where it strains is at the edge of organizational scale: the vendor page references team-based workflows, but architectural specifics about role-based access, admin controls, and integration with enterprise identity providers are not surfaced in available documentation. Teams inside a larger procurement process will hit a due-diligence gap before they can sign off on deployment.
The freemium entry point lowers the barrier to test the interface against a real document, but features required for team workflows and audit logging are paid-only features. The self-hosted option does not exist, meaning data residency is determined entirely by Zohal’s infrastructure choices — a blocking issue for organizations under regional data sovereignty rules.