The largest framework library vs the program that runs itself
Why teams evaluate Hyperproof alternatives
Hyperproof is enterprise compliance infrastructure. Its framework library is the largest in the category at 160+, its crosswalks let one control answer cascade across many frameworks at once, and it prices with unlimited users so a large GRC organization can actually use it. For a staffed team spanning many regulatory regimes, that is a strong fit.
Teams look elsewhere for two reasons. The first is cost: reported entry is around $12,000/yr and the median contract lands near $40,000/yr, which is difficult to justify for a program run by one or two people. The second is that Hyperproof organizes work rather than doing it — it is excellent at routing a task to a human, and the human is still the one writing the policy.
- Someone to do the drafting — agents write the policy, narrative, and questionnaire answer, and a human approves
- Evidence that proves something — every check writes pass, fail, or inconclusive, and a failing check raises a finding
- Boundaries as standard — account, region, resource, and tag scoping without a tier upgrade
Where episki is different
The clearest difference is who does the work. episki's agents draft policies, answer security questionnaires, map controls across frameworks, and advance vendor reviews between audits — with humans approving what matters. The AI authors deterministic recipes that then run without a model in the loop, so the procedure behind each artifact is inspectable rather than asserted.
The second difference is what a control check means. Every integration operation decodes its response, runs its assertions, and writes an explicit verdict. Empty evidence returns inconclusive rather than passing. An unreadable response fails its region rather than resolving to nothing. An incomplete sync cannot attest a control. And an approved exception — with a recorded approver, a justification, and an expiry — can satisfy a check for named records without pretending the underlying condition changed.
When Hyperproof might still be the better fit
If your program spans dozens of regulatory regimes simultaneously and the multi-framework crosswalk cascade is the specific thing you are buying, Hyperproof's library is genuinely larger and its enterprise workflow is mature. If you have a staffed GRC function that needs coordination infrastructure more than it needs an operator, that is what Hyperproof is built to be.
episki vs Hyperproof: feature comparison
| Feature | episki | Hyperproof |
|---|---|---|
| Approach | Autonomous GRC — agents run the program; humans approve the work that matters | Enterprise compliance operations — workflow, crosswalks, and evidence management for a staffed GRC function |
| Who does the work | Agents draft policies, narratives, questionnaire answers, and control mappings; a human approves | Your GRC team, supported by workflow, templates, and automated collection |
| Pricing model | Published — platform $750/mo (or $7,500/yr) + optional modules; unlimited users and frameworks, with AI tokens the only metered resource | Quote-based across Professional, Business, and Enterprise tiers with unlimited users; reported entry near $12,000/yr with a median contract around $40,000/yr |
| Framework coverage | 34+ pre-built frameworks plus custom, all unlimited, with crosswalk derivation through the SCF hub and a controlled mapping vocabulary | The largest library in the category at 160+ frameworks, with multi-framework crosswalks that cascade one control answer across many |
| Controls & evidence | Continuous controls that produce a verdict — every check evaluates the evidence it collected and writes pass, fail, or inconclusive, and a failing check raises a finding. Empty or undecodable evidence attests nothing | Evidence management with automated collection and mapping across frameworks |
| AI capabilities | Agents draft, answer, and map — and the AI authors deterministic recipes that then run without a model in the loop, so output is reproducible | AI assistance layered onto established compliance workflows |
| AI governance | AI Governance module — agent and use-case registry with allowlists and safety floors, AI risk treatments wired to controls and evidence, and ISO 42001, NIST AI RMF, and the EU AI Act mapped. episki governs its own agents through the same module | AI-related frameworks available within the framework library |
| Integrations | AWS (multi-account, multi-region, and Organizations), GitHub, Google, Microsoft, Slack, Teams, Jira, Linear, Supabase, Vercel, and Netlify — each writing evaluated control coverage, not just collected files | Integration library plus custom integrations, typically scoped at the higher tiers |
| Exception handling | An approved exception can satisfy a specific check for named records — it requires a recorded approver and justification, and it expires, so the control returns to failing on its own when the acceptance lapses | Exception and issue tracking through the compliance workflow |
| Scope & boundaries | Programs report against individual boundaries, with scope rules on cloud account, region, resource, and tag — so a PCI CDE or a single business unit is a real boundary, not a saved filter | Scopes available as an advanced capability, positioned at the higher tiers |
| Remediation workflow | Bi-directional Jira, Linear, and GitHub sync — remediation lives in the tracker your engineers already use, and status flows back | Task and issue workflow inside the platform, with ticketing integrations |
| Reporting | Dashboards with evidence-backed assurance scoring and drill-downs into the controls behind each number | Reporting is a commonly cited limitation, with customization often requiring workarounds |
| API & agent access | REST API, a published entity-ontology catalog with a drift checksum, and a hosted MCP server whose writes route through the same API as the UI | REST API |
Why teams switch from Hyperproof to episki
- Agents draft policies, narratives, and questionnaire answers from your own evidence
- Vendor reviews advance over email without anyone chasing them
- AI authors deterministic recipes; the recipes then run without AI in the loop, so auditors can trust the output
- Empty, undecodable, or partially collected evidence returns inconclusive and attests nothing
- A failing check raises a finding with the offending records attached, not a dashboard tile
- An approved exception can satisfy a check for named records — but it needs an approver and it expires
- Boundaries with cloud account, region, resource, and tag rules are standard, not an advanced add-on
- Unlimited users and unlimited frameworks at $7,500/yr, published rather than quoted
- Annual prepay gives two months free; Operator Partner discounts for vCISO and MSP firms
