episki vs Scrut Automation
Both bundle everything. The difference is what the platform does with it
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" episki does too, at a published price, and then goes further": "every check writes a verdict, and agents do the drafting rather than assisting with it."
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Why teams evaluate Scrut Automation alternatives
Scrut earned its position honestly. Bundling every framework, module, and seat into one subscription removed the per-framework tax that most of the category still charges, and its integration library is large. For a mid-market team running several frameworks, it is frequently the cheapest credible option.
So the reason to look at episki is not packaging — it is what the platform does after the evidence lands.
- Evaluation, not just collection — every check writes pass, fail, or inconclusive against the control, and a failing check raises a finding
- Exceptions with an expiry — an accepted risk needs an approver and a window, and the control returns to failing when the window closes
- Published pricing — the whole price list is on the website, with no onboarding fee
Where episki is different
Collecting evidence is the easy half. episki connects the other half: every integration operation decodes its own response, evaluates its assertions, and writes an explicit verdict. The failure modes that resolve silently in your favor are closed by design — empty evidence returns inconclusive rather than passing, an unreadable response fails its region rather than resolving to nothing, and a sync that did not finish cannot attest a control.
Scope is a real boundary rather than a saved filter. Programs report against individual boundaries with rules on cloud account, region, resource, and tag — the axes that actually constrain account-global evidence, which is what makes a PCI CDE definable rather than approximated.
And the agent layer does the work instead of guiding you through it: skills that carry their own instructions and tools, plans that execute as observable step-runs, provenance-aware approvals, and deterministic recipes that run without a model in the loop.
When Scrut might still be the better fit
Scrut ships more frameworks and more integrations. If your evidence lives across a long tail of niche SaaS tools, or you need a specific framework from its library that episki does not yet include, that breadth is a real advantage and its bundled price makes it an easy business case. episki is the better fit when you care more about what each check actually proves than about how many checks there are.
episki vs Scrut Automation: feature comparison
See how the platforms compare across the capabilities that matter most to security and compliance teams.
| Feature | episki | Scrut Automation |
|---|---|---|
| Approach | Autonomous GRC — agents run the program; humans approve the work that matters | Broad compliance automation with AI assistants for remediation guidance and questionnaires |
| Pricing model | Published — platform $750/mo (or $7,500/yr) + optional modules; unlimited users and frameworks, with AI tokens the only metered resource | Bundled — every framework, module, and seat in one subscription, quote-based, typically reported in the $15,000–$40,000/yr range |
| Price transparency | The full price list, token allowances, module costs, and partner discounts are published on the pricing page | Quote-based, with a one-time onboarding fee commonly reported |
| AI capabilities | Agents draft policies, answer questionnaires, map controls, and recommend tasks — and the AI authors deterministic recipes that then run without a model in the loop, so output is reproducible | AI assistants for guided remediation of failed tests, evidence validation, and questionnaire completion |
| 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 | Continuous control monitoring with automated evidence collection across a large integration library |
| 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 bundled library |
| Framework coverage | 34+ pre-built frameworks plus custom, all unlimited, with crosswalk derivation through the SCF hub | 60+ frameworks, all included with no per-framework charge |
| 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 | 100+ integrations for automated evidence collection and continuous monitoring |
| 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 | Findings can be accepted or excluded; the acceptance is not itself an expiring, approver-bound object tied to the check |
| 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 | Framework-level scoping |
| Remediation workflow | Bi-directional Jira, Linear, and GitHub sync — remediation lives in the tracker your engineers already use, and status flows back | Task-management integrations with real-time alerts on mitigation tasks |
| 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 — an agent's write is indistinguishable from a hand-made one in the audit log | REST API and integrations |
| Editor experience | Notion-like, keyboard-first editor for policies, narratives, and responses, with writing actions grounded in the record being described | Standard form and workflow interface |
Why teams switch from Scrut Automation to episki
Real differences that affect how fast your team ships audits and proves trust.
A verdict you can defend, not just a green check
This is the real difference, and it is not about packaging. Scrut collects evidence across a large integration library. episki evaluates what it collected and writes an explicit verdict — closing the failure modes that let a check pass without proving anything.
- 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, so an accepted risk is never a permanent carve-out
Published pricing, not a quote
Scrut's bundling is genuinely competitive — every framework, module, and seat in one subscription. episki bundles the same way and then publishes the number, so you can model three years of cost without a sales call.
- The platform price, module prices, token allowances, and partner discounts are all on the pricing page
- No onboarding or implementation fee
- Annual prepay gives two months free; Operator Partner discounts reach 40% for firms running six or more workspaces
Autonomy, not assistance
Scrut's AI guides you through remediating a failed test. episki's agents do the work and hand it back for approval — drafting policies, answering questionnaires, mapping controls, and advancing vendor reviews between audits.
- Skills bundle their own instructions and tools, loading on demand rather than on every turn
- Plans execute as observable step-runs with provenance-aware approvals and async sub-agents
- AI authors deterministic recipes; the recipes then run without AI in the loop, so auditors can trust the output
episki vs Scrut Automation — frequently asked questions
Yes, though not primarily on price — Scrut's bundling is already strong. The difference is what the platform does with the evidence. episki evaluates every collection and writes pass, fail, or inconclusive against the control, raises findings on failure, and supports approved exceptions that expire. It also leans further into autonomy, with agents drafting the work rather than guiding you through it.
{
"On packaging, largely yes, and that is worth saying plainly": {
" Both avoid the per-framework and per-seat taxes that Vanta, Drata, and Scytale apply": {
" Two things still differ": "episki publishes its price rather than quoting it, and episki charges no onboarding fee, where a one-time onboarding cost is commonly reported for Scrut."
}
}
}
{
"It matters if your evidence lives in a long tail of niche SaaS tools — Scrut's integration count is higher and its framework library is larger": {
" episki's connectors are fewer and deeper": "each one evaluates what it collected and writes deterministic control coverage, with AWS spanning multiple accounts, regions, and Organizations. Breadth and rigor are different purchases."
}
}
When a control legitimately fails — a deliberately public artifacts bucket, say — most platforms let you accept or exclude the finding. In episki an exception points at one check and the specific records it covers, requires a recorded approver and justification, and has a window. When the window closes, the control returns to failing on its own. "Passed with an exception" stays distinguishable from "passed clean", which is what makes it honest in front of an auditor.
If your priority is the widest possible automated collection across a long tail of SaaS tools, or you need a framework from Scrut's larger library that episki does not ship, Scrut's breadth is hard to match at its price point. Its satisfaction scores among mid-market multi-framework teams are strong and well earned.
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