Autonomous GRC vs full-service compliance automation
Why teams evaluate Secureframe alternatives
Secureframe pairs automated evidence collection with a guided, full-service workflow, and its integration library is broad. For organizations that want a hands-held path with deep automation, that combination works well.
Teams look for alternatives when they want the program to run itself and pricing they can see:
- Work that runs itself — instead of guided steps and collected evidence, agents draft the policies, narratives, and questionnaire answers, and the team approves.
- Transparent pricing — Secureframe's custom, quote-based model is hard to budget for. episki publishes a flat platform price with unlimited users, frameworks, and vendors, and AI tokens are the only metered resource.
- Built-in AI governance — episki ships a dedicated AI Governance module and maps ISO 42001, NIST AI RMF, and the EU AI Act out of the box.
Where episki is different
Legacy GRC automates evidence collection. episki automates the program. Agents draft policies, answer questionnaires, map controls across frameworks, and recommend tasks — and the AI authors deterministic recipes that then run without AI in the loop, so the output is reproducible and defensible in front of an auditor. A human always approves the work that matters.
Underneath the agents is a connected workspace: programs, assessments, controls, tasks, risks, and evidence link together, and a fast, keyboard-first editor makes the daily work of writing and reviewing feel like a modern tool.
When Secureframe might still be the better fit
Secureframe is a strong choice for organizations that want deep automated evidence collection across a wide integration library combined with a guided, full-service workflow. If that hands-held automation breadth is your single most important requirement — and a custom quote process is acceptable — Secureframe is compelling.
episki vs Secureframe: feature comparison
| Feature | episki | Secureframe |
|---|---|---|
| Approach | Autonomous GRC — agents run the program; humans approve the work that matters | Automated evidence collection with a guided, full-service workflow |
| Pricing model | Published flat pricing — platform $750/mo (or $7,500/yr) + optional modules; unlimited users, frameworks, and vendors. Only AI tokens are metered, and every model call is attributed to a surface and an operation so you can see what consumed them | Custom, quote-based pricing tied to company size and frameworks |
| AI capabilities | Agents draft policies, answer questionnaires, map controls, and recommend tasks — AI authors deterministic recipes auditors can accept | AI-powered compliance copilot and questionnaire automation |
| Controls & evidence | Continuous controls that produce a verdict — every check evaluates the evidence it collected and writes pass, fail, or inconclusive against the control, and a failing check raises a finding. Empty or undecodable evidence returns inconclusive and attests nothing | Automated evidence collection with 200+ integrations |
| Risk management | Risk module — qualitative and quantitative scoring, treatments, and acceptance wired to controls and evidence | Risk management with quantitative scoring and treatment plans |
| 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 | Dedicated ISO 42001 framework support, cross-mapped to ISO 27001 and SOC 2 |
| Framework coverage | 34+ pre-built frameworks (SOC 2, ISO 27001, HIPAA, PCI DSS, NIST CSF, CMMC, FedRAMP, ISO 42001) plus custom — all unlimited | SOC 2, ISO 27001, HIPAA, PCI DSS, GDPR, and 15+ frameworks |
| 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 | 200+ integrations |
| 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, with boundaries usually separated into their own workspace |
| Remediation workflow | Bi-directional Jira, Linear, and GitHub sync — remediation lives in the tracker your engineers already use, and status flows back without anyone copying it | Ticketing integrations that push tasks outward |
| API & agent access | REST API, a published entity-ontology catalog with a drift checksum, and a hosted MCP server (OAuth 2.1 + PKCE, 20 tools) 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, webhooks, and an MCP server in beta |
| Editor experience | Notion-like, keyboard-first editor for policies, narratives, and responses | Structured interface with guided workflows |
Why teams switch from Secureframe to episki
- Agents draft policies, narratives, and questionnaire answers from your evidence
- AI authors deterministic recipes; the recipes then run without AI in the loop, so auditors can trust the output
- Continuous controls and evergreen evidence linked to programs, tasks, and risks
- No custom quotes or negotiations to see real pricing
- Unlimited users and vendors; only AI tokens are metered
- Annual prepay gives two months free; Operator Partner discounts for vCISO and MSP firms
- 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