NERC CIP, Critical Infrastructure & Enterprise GRC
Compliance programs fail between audits—especially in spreadsheets. Context GRC runs inside your network, using 13 drift engines to route deviations to the people who own them. Purpose-built for NERC CIP and critical frameworks, with automation where every AI-proposed change waits for a named, authenticated reviewer before it takes effect.
Platform
Cloud SaaS requires surrendering your data. Enterprise suites take a year to configure. Spreadsheets break silently between audits. Here is how Context GRC closes the gap.
| Need | Legacy enterprise GRC suite | Workflow platform with a GRC module | Cloud compliance automation SaaS | Federal authorization toolchain | Spreadsheets & shared drives | Context GRC |
|---|---|---|---|---|---|---|
| Runs fully on premises or air-gapped | Often | Sometimes | Rarely | Often | Yes | Yes |
| Local AI with source citations | Rarely | Rarely | Rarely | Rarely | No | Yes |
| Cyber-physical asset modeling (ESP, PSP, SCI) | Rarely | Rarely | Rarely | Sometimes | Manual | Yes |
| NERC CIP content prepackaged | Sometimes | Rarely | Rarely | Rarely | Manual | Yes |
| Continuous drift detection | Rarely | Sometimes | Often | Sometimes | No | Yes |
| Offline license verification | Rarely | Rarely | No | Sometimes | Not applicable | Yes |
| Auditors at no seat cost | Rarely | Rarely | Rarely | Rarely | Yes | Yes |
| Named human approval recorded for AI-proposed changes | Varies | Varies | Varies | Varies | Varies | Yes |
This table reflects general market patterns and each organization's own evaluation will vary.
The 13 Canonical Drift Engines
Thirteen engines run in two families. Six positive engines build forward momentum. Seven negative engines protect against decay. Each context keeps its own settings and history.
positive_olir_driftPRODUCING_VALUEFramework-agnostic: engines read your own records in each context.
positive_evidence_renewalPRODUCING_VALUEFramework-agnostic: engines read your own records in each context.
positive_morning_briefingPRODUCING_VALUEFramework-agnostic: engines read your own records in each context.
positive_policy_blast_radiusPRODUCING_VALUEFramework-agnostic: engines read your own records in each context.
positive_ai_telemetry_flywheelPRODUCING_VALUEFramework-agnostic: engines read your own records in each context.
positive_document_approval_driftPRODUCING_VALUEFramework-agnostic: engines read your own records in each context.
Catalyst AI
AI runs on local models by default, and binds to loopback only, and there are no runtime calls to public content networks. Pointing the platform at an inference endpoint is a deliberate administrator decision that belongs to your organization.
Policy Catalyst
Draft, extract, and gap-analyze policies against active frameworks.
Audit Catalyst
Review evidence readiness, workpapers, and finding summaries.
Risk Catalyst
Surface, score, and prioritize operational and compliance risk.
Remediation Catalyst
Generate corrective action plans with RACI assignments.
Crosswalk Catalyst
Map and verify requirements across disparate frameworks.
Holistic Advisor
End-to-end guidance spanning policy, audit, risk, and remediation.
IBM Granite 4.2 (8B / 30B) Primary reasoning and draftingApache-2.0Phi-4 14B Reasoning, selectable by hardware tierMITMistral-Nemo 12B Reasoning, selectable by hardware tierApache-2.0Granite Guardian 4.1 (8B) Independent Context Guardian judgeApache-2.0nomic-embed-text Local embeddings for retrievalApache-2.0Each model is verified against its manifest family, not just its tag, so a renamed model cannot slip into a runtime pipeline. Model, threads, and context window adapt to host hardware.
Justify deferring the monthly patch cycle for the relay gateways under CIP-007 R2.
1. Bottom lineA deferral can be supported only if the 35-day patch evaluation and mitigation plan are documented for each affected asset.
2. Context-bound analysisYour Patch Management Procedure (POL-4) requires a mitigation plan when a security patch cannot be applied within the evaluation window.
3. Remediation stepsRecord the vendor advisory, attach the compensating controls, and route the plan to the Accountable approver.
4. Next questionDo you want a draft mitigation plan staged in the Action Center for approval?
What does our policy say about satellite clock sources?
Zero-trust abstention
No active records cover satellite clock sources in this context yet. I will not infer an answer. Would you like help drafting a net-new policy record?A single-model assistant grades its own confidence. Context GRC adds an independent local judge, IBM Granite Guardian (granite4.1-guardian:8b), so the model that drafts an analysis is not the model that clears it.
Groundedness verification
Checks drafted controls, root cause analyses, and crosswalk deltas against source documents before they are rendered or applied.
Compliant substitution
When a proposal breaks an organizational rule, such as external cloud MFA, Guardian substitutes the approved alternative, such as on-premises RADIUS or TACACS+ MFA, and de-duplicates sibling options.
Two-Key evidence gate
Evidence is never auto-accepted on one model's score. It needs the primary pass confidence and a clean Guardian groundedness verdict; otherwise it is staged for human review.
Protection scorecard
A four-KPI banner tracks outputs screened, disallowed controls substituted, ungrounded outputs intercepted, and unsafe queries blocked.
Apply to Action Center or Risk Register is an explicit click by a named person; nothing is applied on the model's say-so.
Five placements: Chat input screening, Retrieval output groundedness, Extraction validation, Egress screening, Agentic function calls. Guardian is an administrator-enabled capability.
Human-in-the-Loop Approval
Before an audit, you will be asked who authorized a change. Context GRC stages AI-proposed work for review and records the reviewer's decision against an authenticated account.
AI_PROPOSESA local model drafts a control, mapping, mitigation, or action.
PENDING_REVIEWNothing changes your data. The item is staged in the Action Center.
APPROVED | REJECTEDAn authenticated user with a role in that context approves or rejects.
LEDGER_ENTRYActor, role, context, timestamp, and outcome land in the audit ledger.
Approvals are attributable to a named, authenticated user: PBKDF2 credentials, TOTP multi-factor authentication, and per-context roles.
AI-proposed items stay pending until a person acts on them. Rejected suggestions are not suggested again.
The reviewer's decision, with the original AI output beside any human edit, is recorded. The audit ledger is hash-chained and tamper-evident, and auditors can search the audit trail.
Two-Key evidence gate
Evidence is not auto-accepted on one model's score. Administrator-enabled.
Guardian screening
An independent local judge checks groundedness. Administrator-enabled.
Role-scoped routing
Unassigned items go only to administrator and compliance roles in that context.
Designed to support your audit evidence; it does not confer certification.
Continuous Evidence & Cryptographic Assurance
A hash-chained audit ledger makes after-the-fact edits detectable, so an auditor can trust the trail as well as the artifacts.
Evidence and policy content flow in from the connectors your administrators configure.
Evidence is stored, tracked, and recoverable.
One-click cryptographic sealing of an engagement packet.
Artifacts map directly to regulatory requirements as well as controls. CONTINUITY_RETAINED keeps evidence on the requirement when a control is unmapped or retired.
Evidence inheritance across crosswalks links proof to equivalent controls without duplicating files.
Utility Architecture
Context GRC deploys as a containerized stack on premises or in a private cloud. Connectors and an optional inference endpoint sit outside the boundary and are administrator-controlled.
Request a Pilot
Built for electric utilities and bulk electric system entities. Tell us where compliance work slows you down and we will follow up.
Trust & Security
Designed to support your programs. It does not confer certification.
Containerized on-prem or private cloud. Every front-end library is vendored locally with documented licenses and SHA-256 manifests, so there are no runtime CDNs.
PBKDF2-HMAC-SHA256 at 600,000 iterations, a NIST SP 800-63B passphrase policy, and TOTP multi-factor authentication.
Integration credentials are Fernet-encrypted with a rotation script. Secrets are injected through Docker secrets.
TLS between services and a hash-chained, tamper-evident audit ledger of recorded actions.
Ed25519-signed task envelopes, a least-privilege worker database role under row-level security, pre-persistence DLP screening, and fenced untrusted document text in prompts.
Role-based access with per-context role grants, and context-scoped views and roles.
177 exact-pinned packages with about 3,000 SHA-256 hashes. CI gates: Bandit, TruffleHog, pip-audit --strict, a copyleft license gate, and Trivy.
AI-proposed controls, mappings, and actions are staged for a named, authenticated reviewer to approve across four triage touchpoints, with the decision recorded. Cmd+K opens the command palette.