What a AI Disaster Recovery Planning Tool actually does
Generates IT disaster recovery runbooks from infrastructure diagrams, extracts dependency maps from CMDB exports, creates realistic tabletop exercise scenarios, and performs gap analysis against ISO 22301 and NIST 800-34 controls — all branded under the MSP's own name.
Disaster recovery planning is document-creation work: runbooks, dependency maps, tabletop scenarios, gap analyses. An experienced MSP engineer typically spends 20–40 hours per client per year on DR documentation maintenance. An AI-assisted platform cuts that to 5–8 hours by auto-generating first drafts that the engineer reviews, validates, and approves. Claude Opus 4.8 handles the high-stakes runbook drafting where accuracy is auditor-facing; Sonnet 4.6 handles tabletop scenarios where creative scenario design matters more than precision; Voyage voyage-3-large embeddings retrieve the right compliance framework sections when the MSP asks 'how does our current RTO of 4 hours compare to what ISO 22301 recommends for a Tier-1 system?'
The demand driver is regulatory: ISO 22301 for business continuity, NIST 800-34 for federal-touching clients, HIPAA contingency plan rule for healthcare, and FFIEC handbook for financial services. MSPs selling DR services to regulated industries face increasing audit pressure — clients are asked to demonstrate that DR plans were tested, that RTO/RPO targets were validated, and that runbooks were actually executable. An MSP with a branded AI-assisted platform that produces auditor-ready documentation has a genuine competitive advantage over one handing clients a Word document updated annually.
AI capabilities involved
LLM-drafted runbooks from infrastructure diagrams and CMDB data
Tabletop exercise scenario generation
Compliance gap analysis against ISO 22301 / NIST 800-34
Dependency map extraction from CMDB or ServiceNow exports
Who uses this
- IT MSPs selling DR planning as a recurring service to healthcare, finance, and manufacturing clients
- BCP consultancies that create and maintain DR plans for 10–40 mid-market clients
- GRC (governance, risk, compliance) firms that include DR documentation in their compliance service packages
- Enterprise IT teams that want an internal branded tool for maintaining DR documentation across multiple business units
SaaS alternatives on the market
Real products you can sign up for today — with current 2026 pricing, honest pros and cons.
Cutover
Large enterprises with complex, multi-team DR exercises that need orchestrated runbook execution with real-time status tracking.
Enterprise quote
Pros
- +Purpose-built for runbook automation and DR test orchestration.
- +Strong audit trail for test execution — shows what ran, what failed, and at what time.
- +Integration with ServiceNow, Jira, and PagerDuty for live DR test execution.
- +Real-time status tracking during failover exercises.
Cons
- −No white-label — Cutover brand is on every client-facing screen.
- −Enterprise quote minimum excludes most MSP clients.
- −AI runbook generation is not the platform's strength — it executes runbooks, not drafts them.
- −Complex implementation requiring Cutover professional services.
Castellan Solutions
Large enterprises in regulated industries that need a full BCM platform with BIA, risk assessment, and audit-trail documentation.
Enterprise quote
Pros
- +Full BCM (Business Continuity Management) platform covering BIA, risk assessment, plan management, and exercise tracking.
- +Strong compliance framework alignment (ISO 22301, NIST, FFIEC).
- +Consultant partner program — Castellan-certified consultants can resell implementation.
- +Multi-site plan management with approval workflows.
Cons
- −No white-label platform resale — the consultant channel is implementation services, not branded SaaS.
- −Enterprise pricing excludes small-to-mid-market MSP clients.
- −AI capabilities are limited — documentation is primarily template-driven, not LLM-generated.
- −Long implementation cycles reduce how many clients an MSP can service per year.
Quantivate
Mid-market companies in regulated industries that need affordable BCM software with industry-specific templates.
$5K+/yr
Pros
- +More accessible pricing than Cutover or Castellan.
- +Covers GRC, BCM, and vendor risk management in one platform.
- +Pre-built plan templates for common industries (banking, healthcare).
Cons
- −No white-label.
- −AI capabilities are minimal — template-based documentation, not LLM-generated.
- −Interface can be dated compared to modern SaaS platforms.
- −Limited CMDB integration for automated dependency mapping.
The AI stack
The DR planning stack is accuracy-first: Opus 4.8 for runbooks (auditor-facing), Sonnet 4.6 for tabletop scenarios (realistic but not legally critical), Voyage voyage-3-large for compliance retrieval (high precision required). Cost is secondary to quality in this category.
Runbook generation from infrastructure description
Drafts step-by-step failover runbooks from the client's infrastructure inventory, RTO/RPO targets, and dependency map.
Claude Opus 4.8 ($5/$25 per M)
$5/$25 per M tokens; ~$0.025 per runbook (1K in + 800 out tokens)All production runbooks for Tier-1 systems (ERP, core banking, EHR, email) that must survive audit scrutiny.
Claude Sonnet 4.6 ($3/$15 per M)
$3/$15 per M tokens; ~$0.005 per runbookTier-2 and Tier-3 system runbooks where the stakes of a minor error are lower.
Our pick: Opus 4.8 for Tier-1 critical systems (as classified by the client's BIA). Sonnet 4.6 for Tier-2 and Tier-3 systems. Gate all runbooks with an explicit human-review and sign-off step before storing as 'approved' in the client record.
Tabletop exercise scenario generation
Creates realistic, detailed scenario narratives for DR tabletop exercises — tailored to the client's industry, threat environment, and system inventory.
Claude Sonnet 4.6 ($3/$15 per M)
$3/$15 per M tokensComplex, industry-specific tabletop scenarios (ransomware at a regional bank, supply-chain disruption at a manufacturer).
DeepSeek V4 Flash ($0.14/$0.28 per M)
$0.14/$0.28 per M tokensSimple tabletop scenarios for Tier-3 systems or clients with low regulatory exposure.
Our pick: Sonnet 4.6 for regulated-industry clients (healthcare, finance, government). DeepSeek V4 Flash for simple scenarios or when generating 20+ scenario variants for a scenario library. Total cost per exercise design: $0.05–$0.25.
Compliance framework retrieval and gap analysis
Retrieves the specific control statements from ISO 22301, NIST 800-34, HIPAA, or FFIEC that apply to the client's current DR posture and identifies gaps.
Voyage voyage-3-large ($0.18/M) + Claude Opus 4.8
$0.18/M to embed + $5/$25 per M for Opus 4.8 gap narrativeFormal compliance gap analyses for healthcare (HIPAA), federal (NIST 800-34), financial (FFIEC), or international (ISO 22301) clients.
Voyage voyage-3.5 ($0.06/M) + Claude Sonnet 4.6
$0.06/M to embed + $3/$15 per M for Sonnet 4.6Preliminary gap assessments or internal awareness exercises before a formal compliance project.
Our pick: Voyage voyage-3-large + Opus 4.8 for any gap analysis that will be shared with an auditor or used as the basis for a client compliance commitment. Voyage voyage-3.5 + Sonnet 4.6 for internal assessments.
CMDB dependency map extraction
Parses CMDB exports (ServiceNow, Freshservice, or CSV) to extract system dependency chains and generate human-readable dependency maps.
Claude Sonnet 4.6 ($3/$15 per M)
$3/$15 per M tokensProduction CMDB parsing for clients with 50–500 CIs (configuration items) in their CMDB.
Our pick: Sonnet 4.6 for CMDB parsing. Pre-process large CMDB exports (>1,000 CIs) with a Python script to reduce to the relevant subset before sending to the LLM — reduces token cost and improves focus.
Reference architecture
The platform ingests client infrastructure data (CMDB exports, IT asset inventories, previous DR plans), indexes compliance frameworks in a vector store, and produces a library of DR artifacts per client — all gated by human engineer review before use. The hardest engineering challenge is CMDB integration: every client has a different CMDB schema and data quality, making dependency extraction the most variable part of the pipeline.
Client onboarding: infrastructure inventory, BIA results, RTO/RPO targets, CMDB export uploaded
Next.js client-onboarding form → Supabase client_profiles tableStructured intake: system count and tiers (Tier 1/2/3), RTO and RPO per tier, regulatory frameworks in scope (HIPAA/NIST/FFIEC/ISO 22301), previous DR plan (PDF upload optional). CMDB export (CSV or JSON) uploaded to Supabase Storage.
CMDB dependency map extracted and visualised
Python preprocessing → Sonnet 4.6 Edge Function → D3.js or Mermaid diagramSonnet 4.6 parses the CMDB export, identifies upstream/downstream dependencies for each Tier-1 and Tier-2 system, and outputs a structured JSON dependency graph. Displayed as a Mermaid.js diagram in the platform.
Compliance framework indexed on first deployment
Voyage voyage-3-large → pgvector (Supabase) — done once per frameworkISO 22301:2019, NIST 800-34, HIPAA Contingency Plan rule, and FFIEC Business Continuity handbook broken into 200-token chunks and embedded. Stored in a shared vector index (not per-client — frameworks are common across all clients).
Gap analysis run against client's current DR posture
Voyage voyage-3-large retrieval → Opus 4.8 gap narrativeClient's BIA, RTO/RPO targets, and existing DR artifacts used to query the framework index. Top 10 relevant control statements retrieved per framework. Opus 4.8 writes the gap narrative: which controls are met, which are partially met, which are not addressed.
Runbook drafted for each Tier-1 system
Supabase Edge Function → Opus 4.8 (Tier-1) or Sonnet 4.6 (Tier-2/3)Prompt includes system name, RTO target, dependency chain from CMDB map, and infrastructure description. Output: step-by-step failover runbook with roles, commands (sanitised — no live credentials), estimated time per step, and validation checkpoints.
MSP engineer reviews, edits, and approves each runbook
Next.js document editor with version historyAll AI-generated runbooks show as 'draft — engineer review required.' Engineer edits inline, marks validated steps, and approves. Approved status logged with approver ID and timestamp in immutable audit table.
Tabletop exercise generated and packaged as facilitator guide
Sonnet 4.6 Edge Function → PDF exportInput: client's industry, Tier-1 system list, regulatory frameworks, and requested scenario type (ransomware, cloud outage, natural disaster, third-party failure). Output: 3-hour tabletop guide with 15-minute scenario injects, discussion questions per inject, and debrief template.
RTO/RPO drift detection: quarterly automated comparison
Scheduled Edge Function → Sonnet 4.6Quarterly comparison of current IT inventory against approved runbooks — detects new systems without runbooks, systems that have changed configuration, and RTO targets that have been revised by the client but not yet reflected in runbooks. Outputs a drift report for engineer review.
Estimated cost per request
~$0.025 per runbook draft (Opus 4.8, ~1K in + 1K out tokens); ~$0.005 per tabletop scenario draft (Sonnet 4.6); ~$0.0054 per gap-analysis query (voyage-3-large retrieval + Opus 4.8)
Cost calculator
Drag the sliders to model your actual usage. The numbers update in real time so you can stress-test economics before writing a single line of code.
Cost is dominated by initial setup per client (CMDB parsing, runbook generation, gap analysis) rather than ongoing monthly cost. After initial setup, the main cost is quarterly drift detection and annual runbook refresh.
Estimated monthly cost
$50.42
≈ $605 per year
Calculator notes
- Onboarding cost per client (one-time): CMDB parsing ~$0.05, gap analysis ~$0.10, all Tier-1 runbooks ~$0.20 total. Under $0.40 per client onboarding in AI costs.
- Ongoing monthly: at 20 clients × $0.02 quarterly drift detection amortised = $0.40/mo total. Fixed infra = $50/mo. Total platform cost ~$51/mo at 20 clients.
- Tabletop exercise generation: ~$0.10–$0.25 per exercise per client × 2/year × 20 clients = ~$4–$10/year. Effectively free.
- Annual runbook refresh: 20 clients × 8 Tier-1 systems × $0.025/runbook = $4/year. AI costs are not the constraining factor in this business — engineer review time is.
Build it yourself with vibe-coding tools
A Lovable tabletop-exercise builder — where you load a fictional scenario and run through the AI-generated inject sequence — is an excellent prospect demo tool. It is not suitable for delivering real DR plans to regulated clients.
Time to MVP
12–16 hours (tabletop demo only)
Total cost to MVP
$25 Lovable Pro + ~$30 Anthropic API credits
You'll need
Starter prompt
Build a DEMO of an AI disaster recovery planning assistant for an IT MSP. This is for prospect demonstrations only, not for delivering real DR plans. Use Next.js App Router + Supabase + Tailwind. Functionality: 1. Simple client intake form: client_name, primary_industry (dropdown), top 3 IT systems (name + RTO_hours + RPO_hours each), regulatory_framework (checkbox: ISO 22301 / NIST 800-34 / HIPAA / FFIEC) 2. Infrastructure description field: free-text box where user pastes a description of the IT environment (servers, cloud services, databases, dependencies) 3. 'Generate Runbook' button for each system: calls Opus 4.8 with prompt: 'Write a disaster recovery runbook for {system_name} with RTO of {rto_hours} hours and RPO of {rpo_hours} hours. Infrastructure context: {infrastructure_description}. The runbook should cover: Pre-failure detection indicators, Initial response steps (first 15 minutes), Failover activation procedure, Data recovery and validation, Service restoration sequence, Communication plan. Format as numbered steps with estimated duration per step and responsible role.' 4. 'Generate Tabletop Scenario' button: calls Sonnet 4.6 with: 'Create a 3-hour tabletop exercise scenario for {client_name} in the {primary_industry} industry covering a {scenario_type} incident affecting {system_name}. Include: scenario narrative (15 min), 4 inject events at 30-minute intervals, discussion questions per inject, and debrief guide.' 5. Gap analysis tab: text area for user to describe current DR posture, then Opus 4.8 identifies top 3 gaps vs the selected regulatory_framework and suggests remediation steps. 6. Large disclaimer banner on every page: 'DEMONSTRATION ONLY — Generated content requires qualified IT professional review. Not a substitute for professional DR planning services.' Data model: - demo_clients (id, name, industry, systems_json, regulatory_frameworks_array) - generated_artifacts (id, client_id, artifact_type, content, created_at) Save all generated content to Supabase so the MSP can refer back during the prospect demo.
Paste this into Lovable
Follow-up prompts (run in order)
- 1
Add a Mermaid.js dependency diagram generator: ask the user to describe system dependencies in plain English ('the web app depends on the database, which depends on the backup service'), call DeepSeek V4 Flash to convert this to Mermaid flowchart syntax, and render the diagram on the page.
- 2
Add a scenario inject timeline view: display the 4 tabletop scenario injects as a horizontal timeline with the 30-minute intervals marked. Show the discussion questions for each inject in an expandable accordion below the timeline.
- 3
Add a PDF export button that downloads the runbook and tabletop guide as a branded PDF with the MSP's name in the header. Use browser print or a simple react-pdf layout.
- 4
Add a comparison view: show what the Lovable demo produces vs what a production RapidDev build would add (CMDB integration, full framework indexing, version history, immutable audit trail, quarterly drift detection). This turns the demo into a closing tool.
Expected output
A polished demo of AI-assisted DR planning — runbook generation, tabletop scenario creation, gap analysis — that convinces IT MSP prospects that AI can meaningfully accelerate their DR service delivery.
Known gotchas
- !Opus 4.8 runbook generation takes 15–40 seconds depending on infrastructure complexity. Add a visible progress indicator and explain to the prospect that this is the model accuracy/speed tradeoff — the 35-second wait prevents the kind of errors that fail audits.
- !NIST 800-34 and ISO 22301 retrieval requires a pre-indexed vector store of the framework documents — not achievable in the demo version without significant additional work. The demo's 'gap analysis' is a zero-shot LLM call, not semantic retrieval; label it clearly as preliminary.
- !CMDB parsing is the hardest part and is not included in the Lovable demo. When prospects ask 'how does it handle our ServiceNow data?', be honest: the production build integrates with ServiceNow REST API; the demo uses manual infrastructure description.
- !Opus 4.8's new tokenizer uses up to 35% more tokens than previous Anthropic models for the same input. Budget accordingly — a detailed infrastructure description with 15 systems can consume 2,000+ input tokens per runbook call.
- !Immutable audit logging for DR test exercises requires PostgreSQL INSERT-only policies that Lovable won't configure correctly by default. This is a production requirement that must be specified explicitly to RapidDev.
- !DR plans must be living documents — the Lovable demo produces a one-time artifact with no version control or scheduled refresh. This limitation is fine for a demo but must be addressed in production.
Compliance & risk reality check
A DR planning platform is directly adjacent to the compliance frameworks it documents against — which means the platform itself must meet the security standards it helps clients achieve. This creates a somewhat recursive compliance obligation.
ISO 22301 Business Continuity Management alignment
ISO 22301:2019 specifies requirements for BCMS (Business Continuity Management Systems). If clients claim ISO 22301 compliance partly on the basis of documentation produced by your platform, the platform's methodology must be defensible to an external auditor. Key requirement: plans must be tested, validated, and revised regularly — the platform must support version history, test records, and revision dates.
Mitigation: Build explicit version control for all generated artifacts (runbook v1, v2, v3 with change log). Record tabletop exercise dates and participants in the platform. Support a structured annual review workflow where each runbook is re-validated. Document the AI-generation methodology in a platform data sheet that clients can include in their BCMS documentation.
NIST 800-34 for federal-touching clients
NIST SP 800-34 Rev. 1 (Contingency Planning Guide for Federal Information Systems) defines specific plan elements (CP-1 through CP-10 controls, BIA methodology, RTO/RPO classification). Plans for systems categorised as MODERATE or HIGH impact must meet specific content requirements. AI-generated plans that miss required elements can cause federal clients to fail FISMA assessments.
Mitigation: Index NIST 800-34 Rev. 1 in the compliance framework vector store with high precision (Voyage voyage-3-large). Include a 'NIST 800-34 compliance checklist' as a required section in all plans for federal-touching clients. Flag any generated plan that lacks required elements (BIA results, RTO/RPO per system classification, offsite storage plan, alternate processing site).
HIPAA Contingency Plan rule (45 CFR § 164.308(a)(7))
HIPAA Security Rule requires covered entities and business associates to implement a contingency plan including: data backup, disaster recovery, emergency mode operation, testing and revision procedures, and applications and data criticality analysis. HIPAA auditors examine whether the contingency plan is current, tested, and actually executable — not just documented.
Mitigation: For healthcare clients, include a HIPAA-specific runbook template that addresses all five required elements. Record tabletop test dates and outcomes in the platform. Generate annual revision reminders. If the MSP is itself a business associate handling PHI-adjacent IT systems, a HIPAA BAA with the client is mandatory.
SOC 2 Type II for MSP platform security
Mid-market and enterprise clients evaluating your DR planning service will ask for your SOC 2 Type II. As an MSP handling client IT infrastructure documentation (including details that could be used to map attack surfaces), security expectations are high. Without SOC 2 Type II, you lose deals above $500/mo retainer value.
Mitigation: Start SOC 2 Type II preparation as soon as you sign 3+ enterprise clients. Key controls: encryption at rest and in transit, access control per client (no engineer at client A can see client B's runbooks), immutable audit log of all AI generation calls and human edits, MFA on all platform access.
FFIEC Business Continuity handbook for financial clients
The FFIEC Business Continuity Management booklet (updated January 2019) sets expectations for financial institutions' recovery planning. Regulators (OCC, Fed, FDIC) examine BCM programs during safety-and-soundness exams. Plans must cover interconnections and third-party dependencies — content that aligns with CMDB dependency mapping but requires additional financial-sector context.
Mitigation: Index the FFIEC BCM booklet as a separate vector corpus. Include a financial-services runbook template that addresses connection testing, third-party service provider recovery objectives, and pandemic planning requirements. Recommend clients have their legal/compliance team review all FFIEC-aligned plans before exam preparation.
Build vs buy: the real math
14–22 weeks
Custom build time
$35,000–$80,000
One-time investment
6–12 months
Breakeven vs buying
An MSP with 20 healthcare and finance clients each paying $500/mo for DR-as-a-service generates $10,000/mo MRR. The platform at $35K–$80K breaks even in 4–8 months. After breakeven, ongoing platform cost is approximately $50/mo in infrastructure + under $10/mo in AI costs — roughly 99.4% gross margin on the DR service revenue. Quantivate at $5K+/yr with no white-label has you paying per-client per-year with no asset appreciation; a custom build is a platform asset you own outright. As compliance frameworks update (ISO 22301 revision expected 2024–2025, NIST 800-34 Rev. 2 in draft), your vector indexes need updating — a maintenance cost you control versus a vendor dependency you don't.
Skip the DIY — RapidDev builds the production version
A Lovable MVP gets you a demo. Production needs auth that doesn't leak data, AI calls that don't bankrupt you, observability when models drift, and code you can audit. That's what we ship.
Discovery call (free)
30 minWe map your exact AI Disaster Recovery Planning Tool use case: who uses it, target volume, AI model choice, integrations, compliance scope. You get a detailed scope document and fixed-price quote within 48 hours.
AI-accelerated build
14–22 weeksOur engineers use Claude Code, Lovable, and custom tooling to ship 3–5x faster than agencies. You see weekly progress in a staging environment — not a black box.
Launch + handoff
1 weekWe deploy to your infrastructure, transfer the GitHub repo, set up CI/CD and monitoring, and train your team. You own 100% of the source code, prompts, and model configurations.
What you get
Timeline
14–22 weeks
Investment
$35,000–$80,000
vs SaaS
ROI in 6–12 months
30-min call. Fixed-price quote within 48 hours. No commitment.
Frequently asked questions
How much does it cost to build a white-label AI disaster recovery planning tool?
Expect $35,000–$80,000 with RapidDev — above the standard band because compliance framework indexing (ISO 22301, NIST 800-34, HIPAA, FFIEC), CMDB integration, immutable audit logging, and per-client document versioning add meaningful scope. A tabletop demo on Lovable costs $25 + ~$30 in API credits and takes a weekend. Enterprise BCM SaaS (Cutover, Castellan) is quote-based with no white-label option.
How long does it take to ship this?
14–22 weeks with RapidDev for a production-grade platform — timeline is driven by compliance framework indexing quality, CMDB integration complexity (each client has a different CMDB schema), and the audit-log architecture that makes generated artifacts court-admissible. A Lovable demo takes one weekend.
Will AI-generated DR runbooks actually pass ISO 22301 or NIST audits?
Only if they're reviewed, validated, and approved by a qualified IT engineer who attests to their accuracy. AI-generated runbooks pass audits in the same way word-processor-created runbooks pass audits — because a qualified professional certified them. The AI generates an accurate, detailed first draft in 30 seconds that would otherwise take 4 hours; the MSP engineer validates it against the actual system configuration and signs off. The approval workflow and engineer attestation are non-negotiable features in the production platform.
What's the difference between disaster recovery planning and business continuity planning?
Disaster recovery (DR) is IT-focused: restoring systems, data, and infrastructure after a disruption event. Business continuity (BC) is business-process-focused: keeping the business operating during and after a disruption, which includes DR but also covers manual workarounds, alternate locations, supply chain contingencies, and communication plans. ISO 22301 covers BCM (Business Continuity Management) as a whole. NIST 800-34 covers IT contingency planning specifically. This platform is primarily DR-focused; BCP expansion adds a business-process module that is scoped separately.
Can the platform integrate with ServiceNow to automate CMDB dependency mapping?
Yes — the production RapidDev build includes a ServiceNow REST API integration that pulls CI records and dependency relationships directly. For clients on Freshservice, Jira Assets, or custom CMDBs, we implement custom connector logic during the build. The CMDB integration is the largest variable in build cost — a client with a clean ServiceNow implementation is a week of integration work; a client with a custom CMDB schema can be 3–4 weeks.
Can RapidDev build this for my MSP?
Yes — RapidDev has built 600+ production applications including compliance-critical platforms with immutable audit trails, vector-indexed framework libraries, and per-client document management. We scope the compliance frameworks your clients face, implement the CMDB connectors you need, and deliver a white-label platform your MSP can deploy to 20+ clients. Schedule a free 30-minute consultation at rapidevelopers.com.
Want the production version?
- Delivered in 14–22 weeks
- You own 100% of the code
- AI cost monitoring built in
30-min call. No commitment.
