RocketDocs
Library-first RFP, DDQ, and questionnaire response for regulated industries
Founded 1994 · Atlanta, GA · Private
What is RocketDocs?
RocketDocs is a library-first response management platform for RFPs, RFIs, DDQs, and security questionnaires. It has operated since 1994 and targets regulated industries — financial services, banking, healthcare, and life sciences — where data handling and audit requirements shape how proposal teams work. The platform combines a version-controlled content library with a private AI drafting layer.
How the automation works
RocketDocs answers questions through a layered engine rather than a single generative pass. It first tries an exact match against previously approved answers, then a nearest-neighbor search across the library, and finally a private generative draft when no close match exists. Astro, its AI engine built on Llama 3.1, produces those drafts from your approved knowledge base. Because the model draws on the library rather than live deal context, output quality depends on how well the library is maintained, and G2 reviewers describe the AI as retrieval-oriented and slower to learn than newer AI-native tools (as of July 2026).
Content governance
Governance is built around the library. Content is version-controlled, changes are logged to a full audit trail, and responses move through multi-stage approval gates before they ship. That structure suits compliance sign-off in regulated settings. It stops short of automatic conflict or staleness detection across connected sources, so keeping answers current remains a manual, owner-driven task.
Data residency and security
The private AI model is RocketDocs’ central differentiator. Per the vendor, Astro runs inside RocketDocs’ own environment and never sends customer data to a third-party model provider, with US and EU data residency options. The platform is SOC 2 Type II and ISO 27001 certified. For banking and life-sciences teams constrained by where and how data can be processed, that posture is often the deciding factor.
Where it fits
RocketDocs fits financial services, banking, and life-sciences teams that value data residency control, audit trails, and Microsoft-native workflows over the newest autonomous drafting. Teams that want deal-contextual, end-to-end AI generation, bulk document intake, or win-rate analytics should weigh the reviewer-cited limits on AI depth, manual upload, and reporting (G2, as of July 2026).
Scorecard
How we scoreGood for
- +Regulated teams that need private AI drafting with US/EU data residency
- +DDQ and security-questionnaire workflows requiring version control and audit trails
- +Microsoft-native environments working in Word, Excel, and SharePoint
- +Multi-stage approval and structured review gates for compliance sign-off
Not great for
- –AI is retrieval- and library-led rather than deal-contextual generation, so drafts need meaningful editing (G2 reviewers, as of July 2026)
- –Documents and questions are often loaded manually one by one, and large PDFs can hit upload limits (G2 reviewers, as of July 2026)
- –Search can require exact wording to surface approved answers (G2 reviewers, as of July 2026)
- –No published win/loss or proposal-outcome analytics (G2 reviewers, as of July 2026)
Capabilities
- Astro private generative AI that drafts from an approved knowledge base
- Three-layer answer engine — exact-match autofill, nearest-neighbor search, private drafting
- Auto-parsing of RFPs, RFIs, DDQs, and security questionnaires
- Version-controlled content library management
- Word and Excel export with audit-trail logging
Security & compliance
- SOC 2 Type II certified
- ISO 27001 certified
- Private AI keeps data inside RocketDocs' environment (no third-party model provider)
- US and EU data residency options
Collaboration
- Multi-stage approval workflows with structured gates
- Role-based access controls
- Complete audit-trail logging
- Version control on library content
Use cases
- RFP response
- DDQ automation
- Security questionnaires
- Knowledge base
Integrations
Pricing
- Model
- Quote
- Starting price
- $18,500/year
- Billing
- Annual, quote-based; Starter, Pro, and Enterprise tiers
Pricing as of July 2026. Source.
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FAQ
- Does RocketDocs use a maintained answer library?
- Yes. RocketDocs is library-first: it stores approved responses in a version-controlled content library and drafts new answers from that library using its Astro AI. Response quality tracks how current and complete the library is, so a content owner is needed to keep it fresh.
- What is Astro and how does it keep data private?
- Astro is RocketDocs' private AI engine, built on Llama 3.1. Per the vendor, it runs inside RocketDocs' own environment, drafts only from your approved knowledge base, and does not send your data to a third-party model provider. US and EU data residency options are available (as of July 2026).
- What does RocketDocs cost?
- RocketDocs publishes a starting price of $18,500/year and offers Starter, Pro, and Enterprise tiers, with final pricing quote-based on team size, content volume, and modules (as of July 2026).