Automate your
enterprise RFPs.
Stop wasting hundreds of hours on manual security questionnaires. ProposalFlow uses deep RAG to generate highly accurate, source-cited responses instantly.
"Before building ProposalFlow, I spent 6 years as an Enterprise Solutions Architect. I watched brilliant engineering teams lose 40% of their bandwidth copy-pasting answers into 300-row Excel security questionnaires. We didn't build this to be another 'AI wrapper'—we built this to reclaim human capital."
Engineered for precision.
Deep RAG Engine
Matches semantic intent to your knowledge base.
Parallel Synthesis
Drafts 200-question RFPs concurrently.
Hallucination-Free
No guesses. If it's missing, the engine flags it.
Risk Guardrails
Auto-flags commercially risky requirements.
Semantic Indexing
Vectors large PDFs for fast retrieval.
Brand Alignment
Drafts in your authoritative voice.
How TechCorp reduced RFP response time by 88%.
TechCorp, a leading B2B SaaS provider, struggled with a 3-week turnaround time for enterprise security questionnaires. By deploying ProposalFlow's isolated RAG architecture, they indexed their entire Trust Center and previous SOC 2 mappings.
- Reduced completion time from 120 hours to 14 hours.
- Achieved 99.2% accuracy against InfoSec audit standards.
- Reclaimed $240,000 in annualized engineering bandwidth.
"ProposalFlow completely changed our sales cycle. We no longer drag our principal engineers into procurement calls. The AI maps our SOC 2 controls perfectly to custom questionnaires."
Witness the intelligence.
1. Knowledge Library
Securely index proprietary data for the AI's source of truth.
Drop Files
2. Generation
Submit the target RFP for parallel draft synthesis.
Select Target RFP
Frequently Asked Questions
Technical clarifications regarding data sovereignty, model training, and integration.
Do you use our proprietary data to train foundation models?
Absolutely not. We operate under strict tenant isolation. Your uploaded documents are converted into vector embeddings stored in an isolated namespace. We do not use any client data to fine-tune or train the underlying Large Language Models.
How does the system prevent AI hallucinations?
ProposalFlow utilizes a constrained Retrieval-Augmented Generation (RAG) architecture. The model is strictly instructed to only answer using the retrieved context from your Knowledge Library. If the answer does not exist in your docs, the system will explicitly state 'No exact match found in KB' rather than guessing.
Is ProposalFlow SOC 2 compliant?
Yes. Our entire infrastructure is SOC 2 Type II aligned, utilizing AES-256 encryption at rest and TLS 1.3 in transit. We conduct regular penetration testing and vulnerability scanning.