# VaultAI Customer Research Pack

## Research Status

This WorkspaceData pack is buyer-facing secondary research and product-discovery material. It does not claim signed pilots, customer contracts, formal bank interviews, or independent regulatory certification. It is designed to show how VaultAI maps to real market pressure visible in public institutional sources.

## Research Method

1. Identify enterprise buyer segments with a direct economic reason to care about core banking modernization, deterministic ledgers, operational resilience, sovereign deployment, and M&A data-room intelligence.
2. Map each segment to publicly documented pressures from credible sources.
3. Convert each pressure into concrete product surfaces: dashboards, diligence docs, Figma screens, demo workflows, API surfaces, and acquisition-review evidence.
4. Keep all claims conservative and reviewable by a buyer.

## Market Pressure Signals

### Core Banking Modernization

McKinsey describes bank core systems as high-volume transaction engines that often interface with tens or hundreds of surrounding systems. It also notes that digital banking, APIs, real-time processing, fintech partnerships, frequent feature releases, elastic infrastructure, and faster M&A execution have increased pressure on older cores. McKinsey also describes integration as high-risk and high-cost, with traditional implementation costs potentially exceeding USD 50m for medium-size banks and reaching USD 300m to USD 400m for larger banks.

VaultAI buyer implication: a source-code asset that already packages ledger controls, migration evidence, data-room review, deployment files, and research artifacts can be positioned as a replacement-cost and time-to-market arbitrage asset rather than an ARR-multiple SaaS company.

### AI-Enabled Financial Engines

McKinsey's AI-core research frames the modern bank core as moving from passive transaction recording to intelligent, event-driven decision infrastructure. It identifies recurring pain points around slow product innovation, batch-driven processing, fragmented data, and high run costs.

VaultAI buyer implication: the product should be shown as an enterprise-control layer with event evidence, deterministic settlement rules, AI diligence, fraud/risk surfaces, and an executive terminal, not as a generic dashboard.

### Regulatory Resilience and Sovereignty

DORA and FMI cyber-resilience guidance give buyers a reason to ask for auditability, incident evidence, operational continuity, ICT governance, and third-party risk clarity. The public site should therefore show controlled claims: operational-readiness assets, evidence hashes, resilience workflows, and handover docs.

VaultAI buyer implication: do not claim certification. Show the controls and evidence a buyer can verify after NDA.

## Customer Segments

| Segment | Why They Care | VaultAI Entry Point | Proof Needed |
| --- | --- | --- | --- |
| Regional banks | Core modernization risk and cost | Shadow-ledger migration control plane | Ledger invariants, migration playbook, containerized deployment |
| VDR/M&A platforms | Differentiated AI diligence workflows | Data-room intelligence and cited extraction | UI demo, workflow docs, research mapping |
| Financial software vendors | Build-vs-buy roadmap acceleration | Source-code/IP package | Repository manifest, architecture evidence, onboarding docs |
| System integrators | Sovereign deployment and implementation services | Deployable enterprise stack | Terraform, Docker, API specs, DR playbook |
| Risk and compliance platforms | Regulatory evidence and operational resilience | Audit evidence and control dashboard | WORM audit log model, incident workflow, evidence API |

## Buyer Objections and Prepared Responses

| Objection | Conservative Response |
| --- | --- |
| "There is no ARR." | Correct. This is positioned as source-code/IP acquisition, not an ARR-multiple SaaS sale. Value rests on replacement-cost avoidance, speed-to-market, and strategic control. |
| "AI tools can rebuild software." | The review package emphasizes assembled implementation context, schema design, evidence manifests, documentation, deployment surfaces, and buyer-ready workflows, not isolated code snippets. |
| "Is this certified for banking use?" | No independent banking certification is represented. The evidence pack is designed to support diligence, testing, and buyer-side hardening. |
| "Can we review source?" | Yes, after NDA, buyer qualification, and controlled source-review protocol. |

## Research Backlog

1. Run 8 to 12 direct buyer discovery calls with banking architects, VDR product leaders, and system-integrator partners.
2. Collect buyer-ranked must-have controls: audit, deployment, support, security, migration, evidence, and commercial transfer.
3. Record anonymized objections and convert them into public FAQ updates.
4. Prepare a buyer-specific demo path for each segment.