How do I build a business case for enterprise AI?
Frame it as infrastructure, not productivity. Productivity gains are fuzzy; infrastructure savings are concrete — fewer tickets, faster onboarding, reduced legal review time, less context-loss during handovers. bRRAIn's pricing is designed to match a real-world infra line-item.
Stop pitching productivity, start pitching infrastructure
Productivity pitches for AI fail because "10% faster" is impossible to audit and easy to discount. Infrastructure pitches work because the line items — tickets, onboarding days, legal review hours — are already on the books. Reframe the ask: bRRAIn is not a productivity tool, it is institutional memory infrastructure. The ROI calculator walks a finance team through exactly this reframe, turning soft gains into hard line items. A CFO who rejected "AI productivity" will sign off on "infrastructure debt reduction" when the math is explicit.
Ticket volume as the first hard number
The cleanest metric is internal support ticket volume. Engineering teams field hundreds of "what's our deploy process" and "where is the runbook" tickets a month. Route those through a memory-aware AI backed by the Consolidated Master Context and volume drops 40-70%. Multiply deflected tickets by the loaded cost of the responding engineer and you have a monthly savings figure that finance recognizes. The ROI calculator has presets for this scenario. One deflected ticket a day at a $150k salary covers the seat cost.
Onboarding days as the second hard number
New-hire time-to-productivity is a line item most CFOs already track. The industry average is 90 days for a senior engineer. With bRRAIn's Consolidated Master Context and the Document Portal, that window compresses to 30-45 days because the new hire can self-serve every policy, runbook, and owner question. Three weeks of accelerated ramp at a loaded $300k is roughly $17k per hire. A company hiring 50 engineers a year has $850k in annual onboarding savings, which is substantially larger than a full Managed Install.
Legal review hours as the third hard number
Legal review is expensive and usually bottlenecked. bRRAIn's Vault stores every contract, redlined version, and precedent decision in a retrievable graph. Instead of paralegals re-reading the same NDA language for the hundredth time, the Handler retrieves the canonical clause and flags only novel deviations. Customers report 30-50% reduction in review hours. At $400 an hour across an in-house legal team, the infrastructure case for AI writes itself. Legal, not engineering, is often the fastest line-item win.
Match the pricing to the line item
The final step is matching the ask to how the CFO buys infrastructure. bRRAIn's pricing is intentionally designed as an infrastructure line-item: Self-Service for small teams, Managed Install for single-tenant enterprise, and OEM license for embedding into your own product. Each tier is a predictable annual commitment, not a per-query meter. Predictability is what lets the business case survive a budget review. Hand the CFO three numbers, a known annual cost, and a demo — and the approval path is straightforward.
Relevant bRRAIn products and services
- ROI calculator — turns tickets, onboarding days, and legal hours into a hard savings number.
- Pricing page — predictable annual pricing that fits the infrastructure line-item framing.
- Consolidated Master Context — the memory layer that deflects internal support tickets.
- Document Portal — self-serve surface that compresses new-hire ramp by half.
- bRRAIn Vault — contract and precedent store that cuts legal review hours by 30-50%.
- Book a demo — walk a CFO through the infrastructure pitch in 30 minutes.