Build the Business Case for Docsie
Estimate workload, AI-credit capacity, potential time savings, rollout requirements, and enterprise deployment fit before you enter procurement.
- Estimate AI-credit usage from your actual monthly volumes, not vendor averages.
- Model hours returned and economic value with a realization factor your finance team will accept.
- Hand security and procurement a structured package instead of a slide deck.
- Leave with a pilot plan that has owners, baselines, and pass/fail criteria.
Designed for documentation, learning, enablement, operations, and enterprise teams evaluating AI-powered knowledge workflows.
Run your numbers before anyone asks for a budget.
The calculator turns operating figures you already know into hours returned, capacity value, plan fit, and headroom. Try the simplified preview below. The full workbook adds AI-credit demand, plan recommendation, utilization, and payback.
Your workload
Modeled annual result
- Modeled annual capacity value
- $97,500Gross value × realization. Planning estimate before software and implementation cost.
- Current annual effort
- 4,800 h
- Estimated Docsie effort
- 900 h
- Annual capacity returned
- 3,900 h
- Gross annual capacity value
- $195,000
Illustrative. The pilot replaces these assumptions with observed effort, acceptance rate, rework, and AI-credit use.
Eight documents, one internal approval path.
Each piece answers a question a specific stakeholder will ask: the sponsor, finance, security, IT, and the team that has to run the pilot.
ROI and Capacity Calculator
Enter volumes, source sizes, current effort, selected plan, and operating reserve. Get hours returned, gross and realized capacity value, recommended plan, utilization, headroom, workload coverage, net value, and payback.
Google Sheets workbookExecutive Decision Brief
What Docsie does, how it creates value, the questions the package helps you decide, and the recommended next step. Two pages a sponsor will read.
Business Case and ROI Guide
How the value model works, which assumptions to defend, how to state realization and payback, and how to move from calculator estimates to pilot evidence.
Plan and Capacity Guide
How plan sizing works: included monthly AI credits, base demand plus reserve, recommended versus selected plan, utilization, headroom, and workload coverage.
Workflow and Technical Capability Guide
Video-to-docs, content import, Learn, Compare, forms, localization, publishing, and integrations, with the acceptance criteria to test in a pilot.
Security and AI Governance overview
Plain-language answers on AI data handling, access, retention, provider choice, change control, and audit, plus the configuration options an enterprise can require.
Pilot Evaluation Template
A fillable template for scope, baseline, owners, required controls, acceptance criteria, and a Pass / Partial / Fail / Follow-up result per workflow.
Enterprise Deployment Reference Patterns
Reference architectures for SaaS, private cloud, on-premises, and offline reader delivery, with the identity, network, and inference-boundary decisions each one implies.
Not a whitepaper. A working package for the people who have to say yes.
Every document is meant to be edited, filled in, and forwarded.
Estimate AI-credit usage from real workload
Size demand from your monthly volumes, source sizes, and workflow mix instead of guessing at a plan tier.
Compare plan capacity and headroom
See utilization, shortfall, and operating room for the plan you selected against the plan the model recommends.
Model hours returned and economic value
Gross capacity value, a realization factor, net value, and payback, stated the way finance expects to see them.
Build a pilot with measurable success criteria
Hours returned, turnaround, acceptance rate, rework, adoption, and governance evidence, each with an owner and a target.
Give security and procurement a structured package
Executive answers on AI governance, the controls to validate, and the evidence library your reviewers will ask for.
Understand every deployment option
SaaS, private cloud, on-premises, and offline reader delivery, with what each one means for identity, network, and inference boundary.
Choose the deployment pattern before you load content.
The reference patterns cover four models. Availability and production design for a specific environment are confirmed through solution review.
Docsie SaaS
Fastest path to a pilot. Docsie-configured inference provider, SSO/SAML, and tenant isolation.
Customer private cloud
Docsie runs in a customer-owned cloud account with a compatible customer-approved or customer-controlled inference boundary.
On-premises / local Kubernetes
Self-hosted deployment inside your network for data-residency, air-gap, or regulated environments.
Authoring plus offline reader
Central authoring with offline reader delivery for field, plant, or disconnected sites.
See also the self-hosted deployment overview and the security overview.
A pilot that ends in a decision, not a second pilot.
The Pilot Evaluation Template follows the sequence below. Each workflow ends with Pass, Partial, Fail, or Follow-up required, with evidence attached.
Baseline
Record current effort, turnaround, rework, acceptance quality, and software cost for two or three representative workflows.
Configure
Confirm deployment, identity, AI provider, data, and retention requirements. Set roles, templates, and allowed integrations.
Run and measure
Process representative content. Track review time, corrections, acceptance rate, adoption, control evidence, and AI-credit use.
Decide
Replace calculator estimates with observed results and the current commercial proposal. Proceed, adjust scope, close gaps, or stop.
Permissions control access. Not model output.
The Security and AI Governance overview gives your reviewers plain-language answers and the configuration choices an enterprise can require.
- Retrieval, generation, and actions are designed to stay within authorized tenant and workspace content.
- Select the inference boundary: Docsie-configured provider, compatible customer-approved provider, or customer-controlled infrastructure.
- Keep AI features disabled until provider, data-flow, permission, retention, and enablement requirements are approved.
- Define retention, deletion, logging, network, and support-access requirements in the solution and contract package.
Docsie Trust Center
Security documentation, policies, and compliance evidence for your review.
Before you request the kit
What happens after I submit the form?
You receive an email from hello@docsie.io with access to the kit, usually within a few minutes. Start with the ROI and Capacity Calculator, then use the guides to complete the case. A Docsie enterprise specialist may follow up to offer an evaluation call.
Is the kit free?
Yes. There is no cost, no credit card, and no sales call required to receive it.
Who is it for?
Documentation, learning, enablement, operations, and enterprise teams evaluating AI-powered knowledge workflows, and the finance, security, IT, and procurement stakeholders who have to approve them.
Can I share it with security and procurement?
Yes. The Security and AI Governance overview and the Enterprise Deployment Reference Patterns are written for reviewers. Customer-specific commitments come from the signed order form, DPA, SOW, and deployment plan.
Are the calculator figures a quote?
No. The calculator is a planning model. Plan capacity reflects the current catalog and commercial terms are confirmed with Docsie. The pilot replaces model assumptions with observed results.
Ready to build the case?
Get the calculator, the brief, the guides, and the pilot template in one package.
Get the Enterprise Business Case Kit