Board and management reporting that saves your close.
Assemble reconciled KPI narratives, variance explanations, and board-ready first drafts with every figure linked to an approved source.
Nothing is finalized until a human approves it.
Where the time and money actually go.
Finance teams spend days collecting numbers, reconciling versions, writing repetitive commentary, and correcting figures copied into slides.
FP&A analysts, business-unit finance, executive leadership
Trigger to act: Reporting cycles are slow, leadership questions data lineage, acquisitions add business units, or a fractional-CFO firm wants a scalable deliverable.
The result you can model before you sign.
Illustrative only: 8 contributors × 12 hours removed per monthly reporting cycle × $65 loaded hourly cost = $6,240 monthly capacity. Decision quality is not reduced to time saved.
The outcome, plainly: Assemble reconciled KPI narratives, variance explanations, and board-ready first drafts with every figure linked to an approved source.
Inputs in. A cited, review-ready result out. Your expert decides.
An evidence-grounded reporting agent. Every material fact is grounded in an allowed source and returned with its identifier, with no invented data.
Claude Sonnet 4.6 or GPT-5.6 Terra for complex grounded work, selected by task-level evaluation; Gemini 2.5 Flash, GPT-5.4 mini, or Claude Haiku 4.5 for high-volume routing and drafting. PostgreSQL + pgvector or a managed vector store; policy rules and an evaluator service.
- Actuals
- Budget/forecast
- KPI definitions
- Prior deck
- Business-unit commentary
- Approved narrative rules
AI-Native, not autonomous. Judgment stays with your people.
The machine does the work; the human’s role narrows to the one thing that matters, judgment. That constraint is what makes it safe to deploy.
CFO/controller approves every figure and narrative; business owners validate explanations; the model cannot invent a driver or metric definition.
A scorecard, not a demo. We baseline what breaks in production.
Every deployment ships with an evaluation suite. These are the numbers we baseline before launch and monitor after.
The category is crowded. Most of it isn’t built for your workflow.
Fixed-scope, tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in from day one. A price you own, not a subscription you rent.
It plugs into the stack you already run.
No rip-and-replace. Access is scoped to the minimum data necessary, isolated per tenant, and fully logged.
Transparent by design. The build price buys the workflow and the proof.
A fixed implementation fee plus a monthly bill that scales with volume and governance. No hidden seats.
- ✓ One process / scope
- ✓ Live workflow on your data
- ✓ Baseline evaluation suite
- ✓ Measured vs. current process
- ✓ Full scope & integration
- ✓ Human-review UI & audit trail
- ✓ Write-back to your systems
- ✓ Production evals & monitoring
- ✓ Multi-facility rollout
- ✓ Advanced security & compliance
- ✓ Custom control & escalation
- ✓ Dedicated evaluation program
500 to 5,000 report runs per month plus source queries, model use and export storage.
Planning assumptions, not vendor quotations. Your ERP and other platform licenses are separate and owned by you. Figures confirmed during scoping.
“His vast knowledge of technologies and a natural problem-solving mindset consistently lead us through complex challenges with clarity and confidence.”
Questions serious buyers ask.
Does the AI act on its own?
No. CFO/controller approves every figure and narrative; business owners validate explanations; the model cannot invent a driver or metric definition. The system drafts and recommends; a human approves every consequential action. Explicitly excluded: no publication without CFO review; no unsourced figure or causality claim; no substitution for disclosure controls, investor-relations review, or board judgment.
How do you stop it inventing facts?
Every material claim is grounded in an allowed source record and returned with its source identifier. The system separates observed facts, model inference, and missing information, and routes to a human whenever confidence is low, evidence conflicts, or an adverse outcome is possible.
What does it cost to run each month?
A usage bill of roughly $400 to $3,600 per month (500 to 5,000 report runs per month plus source queries, model use and export storage), plus a $2,600 per month managed retainer for evaluation, monitoring and maintenance. Your existing platform licenses are separate and already yours. Exact figures are confirmed during scoping.
Do we need a ChatGPT or Claude subscription?
No consumer ChatGPT or Claude subscription is required for the production workflow. The client needs an approved API/cloud billing account. Workspace seats are optional for internal prototyping and administrator access.
How is this different from Workiva?
Tools like Workiva, Datarails, and Pigment are broad platforms you adapt to. This is a fixed-scope implementation tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in, and a transparent price instead of a seat subscription.
How long until it is live, and how do we prove it works?
We baseline the reporting cycle time first, then measure against that baseline. You see the scorecard before expanding scope: the evaluation suite ships with the system, not as an afterthought.
Bring your real numbers. Leave with a fixed-scope plan.
A 30-minute engineering-led working session, no slideware. You leave with a sized opportunity estimate, a fixed-scope pilot plan, and the integration & human-review path mapped.
VP of Growth at ViitorCloud · senior delivery owner confirmed before paid work