AI Business Intelligence Development

A restoration company kept its numbers in Excel files that never matched. We built the ROI Engine for WorkWonders, a decision engine that puts profitability and receivables on one screen. Our AI business intelligence development took a working platform from brief to delivery in 20 hours.

The ROI Engine turns a restoration company’s operational and financial records into one clear view of profitability, receivables and job performance. WebOsmotic designed and built it for WorkWonders in the United States.
Job-level cost and revenue now form one picture. It shows where the business makes money and where it loses it. Owners and operations leads use it to decide which work to take on and which invoices to chase. Managers ask questions in plain English and get answers from the same business records. The architecture, the data pipeline, the analytics and the AI layer are all ours, taken from requirements through to delivery.

Industry

Real Estate

Country

United States

Service

Backend Development

Business Intelligence

Technology

Goals, Final Analysis & Consultation Summary

Every answer started with a file: operational and financial data lived across Excel files that did not match. Finding low-margin work, checking overdue invoices or comparing project managers meant opening several files and working through the numbers by hand. An answer took longer to produce than the decision it fed.
Margin hidden in messy files: cost and revenue for each job sat in files with mismatched column names and missing fields.
Numbers managers could trust: incomplete or inconsistent records could skew the results without anyone noticing.
Answers that lead to action: business logic had to sit above the analytics and pick out what mattered most.
Room for what comes next: adding forecasting and alerts later would mean rebuilding the data layer underneath unless the platform planned for it.

Between a business’s data and the person deciding what to do next sits a chain of steps. Ingestion and cleaning come first, then analysis and ranking, then AI questioning. This project shows that layer built end to end for a restoration company in the United States. Excel goes in. Ranked margin issues come out. Our team built it the same way we built the Rapid Scope Pro estimating platform for WorkWonders, so one engineering group knows both products. Restoration and field-service businesses can use it as a reference for AI business intelligence development on messy source data.

What does AI business intelligence development cost?

A first release with flexible file ingestion, data cleaning, a job-level data model, ranked issues and a plain-English question layer typically costs between $40,000 and $110,000. The figure rises with the number of source file formats and the depth of the AI question layer.

How long does it take to build an AI business intelligence platform?

A first production release usually takes 4 to 8 weeks. The ROI Engine reached a working platform 20 hours after the brief, and the real calendar depends on how many data sources and approval rounds follow.

Can a business intelligence platform work from Excel files?

Yes. The ROI Engine takes CSV and XLSX uploads, maps their columns itself and accepts manual corrections. Records are checked and repaired as they arrive, so one normalized record sits behind every job. A new source joins without code.

Can managers ask the platform questions in plain English?

Yes. A question layer sits above the analytics and answers from the same business records. A manager who never opens a report can still ask which jobs lose margin and receive a ranked answer.

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Get a free consultation for your AI business intelligence development project, from data ingestion and cleaning to ranked issues and plain-English answers. WebOsmotic is an ISO 27001:2022 certified AI engineering company with custom AI analytics and backend development experience for restoration and field-service businesses in the United States and worldwide.

AI Business Intelligence Development for Restoration Companies in the United States

From Excel Files to Ranked Margin Issues and Plain-English Answers in 2 to 3 Minutes: Case Study