Construction 12 weeks Melbourne, VIC

AI Estimating Software for a Commercial Electrical Contractor

Custom AI estimating software for a commercial electrical contractor. Costing rules engine, AI draft generation, estimator review interface, and SimPRO integration. Cut quote preparation time by 65%.

AI DevelopmentCustom Software DevelopmentSystem Integration
65% Faster estimate preparation
3x More quotes per week
95% Quote consistency across estimators
Architect analyzing building blueprints with tools representing AI estimating software for commercial electrical contractors
Perth Based. Australia Wide.
18+ Years in Custom Software
Fixed-Price Delivery
Full Code Ownership
Client Context

Commercial electrical contractor, estimating and operations teams

A commercial electrical contractor in Melbourne running 45 staff across commercial fit-outs, new building installations, and industrial projects. The business had grown steadily and was winning progressively larger contracts, which was stretching the estimating team beyond what manual quoting could comfortably handle.

The estimating function was three people: a senior estimator who handled the majority of complex quotes, a mid-level estimator, and a junior who supported both. All three priced jobs manually in Excel, drawing from experience and a loose set of labour rate cards and material pricing sheets that lived in a shared drive.

The Challenge

What needed to change

The estimating team was the bottleneck. Every quote started from scratch. The estimator opened a previous similar job in Excel, adapted the line items, checked the current labour and material rates, applied the margin, formatted the document, and sent it. For a mid-complexity commercial fit-out this took three to four hours. For a larger project, a full day. As enquiry volume grew, turnaround times were slipping.

Quote quality varied by estimator. The senior estimator's quotes reflected fifteen years of pricing knowledge. The junior and mid-level estimators produced good work but missed inclusions the senior would have added automatically — site access allowances on restricted-access buildings, council notification costs on street-fronting work, commissioning and testing line items on industrial switchboard installations. The result was that the same scope quoted by different team members could produce meaningfully different prices.

The senior estimator was approaching retirement. The management team knew that a significant portion of the business's pricing intelligence lived in one person's head. She was the reference point for unusual jobs, the person others asked when they were unsure. If she left, the remaining team would be working from a significantly thinner base of knowledge with no way to recover what had walked out the door.

Approved quotes did not flow into SimPRO. When a quote was won, a job had to be manually created in the job management system — re-entering scope, line items, and client details that were already sitting in the quote spreadsheet. This took another thirty to sixty minutes per won job and introduced data entry errors that caused problems in downstream job costing and invoicing.

The Solution

What we built

A custom <a href='/ai-solutions/ai-estimating-software'>AI estimating software</a> system built around the contractor's labour rate cards, materials pricing structure, and job-type-specific rules. Four components: a costing rules engine encoding the business's pricing logic, an AI draft generator that builds first-draft estimates from job scope inputs, an estimator review interface with full override capability, and a SimPRO integration that creates jobs automatically from approved quotes.

Costing Rules Engine

All labour rate bands, material pricing structures, overhead allocations, and margin rules encoded into a structured rules layer. Job-type-specific inclusions captured from the senior estimator through structured discovery sessions before she retired — switchboard access requirements for industrial jobs, council notification allowances for street-fronting work, commissioning allowances by installation type. The rules engine is the permanent record of the business's pricing intelligence.

AI Draft Estimate Generator

The AI layer takes job scope inputs — type, scale, site conditions, client type — and generates a first-draft estimate with recommended line items, quantities, and pricing applied. Uses <a href="/knowledge/how-ai-estimating-software-works">retrieval-augmented generation</a> to reference similar past jobs alongside the costing rules. Generates a reasoning summary so the estimator can see why each line item was included and which historical jobs it referenced.

Estimator Review Interface

A clean web interface where estimators review AI drafts, accept or modify any line item, add items the AI missed, and approve the final quote. All modifications are recorded for model improvement. One-click output to branded PDF for client delivery, or to the SimPRO integration for automatic job creation on won quotes.

SimPRO Integration

Approved quotes push to SimPRO automatically. Job scope, client details, line items, and cost codes all transfer without re-entry. Estimated costs appear in SimPRO for comparison against actual costs at job completion, enabling ongoing accuracy improvement. <a href="/ai-solutions/ai-automation-and-workflows">Workflow automation</a> triggers a notification to the operations team when a new job is created from an approved quote.

Built with:
PythonOpenAI GPT-4LangChainFastAPIReactPostgreSQLAWSSimPRO API
In Practice

How it works

1

Enquiry received

Enquiry arrives via email, phone, or web form. The estimating team logs the scope, job type, scale, and client details in the estimating system. For email enquiries with attached scope documents, the AI extracts key details automatically to pre-fill the scope fields.

2

AI generates draft

The AI references the costing rules engine and searches indexed historical quotes for similar past jobs. It generates a recommended estimate with line items, quantities, rates, and margins applied. The draft is available within seconds of the scope being entered, along with a reasoning summary citing the historical jobs it drew from.

3

Estimator reviews and adjusts

The estimator reviews each section of the AI draft. Accepts items that look correct, modifies items that need adjustment, adds items the AI missed, and annotates any complex judgment calls. The interface shows the AI's reasoning for each suggestion so the estimator can evaluate it rather than just accepting or rejecting a number.

4

Quote approved and sent

The estimator approves the final numbers. The system generates a branded PDF quote document. For clients who prefer email delivery, the quote goes out directly from the interface. For tender submissions, the appropriate format is selected from the output templates.

5

Won job flows to SimPRO

When the client accepts, one click pushes the approved quote to SimPRO as a new job. No re-entry. Scope, line items, client details, and cost codes all transfer. The operations team receives a notification and can begin scheduling immediately.

6

Actual costs feed back

At job completion, SimPRO actual costs are compared against the original estimate. Significant variances are flagged for review. Patterns in variances inform tuning of the costing rules engine, closing the accuracy improvement loop and making future estimates more precise.

Results

Measurable outcomes

65% Reduction in first-draft estimate preparation time
4 hrs → 90 min Average time from scope input to approved quote
3x Increase in quotes produced per week by the same team
95%+ Quote consistency across all three estimators on common job types
Zero Manual re-entry from approved quote to SimPRO job creation
100% Of senior estimator's pricing knowledge captured in the system before retirement

Our senior estimator was doing 80% of all the quoting. If she had left before we did this, we would have been in serious trouble. Now that knowledge is in the system. Any one of us can produce a consistent quote in the time it used to take to just open the spreadsheet. And we haven't had to re-enter a won job into SimPRO in months.

Operations Manager Commercial Electrical Contractor, Melbourne VIC
Delivery

How we delivered it

1

Phase 1: Discovery and Costing Model Mapping

3 weeks

Three structured two-hour sessions with the senior estimator and operations manager to document all costing rules, labour rate structures, material pricing logic, overhead allocations, and job-type-specific rules. Historical estimate data reviewed, cleaned, and indexed. SimPRO API access scoped and tested. Fixed-price quote delivered for phases 2 and 3 before any development began.

2

Phase 2: Costing Engine and AI Draft Generator

5 weeks

Built the costing rules engine and AI inference layer. Tested against 80 historical quotes to validate accuracy before the estimating team saw it. Iterated on job-type classification, line item suggestions, and reasoning summaries based on estimator feedback. Accuracy on common job types reached above 90% before phase completion. The senior estimator verified that her key pricing rules were correctly represented in the system.

3

Phase 3: Review Interface, Output Templates, and SimPRO Integration

4 weeks

Built the estimator review interface and PDF output templates including client proposal format and tender-ready format. Integrated with SimPRO for approved quote-to-job creation. Training sessions with all three estimators. Two weeks of monitored live use with support before full handover. The senior estimator retired at the end of this phase, with her full pricing knowledge captured and operational in the system.

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