We believe in radical transparency. Here is how our AI works, what it catches, what it misses, and what you can do to get the best results from every analysis.
Trueleveler uses a dual-model architecture — Claude and Gemini run independently on every document, then cross-validate results. This catches errors that any single model would miss and produces more reliable findings.
Your documents are parsed into structured data. Tables, line items, clauses, and terms are extracted and normalized for analysis regardless of source format.
Two AI models (Claude by Anthropic and Gemini by Google) analyze each document independently. Neither model sees the other's output during this stage.
Results are compared and reconciled. Where both models agree, confidence is highest. Where they disagree, the system flags the discrepancy for closer review.
Final results are presented with confidence indicators, source references, and clear explanations so you can quickly verify findings against the original documents.
Accuracy depends on document quality, format, and complexity. All engines deliver consistently high accuracy on well-formatted documents. Below is what each engine is designed to identify.
| Engine | What It Catches | Accuracy Factor |
|---|---|---|
| Bid Leveling | Line-item discrepancies, scope gaps, missing items, unit price outliers, math errors, and bid-to-bid inconsistencies across multiple proposals | Highest on structured bid tables with clear line items |
| Contract Review | Risky clauses, indemnification gaps, payment term issues, insurance requirements, change order provisions, and termination conditions | Best on standard contract formats (AIA, ConsensusDocs, NEC, JCT) |
| Submittal Extractor | Submittal requirements from specifications, section references, responsible parties, due dates, and approval workflows | Strongest on CSI-formatted specifications |
| Scope Check | Bid-to-spec misalignments, missing scope items, qualification conflicts, and exclusion gaps when comparing a bid against project requirements | Most effective with clear scope of work definitions |
| RFQ Generator | Generates comprehensive RFQs from project specs with appropriate scope, terms, and evaluation criteria for each trade package | Quality improves with detailed project specifications |
| Change Order Review | Pricing reasonableness, scope justification, markup compliance, schedule impact, and alignment with original contract terms | Best with itemized change order breakdowns |
| Pay App Review | Overbilling, schedule of values discrepancies, retainage errors, percent-complete mismatches, and stored materials issues | Most accurate with standard AIA G702/G703 formats |
| Document Compare | Clause changes, added/removed terms, modified pricing, scope alterations, and hidden revisions between document versions | Best comparing documents of the same type and format |
No AI system is perfect. Here are the areas where Trueleveler has known limitations and where human review remains essential.
Handwritten annotations, margin notes, and hand-drawn markups are not reliably extracted. If critical terms exist only in handwritten form, they may be missed.
Documents that are heavily skewed, extremely low resolution, or have significant portions obscured will produce incomplete results. Clean re-scans dramatically improve output.
Proprietary or non-standard contract formats, bespoke bid structures, and highly customized templates may reduce accuracy. Standard industry formats yield the best results.
The AI analyzes what is written in the document. Industry-specific verbal agreements, local customs, or context that exists outside the document cannot be considered.
While the AI understands general construction standards, it does not verify compliance with specific local building codes, municipal regulations, or jurisdiction-specific requirements.
Documents mixing multiple languages in the same page may reduce extraction quality. Single-language documents, particularly in English, produce the most reliable results.
You can significantly improve your results by understanding what factors affect AI analysis quality.
Native PDFs (digitally created) produce far better results than scanned documents. If you have the option, always upload the digital original rather than a scanned copy.
When scans are necessary, use 300+ DPI, ensure pages are straight, and avoid dark edges or fold marks. Color scans outperform black-and-white for documents with highlighted sections.
Industry-standard templates (AIA, ConsensusDocs, CSI-formatted specs, standard bid forms) produce the highest accuracy. The AI recognizes these patterns immediately.
English-language documents produce the strongest results. All major European languages are supported with consistently high accuracy, but English remains the benchmark.
Complete documents with all pages included yield better analysis than partial uploads. Missing pages, especially scope descriptions or pricing schedules, will create gaps in findings.
Clear, well-structured tables with consistent column headers and row formatting are parsed with high fidelity. Merged cells, nested tables, and irregular layouts can reduce extraction accuracy.
Trueleveler improves continuously through multiple feedback channels. Your usage helps make the platform more accurate for everyone — without ever storing or training on your documents.
Our engineering team continuously refines the prompts and instructions that guide each AI model, improving how they parse, interpret, and cross-validate construction documents.
When users report unexpected results, we add those document patterns to our internal test suite. This prevents regressions and ensures known edge cases are handled correctly.
As Claude and Gemini release improved model versions, we evaluate and integrate upgrades that improve construction document understanding while maintaining result consistency.
Every analysis includes feedback options. When you flag an inaccuracy or confirm a finding, that signal feeds into our quality pipeline to prioritize the most impactful improvements.
Trueleveler is an AI-powered analytical aid designed to augment — not replace — the expertise of construction professionals. All AI-generated findings should be verified against the original source documents before making project decisions. No AI system can guarantee 100% accuracy, and results should be treated as a highly capable first pass that accelerates your review process, not as a final determination. For contractual, legal, or financial decisions, always consult with qualified professionals.
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