RFQ Processing Software: What It Should Do Before Pricing Starts

The first job is controlled intake. If RFQs arrive by email, the software should capture sender, subject, timestamp, attachments and deadlines without depending on a staff member to manually rename everything in Outlook. This is partly a productivity issue and partly a security issue. The ACSC highlights malicious attachments and links as a persistent threat, so intake cannot be treated as an informal desktop habit.

The second job is evidence preservation. Good software should keep the original package, not overwrite it. National Archives guidance treats file path, checksums and related metadata as part of validating digital records. If a dispute arises about what revision you priced, you want the untouched source package and an attributable log of what happened next.

The third job is file understanding. In a real fabrication RFQ, some files belong to the whole quote and some belong to line items or subassemblies. Software should distinguish between quote-level files such as the inquiry email, BOM, specification and bid sheet, and line-item files such as bracket DXFs, stair PDFs or gusset plate models.

The fourth job is revision control. The software should help users compare likely revisions and identify current versus superseded documents. Acrobat and Bluebeam show what the review layer looks like technically: compare reports, overlays, markups and tracked differences between versions. The business outcome is simple: do not let the estimator work from ambiguous drawing history.

The fifth job is CAD packaging and compatibility handling. For AutoCAD workflows, Autodesk ETRANSMIT can include dependent files such as xrefs and fonts; SOLIDWORKS and Inventor Pack and Go gather related referenced files. Good pre-pricing software should either understand packaged CAD sets or at least flag when references appear to be missing, unresolved or path-dependent.

The sixth job is permissions, resilience and governance. ACSC guidance makes a strong case for multi-factor authentication, least privilege and backups. A shop does not need defence-grade complexity to benefit from those principles. It does need software that can restrict access to sensitive packages and recover from human error or ransomware.

The useful evaluation question is not does it make quoting faster but what work does it remove before pricing starts. In fabrication environments, the high-value pre-pricing capabilities are controlled intake from email or upload portals, original file preservation and archive retention, archive handling for ZIPs and packaged CAD, file type recognition across PDFs, images, native CAD and neutral CAD, current-versus-superseded revision support, line-item creation and file-to-item assignment, quote-level versus part-level document separation, a practical viewer layer for common engineering files, unsupported-file flags and missing-reference flags, and an evidence trail with metadata and handoff record.

In practice, three workflow types compete here. Manual spreadsheets track jobs, due dates, owners and simple assumptions well, but depend entirely on people to organise files, compare revisions, map files to line items and preserve evidence — best for low RFQ volume with a disciplined team. Instant-quote tools price supported file types quickly for clean standardised parts, but handle mixed document packages poorly — best for simple parts and repeatable components. RFQ processing software structures mixed packages, preserves originals, builds line items, routes review, flags exceptions and supports handoff to pricing — best for mixed-package RFQs in fabrication shops and subcontractor teams with revision and file-volume pain.

Instant-quote tools are not a substitute for pre-pricing RFQ processing when the input is messy. SendCutSend expects 2D vector or STEP/STP files at 1:1 scale with generally one part per file — it does not accept STL meshes, raster files or photographs for instant pricing. Xometry differentiates between instant quoting and manual RFQ handling for complex packages. Protolabs centres supported 3D CAD uploads. If a builder sends a stair package with revised PDFs, photos, a BOM and a DWG with references, the problem is not the unit price — it is what exactly should be priced, from which revision, against which evidence.

If AI is involved in RFQ setup, the right question is not whether it is clever. The right question is whether its outputs are reviewable, attributable and safe to use. NIST's Generative AI Profile recommends empirically validated evaluation of capability claims, source and citation review during monitoring, documented retention of test and verification history, and additional human review where risks justify it.

In Australian privacy guidance, the OAIC recommends caution with AI products and that personal and sensitive information should not be entered into publicly available generative AI tools. For RFQ workflows, that means AI can be useful for draft classification, naming suggestions, line-item hints or missing-file prompts. It should not be an unreviewed authority on current revision, scope intent or commercial assumptions.

When a vendor says our AI reads the package for you, ask: can a human verify every extracted revision and file-to-item assignment? Does the system preserve the source files and show what evidence was used? Can it record corrections and build a review history? Can it operate within your privacy and security requirements? If the answers are vague, the AI layer is not mature enough for pre-pricing control.

A 42-line-item RFQ arrives for a stair, handrail and platework package tied to a mid-rise fit-out. The buyer emails a ZIP, two revised PDFs, a finishes schedule, an Excel BOM, two site photos and a note saying please price latest rev only; fabrication plus delivery; install separate. A spreadsheet-driven team can price that job, but only after someone manually names files, checks revisions, builds a parts register, asks clarifications and tracks superseded drawings. An instant-quote tool will help for any clean part files that fit its supported formats, but it will not solve the mixed-package coordination problem on its own.

RFQ processing software, by contrast, should create the quote record, preserve the original package, unpack the ZIP, separate quote-level files from part files, suggest line items, surface revision conflicts, flag missing references or unsupported files, and hand the estimator a clean current package plus an exceptions list. The workflow runs: RFQ arrives → capture original package and metadata → security scan → unzip and classify files → separate quote-level and line-item files → check revisions → flag missing or unresolved files → build assumptions and clarification list → assign owner and priority → handoff clean current package to estimator.

When comparing vendors, ask them to demonstrate the software on a real mixed RFQ package, not a polished demo part. Ask for one job with PDFs, one with missing revisions, one with native CAD references, one with a ZIP, and one with quote-level files plus line-item files. Then score it on these questions: can it preserve the original package? Can it detect or support revision review? Can it handle packaged CAD, not just standalone files? Can it keep a traceable record of user changes? Can it support permissions, MFA and backup expectations? Can AI-assisted outputs be reviewed and corrected safely? Can it hand off a clean current package to pricing without manual folder surgery?

If it cannot do those things, it is not really solving the before-pricing problem. The same principle applies whether you are evaluating a commercial product or deciding whether your current workflow has the right disciplines in place.

What is RFQ processing software actually for? It prepares messy RFQ packages for estimating by organising files, revisions, metadata and handoff before pricing begins.

Is RFQ processing software the same as instant quoting? No. Instant quoting prices supported files quickly. RFQ processing software deals with mixed packages, review and preparation before pricing.

Can a spreadsheet be enough? For low volume and disciplined teams, yes. But as file counts, revisions and stakeholders increase, spreadsheets leave much more work to manual process.

Should the software store the original inquiry email? Yes. Keeping the original package and metadata supports traceability, clarification history and dispute prevention.

Can AI fully automate pre-pricing review? It can assist, but NIST and OAIC guidance both support cautious use, human oversight, validation and privacy-aware controls.

What security controls matter most? Controlled intake, least privilege, MFA, backups and supplier-risk thinking matter more than flashy features.