Quoting large packages with several estimators, revisions and controlled files
If you quote big multi-part packages with several people involved, VenturusEQ keeps one record across all of them. Revisions carry forward, findings are routed through a review queue, controlled data is fenced with a hash-chained ledger, and quote-vs-actual shows where the estimate drifted from the floor.
How a large package gets quoted today
A contract manufacturer's RFQ is a folder, not a file. Sixty drawings, an assembly model, a specification, a parts list and a customer portal deadline. Three estimators split it, engineering is asked about a tolerance, quality is asked about an inspection note, and purchasing is asked for a price on a casting.
Some of the files carry export-controlled data that must not leave the building. Revision C arrives while B is half priced. A week later the customer asks which revision the price was for, and the answer is in four spreadsheets and an email thread.
What is missing is one record across the people, the revisions and the data classes, one that can say who saw what, when.
What VenturusEQ keeps in one record for a contract manufacturer
Packages as large as the ones you receive
384 MB per file, 700 MB per request, 27 file types. ZIPs unpack with lineage, an Excel parts list becomes rows, and a STEP assembly is read into a tree of up to 25 levels and 2,000 nodes.
Revisions that carry forward
Values, terms, breaks, add-ons, expedites, welds and review findings carry into the next revision. Submitting freezes a baseline and supersedes the earlier one, so the record shows what was quoted against what.
A review queue with routing
Findings go to estimating, engineering, quality or purchasing. Claim, release, set a due day, route on, or waive with a second pair of eyes. Bulk actions clear a long list.
Controlled data fenced from cloud storage
Classes per file that ratchet up only. Controlled bytes never reach cloud storage. Every controlled open is ledgered before it is served; the ledger verifies and exports. Downloads are watermarked. Access review and a US-person attestation are built in.
Quote levels and one editor per line
Group lines into levels with their own status and submission history. Each line has one editor at a time, with a visible take-over and a timeout your company sets. Bulk edits change status, estimator, level, material, template and quantities at once.
Quote-vs-actual
The awarded snapshot beside live actuals, per bucket. A portfolio view shows which templates drift. Advisory by design: nothing writes back to your rates without a person.
How a large package becomes a frozen baseline
The folder becomes a package
Every file hashed, given a role and a class. Controlled files are routed to a storage tier that never touches cloud blob. The package brief says what is covered and what is missing.
Lines are created and assigned
Drawings, models, parts-list rows and assembly children become lines with quantities. Lines are assigned per estimator with an assignment email, and a facility is set on the header.
Reads and measurements are queued
Twenty-five files per enqueue, retries, leases and cancel. Controlled files are refused at the AI boundary where that switch is on. Proposals wait for a confirm.
Findings route to the right desk
Tight tolerances, heat treat, finish and inspection needs raise findings with your thresholds. Engineering and quality answer in the queue, not in an email thread.
Revision C arrives
A new revision carries values, terms, breaks, add-ons, expedites, welds and findings forward. Routing and the bill are copied after commit, and the price is rebuilt from the same sources.
Submitting freezes the baseline
The snapshot locks, expiry is set from validity, company terms are frozen on the revision, and the digital quote or a watermarked PDF goes to the buyer by the route the data class allows.
Common questions
The customer sends revision C while we are pricing revision B. What happens?
You create the new revision and it carries forward the values, terms, breaks, add-ons, expedites, welds and review findings; the routing and the bill are copied across once it is committed. When the new revision is submitted, the earlier one is superseded, so the record shows which revision each price was for.
How do we handle export-controlled files?
Each file and package carries a controlled-data class that only ratchets up. Controlled files never reach cloud storage, every controlled open is written to a hash-chained ledger before the bytes are served, downloads are watermarked with person, time and hash, and a controlled quote never gets a public link.
Can engineering and quality sign off on a finding before we price?
Yes. Findings are routed to estimating, engineering, quality or purchasing, with claim, release, a due day and bulk actions. Waiving a finding needs a second person. A finding can also act on its own by adding an operation or refusing the line.
Can we compare what we quoted with what the job actually cost?
Yes. Quote-vs-actual compares the awarded snapshot with live actuals per bucket, and the portfolio view points at the templates that drift. It is advisory; nothing writes back into your rates.
How do people sign in, and what does the audit log keep?
Password plus two-factor with an authenticator app and recovery codes, requirable per role, and sessions are revalidated on every request. The audit log keeps before-and-after values, never passwords or file bytes.
See one of your own large packages become one record
Bring a real package, controlled files included. We walk it through intake, routing, the ledger and the frozen baseline, in the shape your own instance would run, live. If you would rather look first, the interactive demo is open, with no form in front of it.