The intelligence layer
An LLM is a component. The workflow is the product.
The fair question every technical visitor asks: isn't this just a language model reading PDFs? A language model is in there — doing what it's good at. The product is everything wrapped around it: structure, relationships, checks, domain rules, and a human who signs off.
The difference, side by side
Ask a PDF
PDFspecification.pdf · 84 pages
> Summarize this specification.
“This specification covers doors, frames, and hardware requirements for the project, including materials, finishes, and installation guidelines…”
One document in, one paragraph out. Fluent — and blind to every other document in the package.
Interrogate a project
Door 214
rating 90 min · size 3070 · hdw Set 12
08 71 00 — electrified, fail-secure
power supply owner: unresolved
Five sources, one entity, a verdict, and a drafted question — because the system knows these documents describe the same thing.
How a package moves through FastBid24
01
Ingest
Read the bid package as issued — drawings, specs, schedules, addenda. Scans included.
02
Identify
Recognize the things that matter: openings, hardware sets, requirements, revisions.
03
Structure
Turn what was read into data that behaves like data.
04
Connect
Link every entity across every document that mentions it.
05
Reason & validate
Check whether the documents agree — and refuse to guess when they don't.
06
Human review
An estimator reviews every quantity and every flag before delivery. Always.
07
Act
Deliver work you can use: the estimate workbook, QA notes, drafted RFIs.
Every stage above runs in the live Doors & Hardware pipeline today. The same architecture extends trade by trade — that's the product roadmap.
Judge the architecture by its output.
Send a package. The deliverable — flags, QA notes, drafted RFIs — is the argument.