BC RIA 2027 Suite
One public path: understand the regime, assess readiness, draft a position.
Sources reviewed May 26, 2026
Regulatory Workbench
Build a position letter on BC RIA 2027.
Build the letter manually in the browser, use local field hints while you work, or use authenticated AI assist for PDF extraction and a tightened draft. You decide who receives it, you sign and send it yourself, and counsel should review it before it leaves the store. Mechanus IQ does not transmit submissions or aggregate signed letters.
01
Store details
02
Operating numbers
03
Argument set
04
Counsel review
05
Print to PDF
06
Dealer sends
Evidence Ledger
Seven gates from intake to counsel packet.
Facts
0/0
Arguments
2/6
Packet
11%
Source intake
Lift facts first. Draft second.
Manual typing and field hints stay in the browser. Upload and AI generation use authenticated backend calls. Extracted values land in a confirmation queue before they can influence the letter.
Manual lane: Typed values feed the deterministic letter immediately.
Evidence lane: Extracted facts require accept, edit, or reject.
Final lane: Counsel packet shows remaining gaps before export.
Workspace upload · Optional
Signed-in workspaces can upload a contract, F&I menu, spreadsheet, CSV, or image to lift dollar amounts and product names into the form below. Public visitors can use manual entry or the sample packet.
PDF · CSV · XLSX · DOCX · JPG · PNG
Preview without workspace auth
Load a fictional local sample packet to exercise the confirmation queue, argument matrix, and counsel packet. It never calls the backend.
Fact confirmation queue
Nothing extracted becomes evidence until you accept it.
Pending
0
Confirmed
0
Rejected
0
01 / Store packet
Identify the sender.
Confirmed facts and manual edits both feed the header, signature, and operating context. Every extracted value stays traceable back to its source.
02 / Operating numbers
Add the numbers that make it real.
The argument matrix below marks weak claims before they reach the draft. Missing numbers remain visible instead of being hidden inside a polished letter.
03 / Argument matrix
Select the claims the store can support.
Each selected argument shows its evidence lane, missing fields, and legal rewrite lock. AI can tune voice, but it should not invent authority or numbers.
04 / Draft studio
Compare the manual draft against the AI draft.
AI can tighten voice and structure from confirmed facts. It should not add new facts, dates, citations, recipient names, or legal claims.
Locked clauses
- Regulatory dates and authority framing
- Dealer signs and sends the letter
- Mechanus IQ does not transmit submissions
- Counsel review and no-legal-advice language
05 / Counsel packet
Export only after the weak spots are visible.
This panel does not block the dealer, but it shows what counsel still needs to review: pending facts, missing fields, weak arguments, and AI gap flags.
Confirmed facts
0
Pending facts
0
Ready arguments
2/6
Open review items
15
Field gaps
- Letter date
- Store name
- Dealer principal name
- F&I director name
- Store type
- Postal code
- F&I products on menu
- F&I sellers requiring training
- Annual F&I revenue estimate
- Unknown provider transitions
- Average chargeback rate
Evidence gaps
No pending facts or AI gap flags.
Argument gaps
- Final-rule-status argument: Store name, F&I products on menu, Annual F&I revenue estimate
- Training-availability argument: Store name, F&I sellers requiring training
- DR and E&O clarity argument: Store name, Dealer principal name, F&I director name
- Gross-vs-net compensation argument: Store name, Average chargeback rate
Letter preview
ManualBefore you draft
Build the four numbers first.
The strongest submissions use dealer-specific operating economics. Read the Readiness Center for the measurement framework, then come back here when you have your product-level numbers in hand.