Monaghan Legal — data room

1. Overview

Monaghan Legal is a fixed-fee commercial contract practice, started in 2026, acting across the common-law provinces for founders and small businesses that have no in-house counsel. A client sends a contract, gets a quote, and gets back a tracked redline and a one-page note within two business days. No retainer, no hourly billing, no trust money. An AI-native review stack does the first pass on every matter; a lawyer with twenty-five years on commercial contracts reads and signs every one.

The firm exists to prove one thing: that a small business can get a serious commercial lawyer's judgment on its paper at a price it will actually pay, fast enough that it doesn't go to a local generalist instead. The evidence so far says the demand is there and the delivery works. What the firm has not yet solved is acquiring clients at a cost and a rate that compound.

The market has moved underneath this in 2026. Crosby raised a $60M Series B in March as an AI-native law firm for commercial contracts. Athena raised a $2.5M pre-seed from a16z Speedrun on November 3, two months after launch. Falcon AI raised €1.5M on October 1 for same-day, flat-fee commercial legal work where the platform does the first review and a lawyer signs off. None of them is Canadian. Nobody owns Canadian SMB commercial contracts yet.

The ask, in one line: a 30-day acquisition sprint to produce a close-rate and CAC dataset, then a pre-seed of $1.5–2.5M to put two full-time lawyers on the funnel and fund twelve months of acquisition.

2. The numbers

Everything in this section is from the firm's inbox, Google Ads account and site analytics as of November 6, 2026. The raw exports are in Files.

Inbound, October 1 – November 6, 2026

Thirteen people contacted the firm about work in five weeks. Nine were work the firm does; four were out of scope or under the minimum fee. Two paid and were delivered, one is live, five are warm and unworked, one was lost to a local lawyer.

Two things in that table matter more than the totals. Every client who paid or nearly paid is a one- or two-person service business fixing its own client agreement. And the losses split cleanly: four were out of scope or under budget, one chose proximity. Nobody serviceable walked away over the price.

Close rate on serviceable leads: 2 of 9 closed, 1 live, 5 unworked. That 22% is a follow-up problem, not a demand problem; the five warm leads above have not been contacted since their last message.

Google Ads, August 31 – November 6, 2026

The spend ran in two windows: about $600 in early September, which produced two paid matters, and about $1,000 from mid-October, which produced eight inquiries and no closed matters so far. The difference was targeting, not demand.

One ad group produced three quarters of the contacts at $80 each. Broad match wasted most of the rest: visible search terms included "affordable will lawyers near me", "construction lawyer edmonton", "lawyer directory" and named competitor firms. "Business lawyer" is flagged by Google as rarely shown for low quality score, which means the ads and landing page do not match the keywords tightly enough and the account pays more per click than it should.

Site, October 7 – November 6, 2026

Funnel from that: 239 visitors → 27 reach the enquiry page (11%) → 13 emails (5%) → 2 paid (under 1%). Nine visits came from ChatGPT recommendations in 30 days, which understates it, since an AI recommendation usually ends as a direct visit or a branded search. The firm has not been asking leads how they found it; from now on it does.

What the firm currently costs to acquire a client

• Per contact: $137 blended; $80 in the ad group that works.
• Per serviceable inquiry: about $125 on the October spend.
• Per paid matter: $300 on the first $600; undefined on the second $1,000 so far; $825 blended across everything to date.
• Against fees of $600–1,300 a matter, the honest range on the current setup is $300–800. Fixed targeting (one ad group, phrase and exact match, a negative list from the junk already in the search terms) is expected to hold it at the $300 end without new spend.

Organic and AI channels produced four or five serviceable leads in the two weeks the ads were off, at no cost. The one Reddit post the firm has made produced twelve inquiries.

3. The market

AI-native law firms — technology companies that own the stack and serve clients through an affiliated firm where lawyers sign every piece of work — have been funded at every stage in 2026.

Two of those are the same business as Monaghan Legal with a different flag on it. Falcon is the model: fixed fee, same day, first pass by the platform, lawyer signs every review. Athena is the team shape: credentialed lawyers from top firms, a wedge in one practice area, funded on early client count. Crosby is the lane: commercial contracts, and it is American.

In Canada, Clio bought Jurisage to build a Canadian legal AI foundation, and pre-seed legal tech has been funded by Maple VC, Haystack and Inovia with law firms participating (Bench IQ). There is no AI-native Canadian firm in the list above. The Canadian market is smaller than the American one and has a different regulatory shape — non-lawyers cannot own a law firm, so the investable entity is the management company — but it is open.

4. Product and workflow

What happens to a matter

1. A client emails a contract or a description of what they need. The initial look is free.
2. The matter is opened in a private repository, one folder per matter, starting with the client's full email chain and attachments.
3. The stack reads the paper, classifies it, and produces a first-pass redline and a draft note on what matters and what needs a client decision.
4. A lawyer reviews each proposed edit with its reasoning, challenges what is wrong in plain words, sees the change, and signs.
5. The client gets a quote against the published fee schedule and an engagement letter; work is quoted before it starts.
6. The tracked redline and one-page note go back within two business days of the quote being accepted. Review-plus-negotiation matters are split-billed: the review on delivery, the balance when the matter ends.
7. The client's positions are recorded, so the next matter starts from what they have already decided.

What the stack is

A custom back end, built from scratch since late October 2026, with its own document editor rather than a Word add-in, on Canadian infrastructure. Model routing disqualifies any data-retaining model from any step that touches privileged client material. The firm runs on Claude and GPT subscriptions rather than metered API, which keeps marginal cost per matter close to zero at current volume. An earlier LangGraph pipeline with Postgres checkpointing was built and set aside; its lesson — that encoding a lawyer's judgment as executable playbook logic and evaluating it against real redlines works, but only once there are enough matters to learn from — is the basis of the current design.

The problem the design is built around

In any AI-native firm, the failure mode is the lawyer approving machine output without a real basis for the decision. Monaghan's design rule is that lawyer time per matter is short, the system owns rule and law changes, and the lawyer is reserved for the judgment the system cannot supply — business reality, what a counterparty will accept. The lawyer works in one place, sees every edit with its reasoning, can challenge it in his own words, and watches the change happen. The firm has no playbooks or house templates yet; they are built from matters and the lawyer's corrections, not assumed.

What gets built next

• Instant quote: a client uploads a contract and gets back, in minutes, a fixed price, the two clauses that will hurt them, and a sample of how the redline reads, before any human has looked. A lawyer still signs every matter. This is the conversion lever and the demo.
• Intake that runs without the principal lawyer: every inquiry answered within the hour, scoped the same day, stalls chased on day three.
• Playbooks from the first fifty matters: the firm's positions by document type and client type, versioned, with the lawyer's corrections as the training signal.
• A referral ask built into every delivery.

[Dec: add the screen recording of a matter going through, when ready.]

5. Operations

Fees (as published)

Fractional arrangements offered in outreach: about $8,000 a month fixed for two to three months, then about $4,000 a month against agreed volume; a startup package of about $5,000.

Scope

Customer agreements, MSAs and SOWs, NDAs, founder and shareholder agreements, employment contracts, terms of service and privacy policies, commercial leases. Excluded: securities, tax, litigation, M&A, financing, major construction, heavily regulated verticals. Acts in the common-law provinces; not Québec.

How the firm is run

• No trust money; nothing is billed for work not yet done. Invoiced on delivery.
• Every quote maps to the published fee schedule.
• One private repository for all matters, one folder per matter.
• Spellbook was tried and cancelled in October 2026; the in-house stack replaced it.
• No playbooks or house templates yet. They get built from matters.

[Dec: lifetime matter count and revenue since launch, and the engagement letter, to be added.]

6. Thinking

Why fixed fee

The small business buying a $600 review does not buy on hours; it buys on certainty. It wants to know what it will cost before it says yes, and it wants the work back before the counterparty loses patience. Hourly billing makes both impossible and is the reason this buyer has historically used a template or nothing. A fixed fee against a published schedule removes the first conversation entirely, which is the only way a firm with one lawyer can serve volume. It also forces the firm to make the work cheap to produce, which is what the stack is for.

Why AI-native, and why the technology is never sold

Software sold to lawyers makes lawyers faster at the thing they already do. A firm that owns its stack can change what the work is: first pass in minutes, lawyer time measured in minutes, marginal cost near zero, positions that accumulate per client. That only works if the firm controls the whole chain from intake to signature. Selling the stack to other firms would mean building for their workflows instead of ours and competing with Harvey and Legora on their ground. The stack exists to make Monaghan's legal services better and cheaper to deliver; the business sells legal services. That is also the structure every funded AI-native firm uses: a technology company whose only customer is its affiliated firm.

The wedge

The market is Canadian SMB commercial contracts. The beachhead the data supports is narrower: the one- or two-person service business — dietitian, bookkeeper, coach, consultant, doula — that needs its own client agreement fixed. That is who has paid, who has nearly paid, and who converts from a $600 ad click. They are plentiful, they are findable through search and through the accountants and bookkeepers who see their paper first, and they come back when they add a service line. The founder and startup paper that lawyers' networks produce is a second, higher-ticket lane that sits on top of the same stack; it is not the beachhead.

Acquisition

The firm's problem is not demand and it is not the price. Thirteen inquiries in five weeks arrived on $1,000 of badly targeted ads plus free channels, and the losses were out-of-scope or proximity, never the fee. The problem is that the funnel has been run as an inbox: leads email a lawyer and wait, and five warm leads have sat untouched for two weeks. The lever the firm controls completely is conversion — answer within the hour, quote the same day, chase on day three, and let a client upload a contract and see a price and a sample in minutes. Moving the close rate from 22% to 40–45% halves the cost per matter before a dollar of new ad spend. On top of that: Google on one tight ad group at around $100 a day, Reddit worked deliberately rather than once, reviews on a Google Business Profile that currently has none, referrals asked for in every delivery, and a "how did you find us" on every intake so the channels stop blurring together.

Portfolio counsel

The single biggest unlock available to the firm is a venture portfolio. An in-house counsel at a VC is the person every portfolio CEO calls about a customer agreement, an MSA or an employment contract. Twenty portfolio companies on a fixed monthly for startup paper is a different business from the one in section 2, at tickets of $1,300–3,000 rather than $600, with a trusted introduction already made. It is also the clearest pitch: the contract desk for a venture portfolio. Doing it properly means the conflict is agreed in writing with the fund first.

The 30-day sprint

Thirty days, about $5,000 in staged ad spend with a checkpoint at day ten, one tight ad group, the five stalled leads chased, reviews up, a referral ask to the firm's bookkeeper client, a $300 entry tier, every inquiry answered within the hour, a lawyer signing the matters the stack has already worked. Target: fifteen invoiced clients in the window; twelve is the floor that still carries a deck. Every inquiry logged from day one — source, minutes to first reply, quote, outcome, revenue — because the dataset is the deck. Days 30–60: the number goes to investors, with meetings booked in week one so the sprint ends into conversations rather than into a list.

The ask

$1.5–2.5M pre-seed into the management company. Use of funds: two full-time lawyers for twelve months, twelve months of acquisition at a known CAC, the instant-quote and intake product, and a buffer. Comparable rounds: Athena ($2.5M, a16z Speedrun, November 2026), Falcon (€1.5M, October 2026).

7. Team and structure

Robert (Bob) Monaghan — lawyer, principal

Twenty-five years on commercial contracts. Started at Fasken Martineau. General Counsel and Director of Strategic Development at KF Aerospace, one of BC's largest privately owned companies, 2001–2009. President and General Counsel of AVM Solutions, an international aviation contracting business. Government and military contracting, OEM and dealer agreements, twenty years in the helicopter industry. Licensed across the common-law provinces. Reads and signs every matter. His position on the firm is plain and should be read as such: he gives the licence, the name and the judgment, and will commit more time and money when the numbers warrant it, not before.

Dec Monaghan — founder, technology and operations

22. BA Economics, University of Victoria. Prior experience in wealth management. Built the firm's stack, runs its systems, intake and client delivery, and wrote the strategy and the analysis in this room. Bob is his father. Works full time on the firm without a salary.

Jerome Biroo — proposed co-founder

Princeton BA, Queen's JD. Corporate associate at Davies and at Paul, Weiss in Toronto. Legal counsel and operations, then Director of Revenue Optimization and Senior Director of Product Management and Legal Operations at TripArc / Navigatr. Associate General Counsel at Elevation Capital. Proposed role: own the raise and the investor relationships; own conversion and intake as a product; lead a premium tier for founder and portfolio-company paper; practise through the firm as Ontario counsel. [Jerome: your view on the role goes here.]

Structure

Non-lawyers cannot own a law firm in BC or Ontario, so the firm and the technology sit in two entities. Monaghan Legal, the law firm, is owned by its lawyers and sells legal services. The management company owns the stack, the brand, the intake and the acquisition engine, employs the non-lawyer team, and is paid by the firm under a management services agreement. Investors and non-lawyer founders hold equity in the management company. This is the standard structure behind every firm in section 3.

  Investors ──┐
  Dec ────────┼──► Management company ──(management services agreement)──► Monaghan Legal ──► clients
  Jerome ─────┘        owns: stack, brand, intake,                            owned by lawyers
                       acquisition, non-lawyer staff                         sells: legal services only
                       paid by: the firm

Proposed cap table (management company, pre-money)

A $2M round at an $8–10M post-money takes 20–25%; every line above dilutes accordingly.

8. Open questions

These are the things the people reading this room are asked to answer, in writing or on the first call.

1. Is the wedge sentence right — Canadian SMB commercial contracts, beachhead the solo service business fixing its own client paper — or would you put the first dollar somewhere else?
2. Is $1.5–2.5M the right ask for this market in December 2026, and which three investors would take a meeting on the sprint data?
3. What is the realistic volume of portfolio-company paper from a fund like Elevation, and what has to be agreed with the fund before any of it moves?
4. What role do you actually want, and what would you commit to in the first ninety days?
5. What equity number is right for that role? Write it in.
6. What in this room would you tear apart if it were a portfolio company's deck?

9. Files

Inbound log, Oct 1 – Nov 6, 2026 (CSV)
Google Ads summary by ad group (CSV)
[Dec: drop in the Google Ads full export, the two invoices (redacted), the Framer analytics screenshots, and the matter recording.]