PassThrough

1. One-liner

Reads your CAM true-up against your lease and drafts the dispute letter, for tenants too small for auditors.

2. Trend signal — why now?

Every US commercial tenant on a triple-net or modified-gross lease gets one document a year that decides whether they owe their landlord an extra four figures: the CAM reconciliation, or “true-up.” The landlord estimates common-area costs monthly, then 90–120 days after fiscal year end sends a statement comparing estimate to actual and bills or credits the difference.

Three things make this the right moment.

The bills got big. In a typical retail NNN lease, CAM runs $4–$10/SF annually — on a 5,000 SF inline space that’s $20,000–$50,000 a year sitting entirely outside the base-rent number the tenant actually negotiated (GrowthFactor, 2026). Two identical spaces in the same centre can differ by 40% or more purely on lease language. And the pass-through categories that have inflated hardest — property tax reassessment after a sale, and insurance premiums after catastrophe losses — are exactly the ones a triple-net tenant absorbs in full (TowerCorp).

The professionals openly refuse this segment. Contingency lease-audit firms typically require a minimum suspected overcharge of $10,000–$15,000 before they will take an engagement, and traditional firms “only make economic sense for tenants paying over $100,000 in annual CAM” (CAMAudit, 2026). A $5,000 recovery costs $1,650 in contingency fees and gets deprioritised. Boutique firms will go lower but charge $2,500–$5,000 upfront per property — more than the finding is worth. So the 5,000 SF tenant with a $30,000 CAM bill has audit rights written into their lease and no economically rational way to exercise them.

The work is now a document-reading problem, not an accounting problem. The whole job is: parse a 40-page lease for the exclusions, caps, gross-up and pro-rata clauses; parse a landlord GL extract and invoice package; and check one against the other line by line. Long-context document models do this competently now: the 2026 frontier models reason across text and documents in a single call at million-token context, and per-token prices have fallen sharply year over year (AI/ML API, 2026). The unit cost of reading a 40-page lease against a 200-row GL fell below the value of the finding.

The money is real and quantified: third-party lease auditors “frequently find 3–5% in annual overcharges,” and tenants typically recover 3–5% of annual occupancy costs (Rets AI, 2026). Nobody disputes the overcharges exist. They’re “common, self-reported, and rarely challenged.”

Provenance:

• Signal 1 (Demand): Small tenants face $20K–$50K annual CAM on 5,000 SF, with 40%+ variation between identical spaces from lease language alone; most simply pay the true-up — growthfactor.ai — 2026-08-26
• Signal 2 (Economic): Contingency audit firms require $10K–$15K minimum suspected overcharge and only pencil above $100K annual CAM; boutiques charge $2,500–$5,000 upfront — camaudit.io — 2026-08-26
• Signal 3 (Feasibility + Economic): Lease auditors routinely find 3–5% annual overcharges and tenants recover 3–5% of occupancy costs; the detection work is lease-vs-GL document comparison, now cheap given million-token context models and falling per-token prices — rets.ai, aimlapi.com — 2026-08-26 Category: Underserved niche

3. The opportunity

The incumbent isn’t a bad product. It’s no product — a deliberate, stated refusal to serve below a revenue line.

Lease audit is a mature professional service with real firms (Scribcor, CTS Audits, Chelepis, RE BackOffice) doing careful work. Their model is contingency or hourly, which means every engagement carries fixed human cost: read the lease, request the GL, chase the landlord, write the findings. That fixed cost sets a floor, and the floor is roughly $100,000 of annual CAM. Below it the arithmetic is hostile — as the industry itself puts it, “a $5,000 recovery costs $1,650 in contingency fees, and the firm may not prioritize small findings.”

The interesting part is that the software players have run away from the small tenant too. CAMAudit.io — the most visible AI entrant — explicitly positions as “the engine, not the auditor,” selling white-label capability to accounting firms, tenant reps, attorneys and lease administrators. They’re arming the professionals, not replacing them. The tenant with one location and no tenant rep still has nobody.

So the gap is precise: an annual, self-serve, fixed-fee product that turns the small tenant’s existing contractual audit right into a two-hour exercise instead of a $3,000 engagement. The tenant already has the leverage — every lease grants audit rights, and most leases make the landlord pay audit costs if the overcharge exceeds a 3–5% threshold. What they lack is the ability to find the 3% cheaply enough to be worth invoking it.

This is not a disruption play against the audit firms. It’s demand they’ve priced themselves out of and openly decline.

4. Target market

Primary customer: The owner or office manager of a single-location or 2–5-location business occupying 1,500–10,000 SF of retail, flex or small office on a triple-net or modified-gross lease in a multi-tenant property. Dental practices, physical therapy clinics, restaurants, salons, veterinary clinics, insurance agencies, specialty retail, small law firms. Annual CAM exposure $8,000–$60,000. They have no tenant rep on retainer, no lease administrator, and their bookkeeper treats the true-up as a bill to code, not a document to check.

Why they buy: Because in month four of the fiscal year an invoice appears for $3,400 they did not budget, labelled “2025 CAM reconciliation — balance due,” backed by a one-page summary with six line items and no invoices. They have a strong suspicion it’s wrong and absolutely no idea how to say so. The industry description of this moment is blunt: “many tenants simply pay the bill and move on, which can be a mistake” (Modern CRE). Meanwhile a desktop review by a broker or advisor is described as the sensible first step — but the small tenant has no broker to call.

Rough TAM reasoning: There is no clean public count of US small multi-tenant commercial tenancies, so I’ll reason from the constraint rather than assert a number. The addressable set is tenants below the ~$100K annual CAM line that audit firms won’t cross — which by construction is the large majority of multi-tenant occupancies, since $100K CAM at $6/SF implies ~16,000 SF. Every strip centre, medical office building, and flex park in the country is mostly composed of tenants under that threshold. Even a conservative read puts the reachable US population in the high hundreds of thousands. I don’t need a precise TAM: at $299/yr I need roughly 3,350 paying tenants for $1M ARR, which is a rounding error against the population and the real question is distribution, not market size.

Why now for them: CAM line items have inflated fastest in the uncontrollable categories — post-sale tax reassessment and insurance — so true-ups are landing bigger and more often than in the tenant’s memory of prior years. A bill that used to be a $600 annoyance is now a $3,400 event, which is the threshold where an owner starts asking whether they can push back.

5. Product sketch (MVP)

• Upload the lease (PDF or scan) and the landlord’s reconciliation statement; product extracts the clauses that govern the true-up — exclusions, expense caps, gross-up provisions, admin/management fee basis and percentage, pro-rata share definition, audit-rights clause and its deadline.
• Deadline clock. The single highest-value output on day one: reads the audit/dispute window out of the lease (commonly 90 days to 12 months from delivery) and tells the tenant the exact date their right to object expires. Miss it and the statement is deemed accepted.
• Line-item challenge sheet. Each charge on the statement is classified against the lease and flagged: likely capital expenditure billed as operating expense, admin fee applied to a grossed-up or uncontrollable base, gross-up applied to fixed rather than variable costs, charge in a category the lease excludes, pro-rata share inconsistent with stated leasable area. Every flag cites the lease clause by section number and quotes it.
• Document request letter. Auto-drafts the formal request for the supporting package the tenant is entitled to — full GL extract for the CAM pool, invoices above the lease-specified threshold, management-fee calculation worksheet, gross-up worksheet, recurring service contracts — addressed correctly and timed inside the window.
• Second-pass review. When the landlord returns the GL and invoices, upload them; the product reconciles the statement against the backup and re-scores each flag as substantiated, unsubstantiated, or contradicted.
• Dispute letter draft. Produces a professional, clause-cited objection letter with a dollar figure and a schedule of contested items — the artifact the tenant currently cannot produce and therefore never sends.
• Threshold check. Calculates whether the identified overcharge exceeds the lease’s cost-shifting threshold (typically 3–5%), which determines whether the landlord must pay for a formal audit — turning a finding into free escalation.
• Year-over-year comparison. Once a tenant has two statements in the system, flags categories that jumped disproportionately versus the prior year.

6. AI angle — what’s load-bearing

Remove the AI and this product is a checklist PDF, which already exists for free and which nobody uses.

The load-bearing work is reading two unstructured, non-standard documents and cross-referencing them. Commercial leases are bespoke: the exclusions list in a 1998 strip-centre lease and a 2023 lifestyle-centre lease share no structure, no section numbering, and no vocabulary. The landlord’s reconciliation statement is whatever the property manager’s software emitted — sometimes six summary lines, sometimes a 200-row GL dump with abbreviated vendor names. The task is to determine that “Parking Lot Resurfacing — $187,400” is plausibly a capital expenditure under this lease’s definition, that this lease caps controllable expenses at 5% non-cumulative, and that the admin fee was computed on a base that includes the utilities this lease classifies as uncontrollable.

That is document reasoning across two long, idiosyncratic sources with a legal definition in the middle. It’s the exact shape modern long-context models handle well and rule engines handle badly — which is why the professional version costs $3,000 of human time.

One deliberate constraint: the product does fixed math with citations, not estimation. Every flag must quote lease text and point at a statement line. A flag that can’t cite is suppressed rather than guessed. This matters because the output’s whole purpose is to be shown to a landlord — a hallucinated clause reference destroys the tenant’s credibility and the product’s.

7. Localization angle

N/A — this is a US play. CAM reconciliation, the true-up mechanic, gross-up conventions and tenant audit rights are artifacts of US commercial lease drafting. The UK analogue (service charges) has a different regime, its own professional norms under the RICS code, and is already addressed in this catalog. Expansion, if any, is US-first and deep — more property types, multi-location tenants — not geographic.

8. Business model — path to $1M–$5M ARR

• Pricing: $299/year per location, self-serve, covering one reconciliation cycle end-to-end (lease parse, challenge sheet, document request, second-pass review, dispute letter). Multi-location tenants pay $199/location above the first. A $599 tier adds a human review pass on the final letter before it goes out.
• Why this price: It has to be small relative to the finding and obviously smaller than the alternative. Against a typical 3–5% recovery on a $30,000 CAM bill (~$900–$1,500) it’s a clear trade. Against a boutique firm’s $2,500–$5,000 upfront it’s an order of magnitude cheaper. And it’s low enough to be an expense-code decision, not a procurement one.
• ACV: ~$340 blended, accounting for the multi-location mix and tier upgrades.
• Rough math to $1M ARR: ~2,950 paying locations at $340. At single-location dominance, call it 3,300 customers.
• Rough math to $5M ARR: ~14,700 locations. This is where the model has to change: it needs the multi-location tenant (a 12-clinic dental group is $2,400/yr at list) and it needs the channel partners — tenant-rep brokers and small-business CPAs bringing their book, which also raises retention. Pure single-location self-serve does not get to $5M.
• Expansion path: Second and third locations; the $599 reviewed tier; year-over-year comparison becomes more valuable each cycle (a three-year history is a genuinely better product than a one-year one); and eventually pre-lease review — running the draft lease before signing to flag the missing exclusions and absent expense cap, which is the highest-leverage moment and a natural upsell into the broker channel.

The honest structural problem: this is an annual, seasonal purchase. CAM statements arrive in a 90–120 day window after fiscal year end, mostly clustered Q1–Q2 for calendar-year landlords. Revenue is lumpy and the product is dormant for months. Two mitigations, both real: annual auto-renew subscription rather than transactional purchase, and the deadline clock as a year-round reason to stay subscribed. I’m not going to pretend this is smooth monthly SaaS — it isn’t, and it’s reflected in the revenue score.

9. Go-to-market wedge — first 100 customers

The seasonality is a distribution gift if you use it: you know when your customer feels the pain, to the month.

• Target the tenant list by property, not by tenant. County assessor and commercial listing data identify multi-tenant retail and flex properties. Tenants at a given property are visible from Google Maps, the centre’s own directory, and signage. Pick 200 strip centres and medical office buildings in three metros, enumerate their tenants, and you have ~2,000 named small businesses who all receive a CAM true-up from the same landlord in the same month. Time outreach to land 2–3 weeks after typical statement delivery. Message: “Your reconciliation for [Centre Name] should have arrived. Here are the three things landlords most often get wrong in it.”
• Ride the trade associations of the tenant, not the landlord. Dental, veterinary, PT, and restaurant owner groups — state dental associations, AVMA-adjacent practice-management forums, r/Dentistry and r/smallbusiness — are full of practice owners who lease space and discuss overhead openly. A single well-documented teardown post (“I got a $4,100 CAM bill; here’s what was wrong with it”) is native content in these communities and does not read as an ad.
• Free deadline checker as the top of funnel. Upload your lease, get one answer free: the exact date your right to dispute this year’s statement expires, plus which clause grants it. It’s cheap to deliver, genuinely useful, requires the lease upload (which is the hard part of activation), and creates urgency with a date. Convert to paid at the challenge sheet.
• Tenant-rep brokers as a referral channel. A broker’s small clients are exactly the ones the broker can’t profitably service post-signing. Handing them a $299 tool is a relationship-maintenance gift that costs the broker nothing. 20 brokers with 30 small clients each is 600 warm introductions, and the broker looks good.
• Content anchored on the specific document. “How to read your CAM reconciliation statement,” “Is your landlord’s admin fee charged on the right base,” “Capital expense vs repair: what your lease actually says.” This is a search-intent moment with a hard annual seasonality and low commercial competition, because the audit firms don’t market to this segment at all.

First 100: two metros, one true-up season, the free deadline checker as the hook, the association forums for credibility. That’s a 10-week sprint, not a 12-month brand-building exercise.

10. Build complexity — justification

Low. There’s no infrastructure here — no integrations, no real-time anything, no marketplace, minimal state. The entire product is document ingest, long-context extraction against a defined schema, a rules layer that applies the extracted lease terms to the extracted statement lines, and templated letter generation. All off-the-shelf.

The genuinely hard part is not engineering, it’s the lease-term taxonomy — building the extraction schema that reliably captures how the twenty-odd clause families that govern a true-up are expressed across wildly varying lease drafting. That’s iterative accuracy work on real documents, and it’s where the months go. Estimate 8–10 weeks to a v1 a friendly tenant can use, then a full true-up season of accuracy tuning.

11. Gating checklist

Gate	Pass?	Note
Legal in target market	✅	Helps a tenant exercise a right their own lease grants. Must be positioned as document analysis, not legal advice — no attorney-client relationship, letters are drafts the tenant sends in their own name.
Ethical — no harm / dark patterns	✅	Corrects an information asymmetry in favour of the smaller party. The output is cited and checkable; the landlord can rebut on the merits.
Market exists (evidence above)	✅	Mature professional services market with an explicitly stated lower bound that leaves this segment unserved.
1–5 person team can build this	✅	One strong builder plus a part-time lease-savvy advisor.
Launchable with <$50K / ₹40L	✅	Inference, hosting, and a modest paid-acquisition test. Well under $20K to first revenue.

12. Feasibility score

Axis	Weight	Score	Notes
Problem intensity	20	15/20	Real money, real deadline, real helplessness — but felt once a year. Not hair-on-fire daily pain, and the workaround (“just pay it”) is frictionless, which is precisely the problem. Docked for frequency, not severity.
Demand evidence	15	12/15	Strong and convergent: a professional services market with published price floors, industry-standard 3–5% recovery rates, and explicit vendor statements that small tenants aren’t worth serving. What’s missing is direct evidence that small tenants will pay rather than continue absorbing — nobody has tested this segment.
Build feasibility	15	13/15	Off-the-shelf throughout. Only real risk is extraction accuracy across heterogeneous lease drafting, which is tuning work, not invention.
Distribution clarity	15	11/15	The property-then-tenant enumeration is concrete and the timing is knowable to the month. Docked because cold outreach to small-business owners converts poorly, and the free-checker funnel is unproven.
Revenue mechanics	15	11/15	Pricing is well-benchmarked against a known alternative and the value math is favourable. Docked hard for the annual, seasonal, lumpy purchase shape and the genuine renewal question — a tenant who finds nothing in year one may not renew for year two.
Time to first revenue	10	8/10	Sellable the moment a true-up season is running; can pre-sell during build. Constrained by seasonality — launch outside the window and you wait.
Defensibility	10	4/10	Weak, and I won’t dress it up. The lease-term taxonomy and an accumulating corpus of landlord billing patterns by property and manager compound slowly, but a competent team could ship a credible clone in a quarter. This is an execution-and-distribution play with a modest head start, not a moat.
Total	100	74/100

13. Qualitative modifiers

Founder-fit tags

technical-heavy · content-heavy

Technical because extraction accuracy on messy leases is the entire product quality. Content because the distribution wedge is credibility in tenant communities and search-intent content at a seasonal moment. Notably not sales-heavy — at $299 self-serve there is no sales motion, which is the point.

Key assumptions to validate (3–5)

1. Assumption: Small tenants will pay $299 for a finding averaging $900–$1,500 that they must then personally deliver to their own landlord. How to test: Pre-sell. Take 40 tenants at real properties in an active true-up window, offer the full analysis at $299 before it’s built, and count cards — not interest.
2. Assumption: The extraction reliably finds real, citable discrepancies in ordinary small-tenant leases — not just the textbook cases. How to test: Collect 25 real lease + reconciliation pairs, run the analysis blind, and have a lease-audit professional grade every flag as valid, invalid, or missed. Requires ≥80% precision to be shippable, because a false flag sent to a landlord is worse than no product.
3. Assumption: Tenants will actually send the letter. The product’s value is zero if the output sits in a folder because the owner fears antagonising their landlord. How to test: Track send-rate in the first cohort. This is the assumption I’d most expect to be wrong.
4. Assumption: Landlords engage with a cited, professional dispute rather than stonewalling a small tenant. How to test: Follow the first 20 disputes to outcome — recovery, partial credit, or refusal — and measure realised dollars, not identified dollars.

Risk flags

1. Relationship risk (the big one): A small tenant depends on their landlord for renewal, and many will not risk the relationship over $1,200. This is not a product problem, it’s a behavioural one, and it could cap the market well below the addressable population. Partially mitigated by framing output as a routine “request for supporting documentation” — normal commercial hygiene — rather than an accusation.
2. Seasonality: Revenue concentrates in a Q1–Q2 window. Cash flow is lumpy, and a launch mistimed against the season costs a full year of learning.
3. Unauthorized practice of law: Drafting dispute letters that interpret contract terms sits near the line in some states. Must ship as analysis-and-draft with the tenant as author, clear disclaimers, and no representation. Worth a few thousand dollars of counsel before launch, not after.
4. Accuracy is existential, not merely important: A confidently wrong clause citation sent to a landlord embarrasses the customer directly. The suppress-if-uncited rule must be enforced hard, even at the cost of missed findings.
5. Fast-follow risk: CAMAudit.io has the capability today and has chosen the white-label professional channel. If the small-tenant segment proves out, their pivot down-market is short. The defence is owning the tenant relationship and the seasonal content position before they look.

14. Structured verdict

Score:                  74/100
Verdict:                GO
Confidence:             Medium
Best-fit builder:       Technical solo founder who can grind document-extraction
                        accuracy, paired with a part-time lease-audit or tenant-rep
                        advisor for the taxonomy and flag grading
Time to revenue:        6–10 weeks if launched into an active true-up season;
                        otherwise gated by the calendar
Capital to launch:      $15–20K (₹13–17L)
Top 3 assumptions to validate first:
  1. Willingness to pay — pre-sell 40 tenants at $299 in a live true-up window
     before writing extraction code; require cards, not nods
  2. Extraction precision — 25 real lease + statement pairs graded blind by a
     lease-audit professional; ≥80% precision on flags or the idea stalls
  3. Send-rate — do tenants actually deliver the letter? Track the first cohort
     to sent/not-sent, and to realised dollars recovered
Kill criteria:
  - Abandon if fewer than 8 of 40 pre-sell targets pay $299 in a live season
  - Abandon if flag precision stays below 80% after tuning on 25 real lease pairs
  - Abandon if fewer than 40% of customers who receive a challenge sheet actually
    send the dispute letter within their window
  - Abandon if realised recovery across the first 20 disputes averages under $400,
    making the $299 price indefensible

15. Next step — 1-week validation sprint

• Day 1–2: Acquire the raw material. Source 10 real small-tenant lease + CAM reconciliation pairs — via a tenant-rep broker contact, a small-business owner group, or paying owners $100 each for redacted documents. Without real documents this is all theory.
• Day 3–4: Run the analysis by hand with a long-context model and no product. Produce a challenge sheet for each. Then have a lease-audit professional grade every flag: valid, invalid, missed. This gives the precision number that gates everything.
• Day 5: Take the three strongest challenge sheets back to their owners and ask for $299 to have this done properly for their next statement — plus ask the harder question: would you actually send this letter to your landlord? Record the answer verbatim.

Falsifiable outcome: Go if blind flag precision is ≥80% AND at least 1 of the 3 owners pays AND at least 2 of 3 say unprompted they would send the letter. Any of those three failing means the idea is either inaccurate, unwanted, or blocked by landlord-relationship fear — and each failure points at a different fix, so the test is diagnostic, not just pass/fail.