Investor Deck
Investor Deck: Pre-Seed 2026
Pre-Seed · March 2026 · Confidential
Lease compliance and NOI enforcement for commercial real estate portfolios.
trevor@firststreet.ai · www.firststreet.ai
The Problem
CRE firms are managing millions in NOI through unstructured lease documents and manual interpretation, with no reliable way to ensure income accuracy or compliance. Firms rely on legacy systems to store lease data, but the actual lease logic still lives in PDFs, abstracts, and spreadsheets.
The Structural Risk
Property management systems depend on human configuration to translate lease language into billing logic — creating structural risk at every step.
The Result
Revenue leakage is rarely visible in real time — errors accumulate across the portfolio undetected.
Manual review cannot keep pace with a growing portfolio. Execution gaps compound across lease terms.
Issues surface months or years later through tenant audits or disputes.
After that, underbilled revenue is unrecoverable. Most operators find out too late.
The Opportunity
Impact grounded in industry data: CRE portfolios over 500K SF lose $0.50–$1.50/SF annually in unrecovered operating expenses from billing errors and conservative estimates (Springbord, 2024). On a 50M SF portfolio that represents $25M–$75M in addressable annual leakage. Firststreet's $12.5M 3-year NOI uplift reflects a conservative 20–25% capture rate, net of implementation and integration costs. Asset value assumes 6.25% cap rate.
The Gap
Lease clauses governing escalations, recoveries, and caps are interpreted manually, creating underbilling, overbilling, and inconsistent execution across properties. The root cause: lease clause logic (escalation schedules, recovery caps, gross-up provisions) exists only in PDFs. No system enforces it.
Without proactive governance, errors surface only when tenants audit, leaving landlords absorbing write-downs, credits, and legal costs with no early warning system. Defense costs average $25K+ per dispute regardless of outcome.
Lease data may live in PMS, but clause logic is not governed centrally, leaving no portfolio-wide visibility into execution accuracy. The result: no CFO can answer "are we billing correctly across our portfolio?" without a manual audit.
Execution depends on spreadsheets and institutional knowledge, making reconciliations slow and non-repeatable. A single analyst can accurately manage ~150–200 leases manually. Beyond that, error rates compound, and CAM reconciliation seasons stretch 6–8 weeks, delaying collections and straining tenant relationships.
The Solution
Firststreet isn't another point solution.
It's the operating system that enables CRE firms to maximize the value of their portfolios.
CRE operators need to protect NOI today with institutional-grade lease governance.
Product
Start with the fundamentals: understand what your leases require in real time and where exposure exists.
Upload lease documents and addendums (PDFs, docs, sheets). Firststreet abstracts key financial and recovery terms for review.
We normalize the data and apply your proprietary operating procedures to identify initial lease risks and opportunities.
Tailored Firststreet AI Expert Agents are deployed to identify and mitigate lease audit opportunities across Finance, Compliance, Insurance, and more.
Proactively review findings and risks across multiple properties, tenants, and regions. Connect to additional platforms and BI reporting tools.
Competition
| Category | Companies | CRE Focus | AI-Native | Workflow Integrations | Notes |
|---|---|---|---|---|---|
| Firststreet | Firststreet | ● Strong | ● Strong | ● Strong | Built ground-up for CRE with predictive intelligence, integration, and compliance automation |
| CRE Solutions | Yardi, Dealpath, VTS | ● Strong | ◐ Partial | ◐ Partial | Used within departments; lack cross-functional intelligence |
| Global ERP | Salesforce, SAP, Oracle | ◐ Partial | ○ Weak | ◐ Partial | Broad capabilities but require heavy customization |
| AI Platforms | GPT, Hebbia, Gemini, Claude | ○ Weak | ● Strong | ○ Weak | General-purpose models, not tailored for CRE or integrated use |
| Consultants | Legal & Accounting Firms | ◐ Partial | ○ Weak | ◐ Partial | Reactive, time-consuming, expensive, not preventative |
| Category | Examples | What They Do | Core Limitation |
|---|---|---|---|
| Property Management Systems | Yardi, MRI, RealPage | System of record for CRE ops: store lease data, rent rolls, tenant info | Store lease information but do not govern lease logic. Clause interpretation, amendments, recoveries, and compliance are still managed manually. |
| Lease Abstraction / AI Contract Tools | Prophia, Leverton, Kira, MRI Contract Intelligence | Use AI to read lease PDFs and extract key terms | Extract and structure data but do not govern how lease clauses are executed operationally across the portfolio. |
| Lease Administration / Accounting | Visual Lease, LeaseQuery, ProLease | Manage lease accounting compliance (ASC 842 / IFRS 16), track dates, reporting | Focus on accounting and reporting rather than operational execution of lease clauses that determine income and compliance. |
| Lease Governance | Firststreet | Converts lease clauses into structured, governed logic that can be monitored and executed consistently across portfolios | Brings system-level governance to the rules that determine income, enabling consistent interpretation, compliance monitoring, and operational control. |
Business Model
One-time lease audit and deep-dive insights on a per-lease basis.
Ongoing enterprise governance and monitoring, priced on lease volume per year.
One-time, per-lease pricing. Surfaces billing exposure and establishes trust.
Audit findings become the mandate for ongoing governance.
ACV scales as customer acquires new assets.
NRR exceeds 100% structurally: governance pricing scales with lease count, and institutional operators are net acquirers of assets. CAC estimated from pilot outreach cycles. Gross margin reflects software-led delivery with minimal per-customer labor at scale.
SAM derived from ~8,000 institutional CRE operators in North America managing 1M+ SF, at estimated $500K average annual contract value at scale.
Financing
Team
CRE veteran with 10+ years spanning brokerage, investment, and advisory at Colliers International. Deep experience with national retailers, landlords, and institutional investors, giving him a nuanced understanding of where technology can improve real estate decisions.
Past: Colliers International
Growth-focused operator with 12+ years driving sales and commercialization for venture-backed, AI-native, and PropTech companies. Led enterprise sales and strategic partnerships across North America and Europe. Started his career in real estate investments at Cushman & Wakefield.
Past: BrainBox AI, Cushman & Wakefield, Altrio
Seasoned technology leader with deep expertise in AI, machine learning, and cloud-native architecture. Former CEO of Orda. Led development of enterprise-grade platforms used by Square and DoorDash. M.Sc. Computer Science, Tel Aviv University.
Past: Orda, Zend, Perforce
Advisors
Principal, Lease Forensics & Enforcement at Cresa Washington DC. 30+ years pioneering Operating Expense Passthrough Reviews. His team has recovered $30M+ for tenants. Former landlord accountant turned tenant advocate; expert witness in passthrough expense litigation. Guest lecturer, Georgetown University Masters of Real Estate.
Roadmap
Let's Connect
We're raising a $3M pre-seed round to complete our platform, secure initial enterprise pilots, and begin GTM execution.
trevor@firststreet.ai · 514-557-4677 · www.firststreet.ai