Agentic AI for the largest asset class on earth.

Autonomous AI agents that ingest, model, and reason over building-level data to automate the most expensive knowledge work in commercial real estate.

Investor Presentation  |  March 2026  |  Confidential

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From

AI-powered building decarbonization SaaS

To

Agentic AI infrastructure for institutional CRE decisions

Same proprietary data. Same domain expertise. Same institutional customers.
Bigger buyer. Bigger budget.

Market Context

$7.3B

Agentic AI market (2025)

Projected $139B by 2034

40.5%

CAGR through 2034

Fastest-growing AI segment

1B+

AI agents operational by EOY 2026

IBM / Salesforce estimate

MCP (Model Context Protocol) is becoming "the USB-C of AI" for enterprise systems.

Sources: Fortune Business Insights  ·  MEV  ·  CIO.com

Six years. $22M+ invested.
The hardest problem solved.

75%

of North American CRE in proprietary database

950K+

unique physics-based building models

14K+

virtual energy audits delivered

8

purpose-built AI research agents

Validated by JLL at 5% of cost, 1% of time vs. traditional audits. Recognized by GRESB and USGBC (LEED v5 certification pathway).

What Didn't Scale

  • Product went too vertical: long sales cycles, services-heavy delivery
  • Dependence on slow-moving building owners
  • ACV out of balance relative to CAC
  • Selling audits and plans, not solving an acute repeat pain

Where the Money Is.

$9.7T to $16.5T

ESG-labelled assets (2026–2031)

$8–9B

DD / vendor-risk market (mid-decade)

30+

US jurisdictions with Building Performance Standards

Three products. One data moat.

DDQ/RFP Automation Agent

Autonomous completion of institutional due diligence questionnaires. What took a team of analysts weeks now takes minutes.

Buyer

Fund managers, LP relations, ESG compliance

Revenue

Per-questionnaire or annual license

Starwood ready to buy

Portfolio Intelligence Agent

Autonomous capital planning across entire portfolios: prioritization, sequencing, financial modeling, regulatory risk.

Buyer

Asset managers, GPs, property managers

Revenue

Per-building or portfolio subscription

Blackstone, AvalonBay, Tishman, UDR

MCP-Native Data Infrastructure

Audette as a callable data source within any MCP-compatible enterprise AI workflow.

Buyer

Enterprise CRE tech teams, AI platforms

Revenue

API / usage-based pricing

8 agents already deployed

Traditional SaaS Audette Agentic Platform
Data handling User uploads, manual input Autonomous ingestion from 50+ sources
Output Dashboards, static reports Completed documents, decisions, actions
Scope Single workflow per tool Cross-functional reasoning across datasets
Integration Point-to-point APIs MCP-native, any LLM orchestrator
Scaling More seats = more cost More buildings = better models = more value
Revenue Per-seat subscription Per-action, per-building, usage-based

"Vertical AI agents could be 10x bigger than traditional SaaS." Audette is the first mover in commercial real estate.

Six layers. No shortcut.

Proprietary Data

75% of North American CRE. 6 years of ingestion. No shortcut.

Validated Models

950K+ physics-based building models. JLL-verified.

Domain Codification

100 years of building science expertise encoded in inference rules.

Institutional Trust

GRESB, USGBC LEED v5, blue-chip logos.

Data Flywheel

More buildings = better recommendations = more buildings.

Model Agnostic

All LLM integrations behind common API. No vendor lock-in.

Real revenue. Real customers.

Revenue (T12M) $1.73M
ACV ~$1.95M
YoY Growth 55–94%
Gross Margin 73–79%
Pipeline $2.2M
Team 12 FTEs

Notable Customers

Blackstone
Greystar
AvalonBay
Tishman Speyer
UDR
JPMorgan
Camden
Madison Intl
Starwood
KKR
Clarion Partners
Morguard

In their own words.

“Before, we had no way to quantify transition risk during due diligence. With Audette, not only can we quantify it, but we can understand it to make real decisions. That's not something we've ever been able to do before.”

Katie Cappola

VP Sustainability, Madison International Realty

$7B AUM

“What I care about is decarbonization intelligence so I can think about capital allocation at scale. You spoke the language of engineering as well as asset management, and provided a very clear capital planning tool. That really set you apart.

Mauricio Serna

Global Head of Sustainability, Starwood Capital

$115B+ AUM

Audette gives us the ability to conduct that quality of evaluation across our portfolio in a cost-effective way. All while producing a dynamic, interactive report. I just haven't seen an alternative that is competitive.”

Thomas Stanchak

Managing Director, Stoneweg

$11.6B AUM

Addressable Markets

CRE Due Diligence + Compliance $8–9B
ESG-Labelled Assets Under Management $9.7T–$16.5T
Agentic AI Enterprise Infrastructure $7.3B–$139B

Every institutional CRE transaction, fund raise, LP report, regulatory filing, and capital plan that touches building performance data.

Audette is not a climate company that uses AI.
It is an agentic AI company with a proprietary data moat in the largest asset class on earth.

Harvey

→ Audette for CRE due diligence

Vanta

→ Audette for ESG / building compliance

Ramp

→ Audette agents for CRE capital workflows

Palantir

→ Audette ontology for building assets

Leadership

Christopher Naismith

Founder & CEO

Engineer and building scientist. 10+ years in HVAC, building performance, M&V. Co-led USGBC and GRESB working groups.

Pallen Chiu

Chief Growth Officer

Stanford MBA. Enterprise GTM at One Medical and Twin Health.

Tim Cull

Head of Product

Leads product strategy and agentic architecture transition.

The Ask

Engineering Productize DDQ/RFP agent and MCP infrastructure
Go-to-Market Attack the DDQ / compliance buyer
Runway Execute on Starwood and $2.2M pipeline

Audette has already done the hardest part. The data, the models, the trust, the domain AI. Agentic infrastructure is the monetization unlock.

Agentic AI for the largest asset class on earth.

christopher@audette.io  |  audette.io

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