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.
The Origin
We saw a gap no one else could fill.
Energy audits are a $3B+ annual market, deployed across thousands of buildings, but stuck in the 1990s: manual, expensive, slow, and non-scalable. We built AI that does in minutes what took consultants weeks, at 5% of the cost and 1% of the time. We deployed it into the fastest-growing beachhead in commercial real estate.
Traction
2024 proved the model.
Contracted ACV, Jan 2023 through Dec 2024.
“Climate risk is investment risk. We are on the edge of a fundamental reshaping of finance. In the near future, and sooner than most anticipate, there will be a significant reallocation of capital.”
— Larry Fink, BlackRock, 2020 Annual Letter to CEOs
The Headwinds
In 2025, things changed.
Political
ESG backlash, regulatory uncertainty, mandate rollbacks.
Technological
AI commoditized overnight. LLMs collapsed the moat around "AI-powered."
Market
CRE went transactional. Deal volume cratered. Sustainability budgets froze.
Strategic
Product too vertical. Sales cycles too long. ACV out of balance with CAC.
“In 2024, I retired the term ESG. In 2025, we removed it from more than 50 European strategies impacting $51 billion in assets. The language became too politicized to be useful.”
— Larry Fink, Chairman & CEO, BlackRock ($11.6T AUM)
2025 Annual Chairman’s Letter to Investors
The New Play
From product to infrastructure.
What we’re building
AI agents that embed directly into institutional CRE workflows. Not a dashboard. Not a report. Autonomous agents that ingest, reason, and act on building data at the point of decision.
Embed upstream
DDQ/RFP automation for acquisitions teams. Starwood ready to buy.
Monetize downstream
Portfolio intelligence for asset managers. Blackstone, AvalonBay, UDR.
Scale through infrastructure
MCP-native data layer for any AI workflow. API/usage pricing.
Why This Works
Embed upstream. Monetize downstream.
DDQ/RFP Automation Agent
Autonomous completion of institutional due diligence questionnaires. What took analysts weeks now takes minutes.
Revenue
Per-questionnaire or annual license
Signal: Starwood ready to buy
Portfolio Intelligence Agent
Autonomous capital planning across entire portfolios: prioritization, sequencing, financial modeling, regulatory risk.
Revenue
Per-building or portfolio subscription
Signal: Blackstone, AvalonBay, Tishman, UDR
MCP-Native Data Infrastructure
Audette as a callable data source within any MCP-compatible enterprise AI workflow. Any LLM orchestrator. Any stack.
Revenue
API/usage-based pricing
Signal: 8 agents already deployed
Why Agentic
Not “AI-powered.” Autonomous.
| 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 building the vertical AI layer for the largest asset class on earth.
The Moat
Six years of compounding advantage.
Proprietary Data
75% of NA CRE in proprietary database. Years of data partnerships—not scraped.
Validated Models
950K+ physics-based building models. JLL-verified—not hallucinated.
Domain Codification
50+ years of engineering logic encoded into inference rules—not prompted.
Institutional Trust
GRESB, USGBC LEED v5 certified pathway—not self-proclaimed.
Data Flywheel
Every building analyzed makes the next one better. Compounding by design.
Model-Agnostic
Not locked to any LLM. Runs on any foundation model. Future-proof by architecture.
Traction
Real revenue. Real customers.
Notable Customers
Customer Voices
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
Market Size
Addressable Markets
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
The Team
Built for a second bite.
12 FTEs. Six years of domain depth. Ready to scale.
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
Repositioning requires recapitalization.
Ground floor. Derisked. Ready to scale.
christopher@audette.io | audette.io