ENTER PLATFORM

Accelerating Capital.
Securing the Future.

The AI-native platform to identify the companies building a more resilient world.

Pre-seed pitch deck - q3, 2026

The Problem

Exploding energy demand and consumption from AI, electrification, and a growing global middle class create an urgent need to produce more forms of affordable, reliable, and clean energy and upgrade outdated grids. Geopolitical upheaval is reshaping supply chains and putting a premium on resource resilience and energy security. 2024 was the hottest on record and the first to exceed 1.5°C of warming on average, and climate change costs the world 12% in gross domestic product (GDP) losses for every 1°C of warming.

These challenges demand scalable solutions and capital allocators have begun to accelerate institutional capital deployment. Our technology platform helps clients accelerate deployment by converting technical insights into real-world opportunities, creating dynamic, promising feedback loops that drive return on investment and build a more resilient economy.

Why Capital Markets Matters

01

Investment Opportunity

A once-in-a-generation opportunity to shape energy, security, and industrial systems.

02

Industrial Transformation

Transformation of core industrial systems—worth trillions of dollars—that underpin the global economy such as energy, manufacturing, and infrastructure are being rebuilt and driving long-term prosperity.

03

Technology Gap

Capital allocators with legacy tools struggle to handle the complexity and scale required for linking economic resilience, climate transition, and national security.

Market Timing

ResilienceAI harnesses four powerful macroeconomic forces, empowering institutional investors to capture economic value and accelerate commercially viable companies.

Green Industrial Revolution

This "tectonic shift" towards net-zero is hailed as a historic investment opportunity by global financial leaders.

ResilienceAI enables capital markets to research and evaluate companies driving new climate solutions and the transition.

Global Macro-Resiliency

Geopolitics, supply chain on-shoring, strategic defense, and climate are the highest priority for capital allocators.

ResilienceAI helps investors align their strategies and portfolios with diverse thematic research across regions.

Impacts of Climate Change

Climate change poses significant credit, market, and operational risks, with economic losses estimated at 15-30% of global GDP by 2100.

ResilienceAI assists investors in evaluating companies decarbonizing, building climate solutions, and adapting business models to environmental shifts.

Artificial General Intelligence

AI is the 21st century's most transformative technology, now capable of passing complex financial exams.

ResilienceAI leverages AI and agentic workflows to empower investors with complex reasoning for evaluating company financial performance and global macro-resilience.

The Solution

Based on client and investor feedback from tier-1 institutions, our technology platform addresses four critical pain points that prevent investors from efficiently deploying capital into the broader resiliency super-cycle.

1

Financial Intelligence

Deep analysis of companies' financial health, performance metrics, and competitive market positioning through AI-powered research workflows

2

Thematic Research Intelligence

Comprehensive evaluation of global macro-resiliency, including decarbonization trajectories, transition pathways, supply chain on shoring, and strategic defense

3

Data Integration

Seamless connection with third-party vendors and data sources, processing both structured data (financial statements) and unstructured data (reports, PDFs, news)

4

Automated & Agentic Workflows

Deploy AI agents to automate research tasks: company comparisons, report generation, portfolio monitoring, and real-time tracking of climate and financial metrics

Client Requirements

The global economy is undergoing a multi-trillion-dollar structural super-cycle. Clients require technology solutions that help them find companies driving alpha generation across interrelated investments.

Pillar 1

Energy Independence &
Climate Transition

Pillar 2

Resilient Supply Chains &
Advanced Manufacturing

Pillar 3

Strategic Defense &
Aerospace

Pillar 4

Frontier & Strategic
Technologies

The Intelligence Layer for the Resilience Economy:
Model-Agnostic Agentic Engine

OpenAI

Anthropic
Claude

Google
Gemini

Grok

ResilienceAI
Intelligence Router

Omni-Model
Intelligence Routing

dynamically assigns tasks to
the best-suited model.

MCP
Integration

securely connects models to
Bloomberg, climate databases, patent
registries, supply chain manifests.

Multi-Agent
Workflows

Diligence Agent triggers financial
modeling agent triggers climate
risk agent concurrently.

API-First
Extensibility

integrates into proprietary
CRM, ERP, and portfolio
management tools.

Go-To-Market: The Barbell Strategy

GTM Profile: Private Markets -
Private Equity

GTM Profile: Private Credit & Infrastructure Debt

Hook: Speed to conviction and uncovering hidden growth and TAM.

Hook: Automated downside modeling and risk-adjusted pricing.

Core Wedge: Upload a pitch deck, instantly receive AI-generated TAM/SAM/SOM breakdown with cross-domain applications.

Core Wedge: Automated unit economics and financial projections builder for 10–20–20-year infrastructure horizons.

Sales Motion: The Show, Don't Tell Pitch – run a live deck through multi-agent workflow during the demo.

Sales Motion: The Stress-Test Pitch – ingest raw project finance docs live, build financial model, run Monte Carlo DSCR simulation.

Pricing: Seat-based SaaS + API usage tiers for CRM integration.

Pricing: Platform access fee + per-deal analysis fee.

Data Network Effect: PE frontier tech analysis trains the same models that de-risk infrastructure financing.

Competitive Advantage

ResilienceAI stands apart in a crowded market by integrating AI-native architecture with deep economic resilience and climate expertise, addressing a critical gap in institutional investing.

Key Differentiation Factors: Where ResilienceAI Wins

AI-Native Architecture

AI-native architecture is cheaper and faster to scale than retrofitting legacy systems.

Finance Integration

Seamlessly combines climate risk with financial analysis for comprehensive insights.

Automated Workflows

AI agents handle complex research tasks end-to-end, boosting efficiency.

Real-time Processing

Live data integration provides up-to-date information versus static reports.

Cost Efficiency

Delivers powerful capabilities at a fraction of Bloomberg/Refinitiv costs.

Institutional Investor Focus

Purpose-built for asset managers, providing tailored tools versus generic solutions.

Competitive Advantages

First-Mover Advantage

Leading the charge in AI-powered climate finance solutions.

Deep Relationships

Strong institutional connections and extensive domain expertise.

Proprietary AI Models

Advanced AI models trained on specialized climate-finance datasets.

Defensible Moat

Strengthened by network effects and a data flywheel for continuous improvement.

Pipeline & Early Traction

Ongoing market validation and feedback demonstrates significant interest from industry leaders, willingness to collaborate on product development, and active introductions to decision-makers within global financial firms.

Chief Sustainability Officer

Edmond de Rothschild Investment — validated need for integrated climate and financial research workflows

Head of Climate Research & Strategy

State Street Investment Management — validated pain points in existing data and analytics tools

Head of Sustainable Investment Advisory

Allianz Group — validated interest in AI-powered automation for portfolio analysis

Executive Director Climate Technology

J.P. Morgan — new insights into tech investment bank needs and market opportunity

Head of Sustainability Research

State Street Investment Management — validated pricing model and platform feature prioritization

TAM, SAM, SOM: Bottom-Up Market Sizing

$25M ARR SOM (Year 3)


$1.25B SAM

Aggressive but realistic benchmark for venture-backed enterprise SaaS.

Baseline ACV: $50,000 flat platform fee. Comparables: AlphaSense, PitchBook, AI infrastructure platforms ($25K–$150K+ ACV).

Founder Market Fit

Todd Arthur Bridges, Ph.D.
Co-Founder & CEO

Dr. Bridges has a deep passion for building products, technology, and startups that create sustainable economic growth, generate sustainable return on investment (SROI), and help businesses and markets solve the world’s biggest challenges. He has built innovative solutions in the technology and financial services industries. His experience within industry has given him the opportunity to develop global strategies, fundraise (Seed to Series B) across the private capital markets, convert complex ideas into products (Zero to One), build innovative product roadmaps, build high-performing global teams, and advise clients on climate solutions. He enjoys working with public and private investors to build solutions which drive sustainable economic growth, develop innovative AI product solutions, and accelerate their return on investment and the net-zero transition.

Track Record

  • Designed, built, and scaled solutions for State Street, Allianz Group, Goldman Sachs, JP Morgan, Bloomberg, Bridgewater, DWS, and BNY Mellon
  • Worked with multiple CEOs and founding teams at early-stage technology startups to secure venture capital funding (Seed to Series B)
  • Built climate products and platforms (Zero to One) for institutional clients

Product Expertise

Extensive expertise in asset management, climate finance, climate investing, applied research, data & analytics, applied artificial intelligence, and investment workflows

Industry Network

Direct relationships with decision-makers at global asset managers, asset owners, investment banks, and multilateral development banks

Startup Experience

Multiple successful fundraises and product launches

Founder Market Fit

Marcin Mierzejewski

Co-Founder & CTO

Marcin led Google engineering teams that developed a foundational distributed data storage system used across many Google services, including Ads, BigQuery, DeepMind, Maps, Search, and YouTube, to manage exabytes of data and process millions of requests per second.

As an engineering director, he also built and managed the largest Cloud Networking engineering site outside the United States, leading teams responsible for the Google Cloud Console (Networking) and Network Intelligence Center, covering network observability, monitoring, and troubleshooting.

Earlier in his career at Fujitsu, Marcin pioneered AI/ML innovation by developing a first-of-its-kind distributed workflow platform that automated model evaluation for high-stakes applications, including drug discovery and financial credit scoring.

Prior to Google, Marcin was CTO of multiple technology startups.

Track Record

  • Designed, built, and scaled solutions for Google, Google Cloud Platform, OpenX, Fujitsu, and Motorola
  • Worked across engineering site within US, Poland, and global locations to develop cloud-based platforms, enterprise software, and integrate cutting-edge LLMs and ML pipelines
  • Built products, platforms, and engineering teams for Fortune 100 companies

Product Expertise

Extensive expertise in Google Cloud Platform (GCP), artificial intelligence, large language models, distributed systems, storage, infrastructure, security, and compliance

Industry Network

Direct relationships with engineering leadership at top technology companies

Startup Experience

Helped over 10 startups build their MVP as a Founding Engineer and served as CTO for two successful startups

12-Month Product Roadmap: 4 Phases to $1M+ ARR

Months 1–3
Foundation
& Alpha

Months 4–6
Beta & First Revenue

Months 7–9
Scale & API Expansion

Months 10–12
Defensibility &
Seed Prep

Omni-model router MVP, secure ingestion pipeline, TAM/SAM/SOM alpha tool, financial alpha.

Multi-agent orchestration, automated investment memo generator, unit economics builder, first MCP integration.

API endpoints live, high-volume batch pitch deck triage, Monte Carlo DSCR simulation engine.

Cross-domain convergence mapping, SOC2 Type II, proprietary data vaults.

GTM: Sign 4 Design Partners.

GTM: 3 Design Partners converted ($150K ARR), 10 new paid Beta funds.

GTM: 15 paid customers, 3 upsells to high-tier API plans.

GTM: 20+ paid customers, $1M+ ARR.

20 customers × $50K ACV = $1M ARR – Seed round ready.

The Ask: $1M

Pre-Seed Funding

We are raising a $1 million pre-seed round to develop a market-ready MVP and assemble a world-class founding team.

Use of Funds

Product Development

Build market-ready MVP with core AI-powered research workflows, agents, and data integration APIs

Leadership Team

Hire CRO (institutional sales) and Head of AI (model development)

Market Validation

Pilot programs with 3-5 design partners from tier-1 institutions

Key Milestones (12 Months)

Q3 2026

Complete pre-seed raise and hire core team

Q4 2026

Launch MVP with design partners

Q1 2027

Release market-ready MVP and secure initial paying customers

Q2 2027

Prepare for seed round with validated revenue

Appendix

Fully Functioning Prototype

Our prototype has full integration of Google, Athropic, OpenAI, and Grok and deploys those models into 5 AI-powered applications designed to transform complex financial, climate, and resilience workflows. (product demo)

Cloud-Native Platform

Hosted securely on Google Cloud Platform (GCP), our prototype ensures robust, scalable, and high-performance operations for all users.

Natural Language Prompts

Translate financial and climate complexity into decision-useful insights using natural language prompts - with prebuilt suggested prompts.

Applied AI & Reasoning

Leveraging advanced AI, ResilienceAI generates deep, actionable insights from vast datasets, going beyond traditional analytics.

Analysis & Reporting

Seamlessly integrates diverse data sources and automatically generates comprehensive investment committee reports to streamline decision-making.

Technical Roadmap

Our technical roadmap outlines a phased approach to AI development, ensuring robust foundational capabilities while progressively building towards highly specialized and proprietary solutions.

Phase 1: Foundation with Public LLMs

Integrate leading large language models like Google Gemini and OpenAI GPT for initial data processing, risk assessment, and insight generation across both publicly available and client-specific private datasets.

Phase 2: Performance through Fine-Tuning

Develop specialized models by fine-tuning public LLMs (Gemini, OpenAI) with proprietary, domain-specific climate resilience data, significantly enhancing accuracy, relevance, and contextual understanding for our target applications.

Phase 3: Proprietary Models for Strategic Advantage

Build highly optimized, custom large language models based on leading open-source architectures (e.g., Google Gemma, Meta LLaMA), enabling deeper integration, superior cost efficiency, and unparalleled competitive differentiation in climate analytics.

Architecture Roadmap

Our architectural roadmap is designed to maximize agility, security, control, while progressing from flexible public cloud foundations to specialized, secure private deployments.

Phase 1: Multi-Tenant Public Cloud

Utilize Google Cloud Platform (GCP) to build a scalable multi-tenant solution, focusing on evaluating the latest technologies and tools for rapid iteration and deployment.

Phase 2: Single-Tenant Confidential Computing

Transition to a single-tenant confidential computing solution, ensuring all workloads are completely isolated and secured, providing unparalleled data privacy and integrity.

Phase 3: Dedicated Private Cloud Deployment

Develop a dedicated solution capable of deployment in private cloud environments, offering clients maximum control, customization, and integration with their existing infrastructure.

Platform Partnerships & Integration

ResilienceAI will strategically integrate its core intelligence into leading AI platforms like Anthropic, and partner with specialized data providers to deliver unparalleled, trusted financial insights directly within investor workflows.

ResilienceAI Integration

Our proprietary intelligence seamlessly embeds into frontier AI ecosystems.

Anthropic Plugin Architecture

Leveraging Anthropic's robust plugin framework for secure and efficient data exchange.

Data Partner Ecosystem

Accessing specialized, institutional-grade data and domain expertise via partner plugins.

Enhanced Finance Workflows

Integrating trusted, proprietary data directly into Claude's context for finance professionals.

Agentic Intelligence Pipeline

From raw data to investor-ready insight – fully automated

EVIDENCE

ANALYSIS

COMPOSE

Ingest real-time data from Bloomberg, SEC filings, registries, news feeds, supply chain manifests & internal portfolio/user data

Parse, normalize & structure raw data – financial statements, climate disclosures, patent filings

Cross-validate signals across sources; flag anomalies, conflicts & data quality issues

Run AI-powered simulations: climate risk scoring, financial modeling, competitive benchmarking

Auto-generate investor-grade reports, memos & portfolio monitoring dashboards

The Analysis Phase: Parallel Intelligence Engine

Simultaneous execution of quantitative simulation and AI reasoning — converging into a unified investment signal

Monte Carlo Simulation

10,000+ probabilistic scenarios modeled across climate risk, financial stress, and market volatility variables

  • Portfolio Stress Testing
  • VaR Modeling
  • Climate Scenario Analysis
  • Transition Risk Quantification

LLM Agentic Analysis

Multi-model AI agents reason over unstructured data — earnings calls, ESG reports, regulatory filings, news

  • Sentiment Analysis
  • Regulatory Risk
  • Competitive Intelligence
  • Management Quality Scoring

↓

⟶ Unified Resilience Score

Both engines feed into a single composite score: financial health × resilience × transition readiness

Integration Without Disruption

ResilienceAI meets your team where they work — from standalone platform to embedded intelligence in existing workflows

Recommended for new teams

Full-Featured UI

A complete, standalone platform experience. Purpose-built for investment analysts, risk teams, and portfolio managers who want the full ResilienceAI workflow out of the box.

For existing workflows

MCP Integration

Connect ResilienceAI directly into your existing tools via Model Context Protocol. Surface intelligence inside Bloomberg Terminal, Notion, Slack, or any MCP-compatible environment.

For AI-native teams

Agentic Skill

Deploy ResilienceAI as a callable skill within your own agentic pipelines. Let your AI orchestration layer invoke our analysis engine as a specialized tool — on demand, at scale.

All integration modes share the same underlying intelligence engine — same models, same data, same Unified Resilience Score.

Privacy From the Core

A vertically integrated platform built for institutions that cannot compromise on data sovereignty

Cloud-Hosted, Isolated Tenancy

Today: each client operates in a fully isolated environment. No data co-mingling. No shared inference. Your data never trains our models.

Private Cloud Deployment

Near-term: deploy the full ResilienceAI stack inside your own cloud VPC — AWS, Azure, or GCP. You control the keys, the logs, and the egress.

On-Premise & Air-Gapped

Roadmap: full on-premise deployment for sovereign wealth funds, regulated institutions, and defense-adjacent allocators requiring complete network isolation.

Proprietary LLM Models

Endgame: purpose-built ResilienceAI foundation models — trained on financial, climate, and resilience data — served entirely from your private instance. Zero dependency on third-party model providers.

Zero

Third-party data exposure

100%

Audit trail & explainability

Full

Model & infrastructure ownership — on your timeline

Built for institutions where data is the moat. ResilienceAI's vertical integration roadmap ensures your intelligence advantage stays yours.

Always-On Intelligence

ResilienceAI runs continuously in the background — monitoring new signals, re-running analysis, and surfacing alerts before your team even opens the platform

Signal Detection

New data arrives continuously — earnings releases, regulatory filings, climate events, supply chain disruptions, macro shifts. The system ingests in real time.

Automated Re-Analysis

Every new signal triggers a targeted re-run of affected models. Portfolio scores, risk flags, and scenario outputs are refreshed automatically — no manual prompting required.

Delta Alerting

Only meaningful changes surface to your team. Threshold-based alerts notify analysts when a company's Resilience Score moves materially, or when a new risk factor emerges.

Audit Trail

Every re-analysis is logged with timestamps, data sources, and model versions — giving compliance teams a full, explainable history of every score change.

24/7

Continuous monitoring across all portfolio positions

<5 min

Average time from new signal to updated Resilience Score

Zero

Manual triggers required — fully autonomous re-analysis

Your edge isn't just better analysis — it's faster analysis. ResilienceAI ensures your intelligence is always current, never stale.