Muir AI

Muir AI is a Seattle-based technology company that uses satellite imagery, machine learning and supply‑chain data to generate product-level intelligence—primarily automated product carbon footprints (PCFs), should-cost models and supply‑chain origin breakdowns—for enterprises seeking to reduce emissions and optimize costs[1][2].[2]

High-Level overview

• Mission: Muir AI’s stated mission is to deliver product‑level intelligence that helps companies navigate tariffs, baseline and reduce supply‑chain emissions, and improve margins through cost and design insights[2].[2]
• Investment philosophy / Key sectors / Impact on startup ecosystem: Not applicable — Muir AI is a portfolio company / operator, not an investment firm. Instead, as a climate‑tech startup it operates in the decarbonization, supply‑chain intelligence and procurement analytics sectors and contributes to the climate‑tech ecosystem by advancing automated PCF generation and enabling enterprise decarbonization at scale[1][2].[1][2]

For a portfolio company (what Muir AI builds and who it serves)

• What product it builds: Muir builds a supply‑chain intelligence platform that generates automated product carbon footprints (PCFs), dynamic should‑cost models, and material/origin breakdowns using AI and satellite data[2][4][5].[2][4][5]
• Who it serves: Enterprise procurement, sustainability and product teams that need accurate product‑level emissions and cost intelligence across global supply chains[2][6].[2][6]
• What problem it solves: It addresses the difficulty of calculating complex scope‑3 supply‑chain emissions and estimating product manufacturing cost by automating data‑intensive modelling and tracing origins where conventional supplier reporting is sparse[1][5].[1][5]
• Growth momentum: Muir launched in February 2022, participated in Madrona Venture Labs, and raised a $3.25M seed round led by Base10 Partners (total disclosed funding ~$3.75M) as it brought its solution to market[1].[1]

Origin story

• Founders and background: Muir AI was co‑founded by CEO Harris Chalat, who previously worked at SpaceX and Relativity Space, and CTO Peter Williams, an aerospace and Amazon alumnus[1].[1]
• How the idea emerged: The founders combined aerospace and satellite expertise with machine learning to tackle the notoriously hard problem of supply‑chain emissions and sourcing visibility, applying remote sensing and AI to infer material origins and emissions where supplier data is incomplete[1][2].[1][2]
• Early traction / pivotal moments: The company launched in early 2022, joined Madrona Venture Labs’ accelerator, and secured seed financing led by Base10 Partners in 2023—moves that validated investor interest and supported product development and go‑to‑market[1].[1]

Core differentiators

• Data fusion: Combines satellite imagery and remote‑sensing signals with procurement and bill‑of‑materials data to infer product origins and material breakdowns—a differentiator versus purely questionnaire‑ or ledger‑based carbon tools[1][2].[1][2]
• Product‑level focus: Delivers automated, scalable product carbon footprints (PCFs) and should‑cost models rather than only facility‑ or company‑level estimates, enabling decisioning at the SKU or design level[2][5].[2][5]
• Enterprise integration / cloud platform: Built on cloud infrastructure with integrations (including availability through AWS partner listings), positioning it for enterprise workflows and scalability[3][6].[3][6]
• Speed and automation: Emphasizes rapid, automated generation of PCFs from simple procurement inputs to accelerate sustainability and procurement decisions[5].[5]

Role in the broader tech landscape

• Trend it’s riding: Muir sits at the intersection of climate tech, supply‑chain digitization, and AI‑driven analytics—areas seeing growing regulatory and corporate demand for scope‑3 emissions transparency and procurement optimization[1][2].[1][2]
• Why timing matters: Increasing regulatory pressure and corporate commitments on Scope‑3 emissions, plus improved satellite and ML capabilities, create demand for automated, auditable product‑level emissions data[1][2].[1][2]
• Market forces in its favor: Enterprise decarbonization mandates, investor and customer ESG expectations, and advances in remote sensing and AI lower barriers to adoption for automated PCF tools[1][3].[1][3]
• Influence on ecosystem: By producing scalable product‑level insights, Muir can accelerate corporate decarbonization workflows and push competitors and incumbents toward more automated, data‑driven PCF solutions[2][5].[2][5]

Quick take & future outlook

• What’s next: Expect Muir to continue expanding enterprise integrations, enrich models with additional remote‑sensing signals and procurement data, and broaden use cases from emissions to tariff and cost optimization as indicated by its product messaging[2][4].[2][4]
• Trends that will shape them: Regulatory disclosure rules for Scope‑3, corporates’ net‑zero commitments, higher fidelity satellite data, and demand for auditable emissions metrics will be material tailwinds[1][3].[1][3]
• How influence might evolve: If Muir scales adoption among large procurement organizations, it could become a default supplier of automated PCFs and should‑cost intelligence—raising the bar for how product design and procurement teams account for environmental and cost tradeoffs[2][5].[2][5]

Quick reminder: Muir AI is a private, early‑stage company; public information is limited to company statements, product materials and press coverage (seed financing, launch timeline and founders) cited above[1][2][3].[1][2][3]