Pathways builds AI that turns a manufacturer's messy supplier data into third-party-verified environmental reports - the boring paperwork that decides whether green construction actually happens.
Here is a fact about the buildings around you that is both obvious and slightly maddening: roughly 40% of global CO2 emissions come from the built environment, and a large chunk of that is not the lights or the heating - it is the concrete, steel, and glass the thing is made of. Everyone in construction knows this. The problem is that until recently nobody could produce the number fast enough to do anything about it.
The number in question is called an Environmental Product Declaration, or EPD - a third-party-verified label that says how much carbon a specific product, like a batch of ready-mix concrete, is responsible for. Producing one traditionally meant hiring consultants, wrangling spreadsheets, and waiting six to twelve months. By the time the EPD arrived, the data was stale and the project you needed it for had probably moved on. It was, in the polite phrasing of the industry, a bottleneck. In the impolite phrasing of one Pathways customer, it was closer to a root canal that lasted a year.
Pathways, a New York startup founded in 2022, looked at this and made a bet that is almost suspiciously simple: the science of measuring embodied carbon is fine. The paperwork around it is the problem. So they built software that ingests the data a manufacturer already has - raw material inputs, transportation, plant processes, the invoices piling up in some accounting system - and turns it into a verified EPD in weeks. Same rigor. Same third-party verification. Minus most of the waiting.
The clever part is not any single step. It is that Pathways keeps the model alive after the report is filed. A traditional LCA is a photograph - accurate the day it was taken, useless six months later. Pathways runs what it calls an environmental digital twin: a continuously updated model that lets a plant manager watch emissions hotspots move in real time and actually manage them.
AI parses unstructured data - invoices, docs, plant records - from a producer's existing IT systems.
A custom LCA engine calculates global warming potential and other impact metrics for each product.
Pathways coordinates third-party, NRMCA-recognized verification so the EPD holds up on real bids.
Live models surface hotspots, guiding decisions that cut product carbon over the following year.
Generate NRMCA-verified Environmental Product Declarations for ready-mix concrete in weeks instead of months, straight from data you already collect.
A purpose-built life cycle assessment engine tracking global warming potential, acidification, eutrophication, ozone depletion, and smog formation.
Continuously updated models of your production process so you can spot emissions hotspots and watch reduction progress in real time.
A service-first layer that handles data collection, analysis, and verification coordination - so nobody gets pulled off core operations.
The two met as classmates at Harvard, which is a tidy origin for a company that ended up parked inside ready-mix concrete plants. Their backgrounds are complementary in the way founder decks always claim to be but rarely are: one knows heavy industry and sustainability strategy, the other knows how to scale a startup from a whiteboard into something with 90 people.
Spent the prior decade scaling startups including Uber, Clutter, and Two Chairs before turning to climate. Credits a relentless feedback culture for keeping the team aligned - "consistently making time to give feedback removes stigma."
Former McKinsey consultant who previously scaled a venture in material recycling. The industrial-sustainability half of the pair, and the voice behind the company's data-layer mission.
In February 2024 Pathways closed a $2.5M pre-seed round - reported oversubscribed by $1.5M - co-led by Zacua Ventures and Pi Labs, with Blue Lion Global, Positive Ventures, Jetstream, Refashiond, Great Wave Ventures, and Anglet joining. The interesting thing about the round is not the size. It is that a group of investors decided the data layer for green building was worth backing before it was fashionable to say so.