Wastenaut is the live decision platform for the US waste market. Built for operators, investors, and sustainability teams to understand the market, test plans against it, and verify anything.
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Facility records in one place, hauler data in another, generator volumes scattered across permit filings, regulatory data buried in state portals. Stitching it together takes weeks. Doing it for every market you care about takes months.
Consultant deliverables, custom models, spreadsheet builds. All frozen at the moment of production. When the market shifts, the assumption changes, or a stakeholder asks "what if," the work starts over from scratch.
The investment memo says 250 tons a day at $58 a ton. The diligence report says the feedstock is "in hand." The sustainability report says diversion is on track. Each claim deserves scrutiny. Most of the time, no one's checking.
Every household. Every business. Every cropland parcel. Every forest parcel. Every livestock farm. Every generator of waste in the country. Plus every facility that processes it, every hauler that moves it, every material flow between them. Look up any of them and see how it connects to the rest: the contracts, the permits, the volumes. The system stays current as the market changes.
One connected layer covering the whole US waste market.
One platform. Five workflows. Pick where you start.
Draw a geography. See not just what's in it, but how it connects: who serves which generators, where material moves, where the gaps are. Come back next quarter and watch it change.
Pull a market profile →
Three sites. Three supply mixes. Three service designs. Run them against the same data and see the trade-offs in one view. Change an assumption. Rerun.
Run a comparison →
Take a projected volume, a supply commitment, a diversion rate. Verify each one against independent facility, hauler, and generator data. Cite the source. Hand the result to your IC. Rerun when the market or the deal moves.
Run a verification →
Move from "this market looks interesting" to "here's the operating plan." A sourcing strategy, a service area, an expansion path, a diversion approach. Sourced, dated, exportable. Update it as the market shifts or the plan does.
Build the plan →
Feedstock feasibility, market study, site comparison, diligence validation. Sourced, cited, current. Generated from the platform work that produced them. Regenerate when the underlying data does.
See a sample report →
01 Open the platform. Find your geography, your target, or the claim you need to test.
02 Change the inputs. Rerun. The data updates as the market does.
03 The report your IC, your board, or your lender is waiting for came from the work you just did. Export it. Rerun it when something changes.
01 Pull the facilities, haulers, and generators inside a geography. Trace the flows between them. Filter by what matters.
02 Run a scenario. Change the inputs. Rerun. Compare three sites, three supply mixes, three operational models against the same data. The data underneath is current, so the answer is too.
03 Take a projected volume, a supply commitment, a diversion rate. Verify each one against independent facility, hauler, and generator data. Surface the assumptions that don't hold. Hand your stakeholders the artifact they'll accept.
One query or a full integration. Pull any data point into your existing systems. Best for corporate teams and developers.
See Stream API →Sign in and drive the platform yourself. Surveys, scenarios, validations, reports. Best for operators, investors, and sustainability teams.
See Nexus →Custom integrations, embedded analyst function, deal-specific deep-dives. Best for organizations whose scope doesn't fit a standard subscription.
See Enterprise →We used to commission a fresh market study every cycle. Each one was outdated before we shipped the deck. We stopped doing that after we had the platform.
Our IC didn't push back on the supply assumptions. The artifact had what they wanted to see.
It's the connections we couldn't see before. Generator to hauler to facility to permit, all linked. That's what made the model defensible to our board.
A seller's projection didn't match what the underlying records showed. We caught it before the deal closed.
Pulling facility records, classifying them, cross-checking permits. That used to be analyst time. Now it's a query.
We came in to scope one market. We stayed because the next one needed scoping too.
Waste market intelligence is the data layer that connects facilities, haulers, generators, and material flows into one decision-ready picture. What it covers, who needs it, and why the industry went so long without it.
A complete guide to waste facility due diligence for investors — environmental, operational, financial, and competitive diligence across landfills, MRFs, and transfer stations.
Revenue data and growth drivers behind the US waste management market. Expert analysis of fragmented industry valuations, key segments, and what's driving growth through 2030.
What a tipping fee is, what US landfills charge per ton, and what moves disposal pricing — with state-by-state averages and how to use the data for site selection and deal models.
Traditional waste market studies take months and deliver static PDFs. Wastenaut delivers the same intelligence as a living data layer you can query, update, and rerun. Here is how the two approaches compare.
A guide to biomass feedstock economics for waste-to-energy investors — comparing rice husk, wood/bark, corn stover, manure/RNG, and forestry residues on cost, availability, energy yield, and supply risk.
Bring a deal, a market, or a claim you're working on. We'll walk you through what Wastenaut does with it.
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