In 2026 the DePIN vs. cloud cost debate is a data problem, not a vibes problem. We compare decentralized compute (Akash, io.net) and storage (Filecoin) against hyperscalers using verifiable supply and pricing data.
Not all DePIN networks generate revenue. We analyze on-chain protocol fees for 78 DePIN networks to show which ones have real economic activity and which are ghost towns. Revenue data sourced directly from chain state with verify_urls.
DePIN networks serve fundamentally different resource classes — storage, compute, GPU, bandwidth, wireless. We compare supply metrics across Filecoin, Akash, and io.net to show why cross-network comparison requires canonical metric mapping and why raw numbers mislead.
Most DePIN market cap figures are wrong because they multiply price by the wrong supply number. We break down circulating vs. fully-diluted valuation, how to source supply data directly, and why every number needs a verify_url.
DePIN is a transparency paradox: networks built on open ledgers still publish supply numbers nobody can verify. We diagnose the problem and lay out a concrete fix — verify_urls, canonical units, and Bitcoin-anchored provenance.
The headline GPU count on io.net is registered capacity, not working supply. We break down registered vs. active devices, explain why fill rate isn't utilization, and show how to query the real GPU supply data.
How anchoring DePIN telemetry batches to Bitcoin via OpenTimestamps creates a tamper-evident audit trail. Why this matters for data integrity, regulatory compliance, and building trust in decentralized infrastructure metrics.
Filecoin storage is measured in petabytes and exbibytes that get conflated constantly. We explain the unit trap (PB vs. EiB is a 1,024x error), how to read Filecoin's real storage stats, and why every value needs a unit and a verify_url.
A deep dive into the end-to-end protocol flow by which autonomous AI agents discover, evaluate, and purchase DePIN data products via the Model Context Protocol—covering JSON-RPC registration, credit issuance, product listing, snapshot procurement, Stripe-mediated top-ups, and the cryptographic trust guarantees that make agent commerce viable.
DePIN data is the fastest-growing segment of our catalog. Solar, water, EV, telecom — the sensors are multiplying and the data is undervalued.
Rate limiting is necessary but dangerous — too aggressive and agents can't evaluate your data. Our adaptive rate limiting strategy that balances protection with access.
How AI agents interact with structured data — experiments, insights, and production lessons.