Trusty: provenance library workspace (initial import)

docs/product-use-cases.md

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+# Trusty — Product Use Cases and Beneficiaries
+
+A non-technical overview of what Trusty enables, the products it unlocks, and
+who benefits. This is the "what it does for the customer" view, not the
+"how it works under the hood" view.
+
+---
+
+## What Trusty Is, In One Paragraph
+
+Trusty is a tamper-evident audit layer. Any data that flows through it — a
+sensor reading, a state transition, a decision, an agent action — gets sealed
+into a chain that cannot be silently edited after the fact. If anyone changes,
+inserts, deletes, or reorders a single record, the chain visibly breaks. That
+break is itself an event the system can alert on. It is deliberately small,
+cheap to run, and embeddable anywhere data needs to be trustworthy.
+
+The business model is commodity-priced, high-margin, volume-driven. Trusty is
+the door-opener. Every application that sits on top of it — carbon-credit
+SaaS, compliance monitoring, AI agent accountability, data marketplaces, and
+Threadkeeper — rides the same audit spine.
+
+---
+
+## 1. Carbon Credits You Can Actually Insure
+
+**The problem.** Carbon credits are only worth what someone will pay for them,
+and insurers will not underwrite credits backed by sensor data that could have
+been quietly edited after the fact.
+
+**What Trusty enables.** Every environmental reading from every sensor gets a
+tamper-proof timestamp and fingerprint the moment it is recorded. If anyone
+changes a single number later, it shows immediately and publicly. Climate
+models (via NVIDIA Omniverse / Earth-2) then ingest data that is provably
+untampered.
+
+**Who benefits.**
+- Carbon-credit SaaS operators — can now sell credits that insurers will
+  underwrite.
+- Insurers — can price carbon-credit policies with actual evidentiary
+  foundation.
+- Buyers / offset purchasers — know the credit represents real, measured
+  reduction, not a spreadsheet.
+- Regulators — can audit the full chain without trusting the operator.
+
+---
+
+## 2. IoT Sensor Networks That Prove Themselves
+
+**The problem.** With thousands of sensors in the field — pipelines, factories,
+farms, power grids, cold chains, emissions monitors — you cannot watch them
+all. A malfunctioning, spoofed, or tampered sensor can go undetected for
+months, and the financial, regulatory, and reputational cost is enormous.
+
+**What Trusty enables.** Every sensor reading is chained to the one before
+it. The absence of a valid reading is itself the alarm — you do not need a
+separate intrusion detector. Trusty handles fleet-scale workloads
+(approximately 19,000 readings per second per host), so thousands of devices
+can write into the same audit trail without slowing anything down.
+
+**Who benefits.**
+- Industrial operators (oil and gas, manufacturing, utilities) — catch
+  tampering and device failure in real time.
+- Insurance and reinsurance — underwrite sensor-driven policies with
+  confidence.
+- Supply chain and cold-chain operators — prove goods were handled correctly
+  end to end.
+- Compliance and safety teams — turn "we think the sensors worked" into "we
+  can prove it."
+
+---
+
+## 3. Active Compliance Monitoring and the Liability Flip
+
+**The problem.** In regulated industries — pharma, aviation, finance, food
+safety, medical devices — disputes come down to "what did your system
+record?" Most enterprise logs are editable, which leaves the company
+carrying the liability.
+
+**What Trusty enables.** Pair Trusty with a rule set that defines which
+transitions are *legal* ("a dose can only be administered after a
+verification step"). Every legitimate transition is sealed into the chain.
+Anything outside the rules cannot produce a valid entry. The chain becomes
+legal-grade evidence of what actually happened.
+
+**The liability flip.** "It is in the chain" or "it is not in the chain" is
+a stronger claim in a dispute than any editable database log. The burden of
+proof moves from the operator (who currently has to defend the integrity of
+their logs) onto the claimant. This is the single strongest commercial
+story Trusty has.
+
+**Who benefits.**
+- Pharma and medical device manufacturers — audit-ready by default for FDA,
+  EMA, and equivalent regulators.
+- Aviation and aerospace — tamper-evident maintenance and flight-ops records.
+- Financial services — provable trade, order, and settlement history.
+- Legal teams — reduce discovery cost and win disputes on evidentiary
+  strength.
+- Insurers of the above — lower claim cost when the audit trail is
+  unambiguous.
+
+---
+
+## 4. Audit-Ready by Default: The Proof Bundle
+
+**The problem.** Audits, regulatory reviews, insurance claims, and legal
+disputes all require handing evidence to someone who does not trust you.
+Today that is a scramble of spreadsheets, screenshots, and lawyers, and the
+recipient still has to take your word for most of it.
+
+**What Trusty enables.** Export a single sealed bundle covering any time
+window or entity. The recipient — auditor, insurer, regulator, opposing
+counsel — verifies it independently on their own equipment, with no access
+to your systems and no need to trust the operator. The bundle carries
+everything required: the records, the cryptographic anchors, and the
+verification keys.
+
+**Who benefits.**
+- Compliance and audit teams — turn compliance from a project into a button.
+- Insurers and claims adjusters — verify losses without site visits or
+  vendor cooperation.
+- Regulators — receive evidence in a standard, self-verifying format.
+- Law firms — deliver and receive discovery material that is demonstrably
+  authentic.
+- Any business with "prove it" as part of its sales cycle — verifiability
+  becomes the product.
+
+---
+
+## 5. Data Marketplace Provenance
+
+**The problem.** In peer-to-peer and decentralized data marketplaces,
+publishers can silently swap individual pieces of a dataset even when each
+piece is individually signed — because signatures do not prove ordering or
+history.
+
+**What Trusty enables.** Every slice of the dataset is linked to its
+neighbors so any substitution, deletion, or reordering is immediately
+visible. You can prove not just "this piece is authentic" but "this is the
+complete history, in order, unchanged."
+
+**Who benefits.**
+- Distant Star (Eric's decentralized data-network protocol) — gains a
+  provenance layer it currently lacks.
+- Data publishers — can charge a premium for verifiable datasets.
+- Data buyers (enterprise, scientific, government) — can finally adopt
+  decentralized data sources for regulated work.
+- Validators and data curators — their attestations now anchor to a chain
+  state that proves what they reviewed has not changed.
+
+---
+
+## 6. Provable AI Agents and Agent Swarms
+
+**The problem.** When AI agents make decisions — trading, legal, medical,
+autonomous systems, customer-facing automation — regulators, customers, and
+insurers increasingly need to prove not just *what the agent did* but *what
+it was paying attention to* when it did it. Without that, AI cannot be
+adopted at scale in regulated environments.
+
+**What Trusty enables.** Every agent carries parallel audit chains — one
+per dimension being monitored (attention, uncertainty, inter-agent
+interaction, input context, output action). Any drift, hallucination, or
+off-policy behavior shows up as a chain break on the relevant dimension.
+You get an audit trail not just of agent outputs but of agent *state*.
+
+**Who benefits.**
+- AI platform operators — ship AI into regulated markets they currently
+  cannot enter.
+- Enterprises adopting AI — get an accountability layer their compliance
+  teams will accept.
+- Regulators — gain a standard way to inspect agent behavior after the fact.
+- AI safety and alignment researchers — have a production-grade substrate
+  for behavioral monitoring.
+
+---
+
+## 7. Threadkeeper
+
+**What Threadkeeper is.** Threadkeeper is Eric's desktop knowledge /
+conversation-capture application. It records, organizes, and reasons over
+long-running threads of work — transcripts, notes, decisions, research
+artifacts — across sessions and projects.
+
+**The problem Threadkeeper has.** A knowledge tool is only as trustworthy as
+the history it presents. If a user, a sync bug, or an automated process can
+silently rewrite past entries, the tool cannot be used for anything where
+"what was said and when" matters — legal matters, investigative work,
+research that will later be published, client-facing deliverables, or
+regulated professional practice.
+
+**What Trusty enables for Threadkeeper.**
+- Every captured entry is sealed on write. The historical record is
+  demonstrably the record that was originally created.
+- Any external party — a client, a court, a reviewer — can be handed a
+  Proof Bundle and verify the thread's integrity independently.
+- Cross-thread references (entry A cites entry B at a specific point in its
+  history) are themselves tamper-evident, so citation integrity is
+  preserved.
+- When AI assistance is layered into Threadkeeper (summarization,
+  reasoning, agentic workflows), the agent's activity rides the same chain
+  — so "what the assistant did, when, and why" is part of the same audit
+  trail as the human-authored content.
+
+**Who benefits inside the Threadkeeper story.**
+- Lawyers, consultants, and advisors — deliverables built on Threadkeeper
+  are audit-ready and defensible by default.
+- Investigators and journalists — source material and working notes carry
+  provable provenance.
+- Researchers — lab notebooks, experiment logs, and authorship trails are
+  tamper-evident.
+- Solo professionals and small firms — get enterprise-grade evidentiary
+  rigor without enterprise-grade tooling cost.
+- Anyone handing work product to a skeptical third party — the product
+  ships with its own proof of integrity.
+
+**Why this matters commercially.** Threadkeeper plus Trusty is the
+reference implementation of "knowledge work that proves itself." It is the
+most visible, user-facing demonstration of the Trusty substrate, and it is
+the story that translates the technology into something non-technical
+buyers intuitively understand.
+
+---
+
+## The Common Thread
+
+Trusty is deliberately narrow — a commodity audit layer, not a platform.
+Low per-unit cost, high margin, easy to embed anywhere trustworthy data
+matters. Once embedded, every application layer on top — carbon credits,
+compliance monitoring, agent accountability, data marketplaces,
+Threadkeeper — rides the same audit spine and inherits the same
+evidentiary guarantees.
+
+The consistent benefit across every use case: **the burden of trust shifts
+away from the operator and onto the math.** Customers stop having to
+convince counterparties their logs are honest, because the logs prove
+themselves.