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Documentation Index

Fetch the complete documentation index at: https://docs.ixo.world/llms.txt

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Most organisations are not blocked because they lack AI tools. They are blocked because people and agents operate on conflicting information, decisions are disconnected from evidence, workflows break across organisational boundaries, automation cannot be trusted with real-world consequences, and nobody can clearly prove what happened, who acted, or whether outcomes were achieved. The IXO Stack — IXO Protocol as the verifiable state layer and the Qi Intelligent Cooperating System as the human–AI cooperation layer — addresses that class of problem. It is not chat-based AI automation; it is outcome-driven coordination infrastructure for humans, AI agents, organisations, data systems, governance processes, and financial systems operating against shared, verifiable state.

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The two layers

IXO defines what is true and verifiable. Qi defines how intelligent actors cooperate over that state inside real workflows.

IXO: the verifiable state layer

Identity, claims, evidence, credentials, governance, programmable coordination, payments, and outcomes — modelled as cryptographically verifiable state on the IXO Graph.

Qi: the intelligent cooperating system

Humans and AI agents working together over IXO-backed state through shared context, declared interfaces, governed workflows, and inspectable actions.
A useful rule: use IXO to define, verify, persist, or query the shared state of reality; use Qi to interpret, reason, decide, automate, or act on that reality.

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What IXO records

IXO maps real-world systems into cryptographically verifiable digital state. Typical state transitions include:
  • a carbon reduction event
  • a youth skills credential
  • a pathogen detection signal
  • a delivery confirmation
  • a governance decision
  • a machine telemetry reading
  • an evaluation outcome
  • an AI-generated recommendation
These are recorded as reality-backed state, not spreadsheets, screenshots, or unverifiable API logs. See IXO Protocol for the on-chain primitives and IXO Graph for the shared, queryable map.

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What Qi coordinates

Qi creates persistent cooperative environments where context is shared, memory persists, authority is explicit, actions are governed, and outcomes are verifiable. It is designed around intent, shared state, flows, capabilities, and outcomes — moving teams from generating AI outputs to producing accountable outcomes. See Qi Intelligent Cooperating System.

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Core building blocks

These are the four building blocks every reader should recognise before going deeper.
Humans, AI agents, applications, and workflows operate against the same evolving source of truth. Shared state is synchronised with conflict-free replicated data types (CRDTs) so multi-party collaboration does not require a centralised authority. It produces continuity, coordination, accountability, durable memory, and explainability across actors.Read more: Core concepts — state, data, context, and action.
A POD (Programmable Organisational Domain) is a governed cooperation environment — a team, company, project, field operation, supply chain, public health response, financing facility, or research collaboration. Every POD has identity, governance, shared memory, verifiable history, programmable permissions, and financial coordination primitives. PODs are the operational trust boundary for AI-enabled organisations.Read more: IXO PODs. Hands-on: Build a POD.
Qi Flows coordinate work between humans and AI agents. Flows are state-driven, governance checkpoints are programmable, humans remain in the loop, and evidence and outcomes are first-class objects. A Flow can orchestrate AI services, request evaluations, trigger payments, issue credentials, update governance state, coordinate field operations, manage disputes, and route work dynamically — embedded directly into collaborative workspaces, not separate orchestration dashboards.Hands-on: Build a Flow.
An Agentic Oracle is not just a model endpoint. It is a governed economic actor with identity, permissions, policies, payment mechanisms, reputation, verifiable execution records, and evaluatable outcomes. Examples include document evaluation, carbon verification, epidemiology, accounting, legal review, and sensor anomaly detection agents. Every action can be authorised, audited, evaluated, disputed, and settled.Read more: Agentic Oracles and Oracle architecture. Evaluation model: Claim evaluation protocol.

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Trust architecture

The trust architecture is what makes intelligent automation safe for consequential work.
IXO uses Decentralized Identifiers (DIDs) to establish cryptographically verifiable identity for people, organisations, agents, devices, workflows, and governance domains. This enables portable trust, sovereign identity, verifiable delegation, and cross-platform interoperability.The system aligns with W3C Verifiable Credentials, W3C DID Core, and W3C Data Integrity. See Identity and credentials.
Qi uses object-capability security for fine-grained authorisation. Permissions are explicit, delegated, time-bound, revocable, and scoped to intent and resources, so organisations can safely authorise agents to access systems, perform actions, operate tools, and coordinate with other agents — without granting blanket control.Capability delegation patterns are informed by UCAN and ZCAP-LD. See Authentication, Session keys, and Authz.
Collaboration and shared state are protected with end-to-end encryption so platform operators cannot inspect private operational data, organisations retain sovereignty over their information, and AI cooperation occurs within controlled trust boundaries.Secure coordination is built on the Matrix Protocol. See IXO Matrix.
Outcomes — evidence, evaluations, approvals, causal reasoning, financial settlement, governance decisions — become part of a durable, verifiable audit graph. Organisations can then automate trust, finance verified outcomes, coordinate across institutional boundaries, evaluate AI performance, and improve decision quality over time.Read more: Claim evaluation protocol and Digital MRV.

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Typical deployment layers

A production IXO + Qi deployment composes several layers, each with a canonical home in the docs.
LayerPurposeCanonical reference
IXO verifiable stateIdentity, claims, governance, settlementIXO Protocol
Graph substrateShared, queryable map of entities and relationshipsIXO Graph
POD runtimeOrganisational cooperation environmentsIXO PODs
Qi Flow engineHuman–AI workflow coordinationQi Intelligent Cooperating System
Agentic OraclesAI services and accountable automationAgentic Oracles
Matrix federationEncrypted collaboration and shared documentsIXO Matrix
Indexing and queryRead-side access to protocol stateIXO Blocksync
Endpoints and networksChain IDs, RPC, REST, Matrix base URLsNetworks and endpoints
External integrationsERP, CRM, sensors, APIs, AI modelsIntegrations

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Why this matters

AI systems can increasingly reason, plan, operate tools, execute workflows, and coordinate actions. But intelligence without trust creates systemic risk. The next layer of infrastructure must answer:
  • Who authorised this action?
  • What evidence supports this decision?
  • Which agent performed the work?
  • Can the outcome be independently verified?
  • Can governance intervene?
  • Can financial settlement be automated safely?
IXO and Qi are designed to answer these questions at infrastructure level. The internet connected information; this stack connects accountable action — for trusted cooperation, verifiable outcomes, governed AI systems, and programmable institutions.

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What you can build

Outcome finance

Carbon markets, impact finance, youth livelihoods, development finance, and grant disbursement systems that move value only when outcomes are evidenced and verified.

Digital MRV

Measurement, reporting, and verification systems with cryptographic trust, automated evaluation, and verifiable certification.

AI-native operations

AI-assisted accounting, public health coordination, digital compliance, supply chain verification, and scientific collaboration with governed AI delegation and verifiable execution.

Sovereign collaboration

Federated research, public–private coordination, regulated data exchanges, and decentralised service marketplaces with sovereign data ownership and interoperable identity.
See What you can build for a fuller list of build paths with first-step guides.

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Design principles

Humans stay in the loop for governance, policy, accountability, oversight, escalation, and strategic judgement. AI systems augment coordination capacity. They do not replace institutional responsibility.
Assertions are insufficient. The system must support evidence, provenance, cryptographic verification, reproducibility, evaluation, and dispute resolution.
Organisations fail when coordination fragments. Shared verifiable state is the coordination substrate for people, agents, systems, and institutions.
The value of AI is not generated by conversations. It is generated by decisions, coordination, execution, and measurable outcomes.

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Frequently asked questions

Partially. Blockchain is used where durable public verification and settlement are necessary. Most operational collaboration occurs off-chain using encrypted shared state. The architecture balances sovereignty, scalability, privacy, interoperability, and auditability. See IXO Protocol and IXO Matrix.
No. IXO and Qi integrate with existing CRMs, ERPs, AI platforms, databases, identity providers, messaging systems, and analytics systems. The goal is trusted coordination across systems, not replacement. See Integrations and Model Context Protocol (MCP) servers.
Yes. The architecture is designed around sovereign identity, end-to-end encryption, federated infrastructure, explicit permissions, and portable trust. See Domain privacy and IXO Matrix.
Yes — within governed trust boundaries. Agents can evaluate, coordinate, classify, generate, monitor, trigger workflows, and propose actions. Sensitive operations can require approvals, evaluations, multi-party authorisation, policy enforcement, and human oversight. See Agent evaluations and Claim evaluation protocol.

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Where to go next

Act on Reality

Outcome-first positioning and a short verified-claims walkthrough.

Core concepts

Vocabulary and mental models for entities, claims, evidence, state, and cooperation.

What you can build

Pick a first POD, Flow, Blueprint, Oracle, asset, or Market.

Developer overview

SDKs, APIs, and implementation entry points.

Glossary

Short definitions of IXO and Qi terms.

Product and SDK map

Which surface owns what across the stack.