The Data and AI Solutions Fabric playbook.
A single guide to understand, assess and start. It begins with the fabric (data ready, organization and agents, decisions with proof of effect) and shows how knowledge becomes operation, with governance from the design.
One-minute summary
- What it is
- A fabric that prepares the data, decides with authority, executes with a mandate and measures the effect. Delivered as software, with people where the decision requires.
- What sustains it
- Three capabilities (Data Ready, Organization and Agents, Decision Intelligence) in one environment with shared controls: identity, costs, security, governance, audit and operation.
- How it is governed
- Ten governance dimensions and twelve control stations; each case defines the ones it requires. Every act leaves a receipt, including what was denied.
- How it starts
- With one decision: six entry doors and a ladder of offers, with an exit criterion at each step.
The market now asks for results. We deliver what makes them verifiable.
The service is delivered by software, with people where the decision requires it. Every delivery ends with evidence, and gains are declared only after they are measured.
| What the market is asking for | What we deliver | Evidence of delivery |
|---|---|---|
| The question is no longer whether a company has AI, but what results it shows. | We start with the decision and the baseline, before any agent. | A baseline with source, formula, owner and frequency. |
| More agents and more interactions do not mean more value. | We measure the whole flow, people and agents together: every action has an owner. | A receipt for every action: who requested it, who approved it and the result. |
| Before investing, you need to know who approves, who pauses and when to review. | Mandate, authority limits and a stop condition defined for the case, using the ten-dimension stack. | A recorded mandate, review by a different person and an auditable stop. |
| A project must state when to continue and when to stop. | Each step ends with a continuation decision: proceed, correct, expand or close. | A gate with the evidence of the step and the proposal for the next one. |
We do not price by outcome or promise gains before measuring. What we deliver is the ability to verify the result of each decision.
The fabric: from data to value capture.
The cycle is the same in every case. The scope defines which capabilities come in and how they work together.
Prepare
Purpose, context and trusted data.
Decide
Options, criteria and authority.
Execute
People and agents with a mandate.
Measure and learn
Observed effects and next steps.
- Data Ready
- Data fit for use. Data products with meaning, provenance, quality and ownership. Context for the decision.
- Organization & Agents
- Coordinated work. People, agents, knowledge and tools organized through roles, mandates and boundaries.
- Decision Intelligence
- Decisions and outcomes. Options, actions, deadlines and effects tracked through to outcome review.
Governance in the design, not at the end.
Controls follow the cycle, from data entry to the review of results. A person sets the authority level; the agent executes within the limit and the case returns to a person when it needs a decision.
- Ownership
- A person is accountable for the data, the agent and the decision.
- Authority
- Roles, access and mandates define permitted action.
- Intervention
- Reviews, limits and stopping conditions are defined for the case.
- Evidence
- Records connect what was authorized, done and observed.
The factory’s 12 stations
- AI model
- Select the model and record purpose, data destination and owner.
- Data product
- Define meaning, provenance, quality, access and owner.
- Memory
- Establish curation, change authorization and retention.
- Agent
- Attach identity, ownership and a mandate to its work.
- Supervision
- Separate proposal, review and approval according to risk.
- Connections
- Authorize tools and delegation within scope.
- Security
- Define blocking rules and information protection.
- Stopping
- Define when to stop and who may authorize resumption.
- Quality
- Test behavior and review changes before use.
- Records
- Track actions, owners and authorizations.
- Observation
- Review progress, consumption, exceptions and intervention needs.
- Outcome
- Compare observed and expected effects to guide the next cycle.
Knowledge becomes operation: Service-as-Software.
What Arcogi knows how to do is delivered as software, with people where the decision requires. Four layers, from practice to operation.
BoK
How to think and practice: the EDAVEN method and doctrine.
Cookbooks
Optional accelerators: the BoK’s knowledge by sector, function and journey, on top of the hub.
Services
Implementation with the CoE, as contracted.
EDAVEN SaaS
Data Ready, Organization and Agents and Decision Intelligence, as the case requires.
17 cookbooks: 6 by sector, 5 by journey and 6 by function. See the cookbooks
Start with one decision.
Six entry doors start from what the client is facing, and a ladder of offers advances with an exit criterion at each step.
Decision map
The company says: “I don’t know where to start with AI.”
Inventory and the priority decision.
Differentiating decision
The company says: “I already know which decision I want to solve.”
Decision in operation and effect measured.
Govern the AI you already have
The company says: “We have Cortex, Copilot, AI in the ERP, and no one controls it.”
Third-party AI under control.
Agent factory
The company says: “I want my team to build agents, with governance.”
Agents with an owner and a mandate.
Data ready
The company says: “Nobody trusts the numbers.”
Data products with a contract.
Agents in your ecosystem
The company says: “My people want to use agents, in a controlled way.”
Adapters and connectors with Snowflake, Databricks, AWS, GCP, Microsoft and others, per project.
What this playbook does not claim
- We do not price by outcome nor promise gains before measuring.
- Synthetic proof is proof of control, not a market result.
- Recipes guide adaptation and supervised implementation; results depend on the integrations, the data and the criteria agreed in the project.
- NIST AI RMF, OECD and LGPD guide the design; they are not certification or compliance.
- The screens show a demonstration environment with synthetic data. Available controls and capabilities are verified in the scope of each engagement.
Which part of your operation needs to move forward?
Start with a recurring decision or an outcome that matters. Together we identify the data, people and first capability required.