HOW IT WORKS EMPOWERED INTELLIGENCE

See how your organization operates with the data you already have.

Reach first insights in weeks, not quarters, without replacing your systems or launching a separate IT project.

Skip to the technical details

01 Week 1-2
Context Decision defined
02 Week 3-4
Evidence Useful sources connected
03 Week 5-8
Observe Current model in use
04 Ongoing
Decide & review Run the rhythm
THE PROCESS01

First insights in weeks, not quarters. Regular reviews follow.

First, leaders define the decision and shape a model of how the organization works. We then connect the minimum useful evidence. Leaders review that evidence on a schedule the business can sustain and check what changed after each decision.

Each review produces a recorded decision and a result to check.

01-03

Visibility

Define the context, shape the model, and connect enough evidence to observe the work.

04

Review cycle

Use the company model in regular reviews. Record each decision, then check its result at the next review.

STEP ONE / CONTEXT02
STEP 01 Context

Start with the decision. Shape the model around it.

The ontology records the objects, relationships, and authority in your organization. Empowered Intelligence prepares a draft from leader context, and domain experts review every part before approval.

The approved model defines each object, its attributes, and its relationships.

Ontology approved Example
ENTITIES
|- Client |  |- name |  |- industry |  \- status: active / churned
|- Project |  |- name |  |- start_date |  \- status: planning / active / done
|- Invoice |  |- number |  |- amount |  \- status: draft / sent / paid
\- Employee    |- name    |- role    \- department
Relationships Project belongs to Client Invoice belongs to Project Invoice is assigned to Employee Employee works on Project

How modeling works

01

Name the decision

A leader identifies the question, process, and decision that matter first.

02

Shape the ontology

Empowered Intelligence drafts the objects, attributes, relationships, authority, and flows in business language.

03

Choose the evidence

The team identifies the minimum sources needed to support that decision.

04

You approve

Domain experts review the model before it becomes the basis for ongoing decisions.

Why this matters

Shared understanding

Teams use the same definitions for terms such as client, project, and invoice.

AI context

The ontology gives Empowered Intelligence the definitions it needs to interpret your questions.

Current definitions

When the organization changes, update the ontology so the company model uses the revised structure.

STEP TWO / EVIDENCE03
STEP 02 Evidence

Connect only the evidence you need first.

Empowered Intelligence can connect to data in your ERP, CRM, databases, and spreadsheets. Start with the sources needed for the first decision; the rest can wait.

Your team keeps its existing tools and working methods.

What we connect

Category
Examples
ERP & finance
SAP, NetSuite, QuickBooks, Xero
CRM & sales
Salesforce, HubSpot, Pipedrive
Databases
PostgreSQL, MySQL, SQL Server, MongoDB
Project management
Jira, Asana, Monday, ClickUp
Files
Google Sheets, Excel, Airtable
Custom
REST APIs, webhooks, custom databases

How connection works

01

Authenticate

OAuth or secure credentials. No code required.

02

Select data

Choose which tables, objects, or fields to sync.

03

Configure sync

Set the frequency to real-time CDC, hourly, or daily.

04

Validate

We check data quality and completeness.

What stays in place

  • Data remains in its current systems
  • Existing schemas remain intact
  • The connection does not require a separate IT project
  • A separate consulting team is not required
STEP THREE / OBSERVE04
STEP 03 Observe

Your company model goes live.

Current data fills the approved ontology. Ask a question in plain language and Empowered Intelligence answers from the records in the company model.

Each answer stays linked to the underlying data.

AI assistant · illustrative example
Grounded
YOU
How many invoices are stuck in verification more than 5 days?
Context attached from ontology
Invoice Flow · verification Client SLA
23 invoices stuck, worth $182K
Traceable · invoices ⋈ flow_state · BigQuery

Ask questions

  • Which projects are over budget?
  • How long does client onboarding take on average?
  • Show me all invoices stuck in approval.

Track KPIs

Describe the metric in business language. Empowered Intelligence drafts a calculation for your approval.

01

Describe

Say what you want to measure, in business language.

02

Draft the calculation

Empowered Intelligence proposes a calculation method.

03

See results

Run it on real data from the company model.

04

Approve or refine

Lock it in, or adjust until it is right.

Define processes

Save a lens for each workflow your team wants to track.

Process
What you measure
Invoice processing
Time at each stage, bottlenecks, cost of delays
Client onboarding
Handoff delays, time-to-value, drop-off points
Sales to delivery
Pipeline accuracy, resource allocation
Monitor on schedule

Empowered Intelligence calculates approved KPIs daily or weekly. The history shows when a process starts moving away from its target.

STEP FOUR / DECIDE & REVIEW05
STEP 04 Decide & review

Build a reliable decision rhythm.

At each review, leaders use current data from the company model, record the decision, and assign an owner. The next review checks the result against the target.

Use the plan, do, check, act loop at a frequency the business can sustain.

Repeated reviews show whether decisions improve the process over a quarter.

01

Set the rhythm

Choose how often to evaluate each process: daily, weekly, every two weeks, or monthly. Assign an owner to each review.

02

Review current data

Use the company model during the review so everyone works from the same numbers.

03

Check the result

Record the decision and its reason. At the next review, compare the result with the target.

TIMELINE06

From signup to first insights.

First insights arrive in weeks, not quarters. After launch, add sources and update the model as the organization changes.

Week 1-2

Context

Define the first decision, its owner, the process, and the review rhythm.

Week 3-4

Ontology

Shape the business model and have domain experts approve its meaning.

Week 5-6

Evidence

Connect and validate the minimum useful sources for the first decision.

Week 7-8

Activation

Define initial processes, create KPIs, train users, go live.

Ongoing

Evolution

Add sources and update the ontology as new processes need to be tracked.

AFTER GO-LIVE07

Keep the model current after launch.

Add more data sources

Start with critical systems. Expand as needed.

Refine the ontology

Update definitions and relationships when the organization changes.

Build new processes

Define new lenses and KPIs as questions emerge.

Add advanced analysis

Add anomaly detection and predictive insights after teams are comfortable querying the company model.

FOR TECHNICAL TEAMSARCHITECTURE

The architecture behind it.

The four layers, how Empowered Intelligence connects to your systems, the security controls and the technical stack. Written for the people who will run it.

THE FOUR LAYERS 08

The system has four connected layers.

Integration supplies source data. The ontology gives that data meaning, the twin records its current state, and the presentation layer makes it usable for action.

If one layer is missing, the results become unreliable.

INTEGRATION 09
LAYER 01

Connect your existing systems without moving the data.

Your data stays in the ERP, CRM, databases, spreadsheets, and project tools you already use. Empowered Intelligence connects to those systems where they are.

What we connect
  • Enterprise systems: ERP, CRM, HRIS
  • Databases: PostgreSQL, MySQL, BigQuery
  • Business tools: Salesforce, HubSpot, Jira
  • Custom APIs and internal systems
How it works
  • Sync with configurable frequency
  • Data validation and quality checks
  • Empowered Intelligence maps to your schema without a migration
  • Clear audit trail of every data movement
The result

Empowered Intelligence creates one consistent data layer across connected systems.

Each metric includes its source.

ONTOLOGY 10
LAYER 02

The structured vocabulary that defines your organization.

AI needs a clear model of your business. The ontology defines which objects exist, how they relate, and how they move through each process.

What ontology contains
ElementDescriptionExample
EntitiesThe things that exist in your organizationInvoice, Client, Employee, Project
AttributesProperties of each objectAmount, status, due date, owner
RelationshipsHow objects connectInvoice belongs to Client, assigned to Employee
ProcessesHow objects move through statesDraft to verified to sent to paid
How we build it
  • AI reviews schemas, sample data, and existing documentation
  • It proposes the objects and relationships in the model
  • You review the model and apply your domain knowledge
  • Empowered Intelligence builds the knowledge graph from the approved ontology
What the ontology provides
  • A shared vocabulary for your data and AI
  • Consistent definitions across different systems
  • Automatic updates after each sync
  • Defined inputs for KPIs, analysis, and AI capabilities
THE COMPANY MODEL KNOWLEDGE GRAPH
LIVING MODEL

A living model of your organization.

The ontology defines the structure. The company model fills it with current data about the objects, relationships, and events in your organization.

Nodes Specific instances, such as Invoice FV/2024/001 and Client "Company ABC"
Edges Relationships between nodes, such as an invoice belonging to a client
History Each change records the actor, value, and time
Queryable Ask questions in natural language, get answers from the graph
BELONGS_TO BELONGS_TO BELONGS_TO Client Company ABC Invoice FV/2024/001 Meeting 12.01 Email 15.01

The company model records what happened without adding interpretation.

PRESENTATION 11
LAYER 03

See the business through the processes you define.

The presentation layer turns digital-twin data into views built around the questions your team needs to answer.

Lenses (processes)

A lens defines which part of the organization to view and how to measure it.

Lens typeWhat it measuresExample
Flow processObjects moving through statesInvoice: draft to verified to paid
Activity processAggregated activities + correlationMeetings compared with sales conversion
Goal-based processDefined target + metrics + horizonIncrease retention by 10% in Q2
KPIs with AI assistance
  • Describe what you want to measure in business language
  • AI proposes a calculation method and query
  • See results on real data
  • Approve or iterate

Business users can define a KPI and inspect the calculation behind each number.

Views
Dashboards Current state at a glance
Trends How metrics change over time
Drill-downs Inspect the records behind a summary
Natural language Ask a question in plain language
ACTION 12
LAYER 04

Use the model to spot issues and act.

The action layer uses the ontology and current company data to answer questions and guide action. Each result can be traced to its source.

Anomaly detection

Get notified when a metric moves outside its expected range.

Predictive insights

Model "what if" scenarios before committing resources.

Process recommendations

Recommendations use measured bottleneck data.

Natural language queries

Ask for invoices stuck in verification for more than five days and get the matching records.

Alerts & notifications

Receive alerts for the metrics and events you choose.

How Empowered Intelligence grounds AI in company data

General AI tools do not know how your company defines its objects and processes. Empowered Intelligence supplies that context from the ontology and knowledge graph.

  • The ontology supplies your organization's vocabulary
  • The knowledge graph supplies the current state of the organization
  • Each answer can be traced to source data
  • Each answer includes reasoning you can inspect and question
ARCHITECTURE OVERVIEW 13

How Empowered Intelligence connects your systems.

Empowered Intelligence cleans and maps source data before storing it in the company model. Process views and the AI assistant use the same model.

Client systems
Where your data already lives
ERPCRMDatabasesSpreadsheetsOther systems
Data layer
Source data is cleaned, unified, and mapped Data moves through ingestion and transformation into the warehouse. Every metric is traceable to its origin.
AirbytedbtBigQuery
Company model
A living representation of your organization Graph database: nodes, relationships, and full history of every change.
Processes & KPIs
Lenses, metrics, trends, dashboards
AI assistant
Natural language, insights, alerts
PROCESS DEFINITION FRAMEWORK 14

Measure each process according to how it works.

01

Flow process

Track objects moving through defined states.

What it measures

Invoice counts by stage, time in stage, and handling time by owner.

Purchase Invoice Handling
Name Purchase Invoice Handling
Object Invoice (type: purchase)
Steps draft to verified to sent to paid
SLA max 14 days, entry to payment
02

Activity process

Correlate activities with outcomes.

What it measures

The relationship between client engagement, revenue, and specific sales activities.

Client Engagement
Name Client Engagement
Activities Meetings, Emails, Notes
Input Meetings/client/month, response time
Output Invoice value per client, upsells
Thesis More meetings correlate with higher sales value
03

Goal-based process

Set targets and track progress.

What it measures

Progress against the target, including drivers and blockers.

Q2 Retention Initiative
Name Q2 Retention Initiative
Goal Increase retention by 10%
Metrics Churn rate, NPS, support tickets
Horizon Q2 2025
SECURITY & COMPLIANCE 15

Security controls for enterprise deployment.

Data security

  • Encrypted at rest and in transit
  • Regular audits & penetration testing

Access control

  • SSO support (SAML, OIDC)
  • Role-based access control
  • Audit logs for all data access

Data privacy

  • Your data stays yours
  • Clear data processing agreements
  • GDPR-compliant data handling

Deployment options

  • Cloud, managed by EmpoweredHouse
  • Private cloud in your infrastructure
  • Hybrid with sensitive data on premises
TECHNICAL SPECIFICATIONS 16

Technical stack and performance targets.

ComponentTechnologyNotes
Supported ingestionAirbyteOptional path with 300+ connectors
Supported transformationdbtOptional, version-controlled, tested
Supported warehouseBigQueryUsed when the evidence path requires it
Graph databaseNeo4jACID compliant and optimized for graph queries
AI / LLMOpenAI / AnthropicSupports multiple model providers
APIREST + GraphQLProgrammatic access to Empowered Intelligence data
Performance targets
UI response < 500ms
API p95 < 800ms
Cache hit < 200ms
LLM Streaming in real time
FAQ17

Answers for teams evaluating Empowered Intelligence.

How long does implementation take?

First insights take weeks, not quarters. We begin with the processes that matter most to your team, then add more.

Do we need to change our existing systems?

Your systems and schemas stay in place. Empowered Intelligence connects to them without a migration or separate IT project.

What if our data is messy?

Messy data is common. We flag quality issues during connection, then use the ontology to give records consistent definitions.

Who needs to be involved?

A sponsor, a domain expert, and someone who can grant data access. No dedicated IT team required.

What about security?

Data is encrypted at rest and in transit, access is role-based, and your data stays yours.

Can we start small?

Yes. Start with two or three data sources and one or two processes. Add more after the first results are useful.

What if the AI-proposed ontology is wrong?

Every proposed ontology requires your approval. Your team can rename, remove, or reconnect elements until the model matches the organization.

How is this different from BI tools?

BI tools present dashboards. Empowered Intelligence maintains a model of the organization that you can query in plain language.

SEE IT ON YOUR DATA

See Empowered Intelligence on your systems.

In a working session, we will map the systems you use and show how Empowered Intelligence would model your organization with your data.