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EU  AI  Act  –  GPAI  Code  of  Practice
Incorporating  Bria  Models  In  European  Union
Updated:  January  6,  2026

List  of  Documents
1.  Public  Notice:  Bria  AI  Compliance  with  EU  AI  Act  "GPAI  Code  of  Practice"  Requirements 2.  Public  Notice:  Bria  AI  Compliance  with  the  EU  AI  Act 3.  Public  Summary  of  Training  Content  for  General-Purpose  AI  models 4.  Bria  Copyright  Policy

Letter  to  Customers
Dear  Valued  Customer,
As  you  intend  to  use  and/or  integrate  our  Bria  3.2  model,  we  want  to  ensure  you
have

all

the

information

needed

to

successfully

incorporate

our

AI

model

into

your

systems.

This

Model

Documentation

Form

is

part

of

our

commitment

to

transparency

and

compliance

related

to

our

development

of

General-Purpose

AI

models,

in

compliance

with

some

specific

provisions

of

the

EU

AI

Act,

which

came

into

effect

in

August

2025.

Why  are  we  sharing  this  information?
As  a  downstream  provider  integrating  Bria's  general-purpose  AI  model  into  your
systems,

you

need

comprehensive

technical

details

to:

●  Understand  our  model's  capabilities  ●  Meet  your  own  compliance  obligations  under  the  AI  Act  ●  Build  trust  with  your  end  users  through  transparency
What  is  included  as  part  of  this  form?
This  documentation  provides  detailed  information  about  our  model's  technical
specifications,

training

methodology,

licensing

terms,

and

acceptable

use

policies.

We've

organized

the

information

to

help

you

quickly

find

what

matters

most

for

your

specific

use

case,

whether

you're

building

creative

tools,

enhancing

workflows,

or

developing

new

AI-powered

products.

Our  Commitment  to  Partnership
Bria  has  signed  the  EU's  General-Purpose  AI  Code  of  Practice,  demonstrating  our
dedication

to

responsible

AI

development.

This

Form

includes

all

the

information

to

be

documented

as

part

of

Measure

1.1

of

the

Transparency

Chapter

of

the

Code

of

Practice.

By

providing

this

detailed

documentation

proactively,

we're

not

just

meeting

regulatory

requirements,

but

we

are

supporting

your

success

and

ensuring

our

partnership

is

built

on

transparency

and

trust.

If  you  have  questions  about  any  aspect  of  this  documentation  or  need  additional
technical

details

for

your

integration,

please

don't

hesitate

to

reach

out

to

our

team.

We're

here

to

support

your

AI

journey

every

step

of

the

way.

Best  regards,
Bria  Team

1.  Public  Notice:  Bria  AI  Compliance  with  EU  AI  Act
"GPAI

Code

of

Practice"

Requirements

We  are  pleased  to  announce  that  Bria  has  successfully  complied  with  the  Code  of
Practice

Requirements

under

the

EU

AI

Act

and

is

now

making

available

its

Copyright

Policy

and

Public

Summary

of

Training

Content

as

required

by

law.

We

have

also

gone

beyond

our

legal

responsibilities

and

published

the

comprehensive

Model

Documentation

Form

-

a

detailed

technical

specification

document

that

we

are

only

required

to

provide

to

our

downstream

customers

upon

request,

but

which

we

are

now

making

publicly

available

to

demonstrate

our

unwavering

commitment

to

transparency

and

industry

leadership.

At  Bria,  we  believe  that  innovation  and  responsibility  go  hand  in  hand.  As  a
leading

generative

AI

company

building

rights-cleared,

attribution-based

models

for

enterprise

use,

we

are

proud

to

be

among

the

first

to

demonstrate

full

compliance

with

the

European

Union's

groundbreaking

AI

Act

requirements.

What  did  Bria  implement:
✓  Transparency  Commitment :  We  have  successfully  implemented  the
transparency

commitments

of

the

EU's

General-Purpose

AI

Code

of

Practice,

demonstrating

our

dedication

to

responsible

AI

development

and

transparent

business

practices.

✓  Public  Documentation  Available :  Our  comprehensive  Public  Summary  of
Training

Content

is

now

publicly

accessible,

providing

detailed

information

about

our

model

training

data,

sources,

and

compliance

measures.

✓  Comprehensive  Copyright  Policy :  Bria  has  implemented  and  published  a
comprehensive

Copyright

Policy

that

establishes

our

framework

for

copyright

compliance

in

AI

development,

including:

●  Exclusive  use  of  commercially  licensed  training  data  ●  Proprietary  attribution  technology  for  fair  compensation  to  data  licensors  ●  Robust  technical  safeguards  to  prevent  copyright-infringing  outputs  ●  Rigorous  due  diligence  procedures  for  third-party  data  sources  ●  Accessible  communication  channels  for  rightsholder  concerns
Access  Our  Compliance  Documentation
You  can  now  access  our  Copyright  Policy,  Public  Summary  of  Training  Content,
and

detailed

Model

Documentation

Form,

which

provide

comprehensive

information

about:

●  Training  data  sources

●  Technical  specifications  and  model  capabilities  ●  Copyright  compliance  policies  and  procedures  ●  Data  processing  methodologies  and  safeguards
Our  Commitment  to  Responsible  AI
This  compliance  milestone  reflects  our  core  belief  that  generative  AI  can  be  both
innovative

and

ethical.

Through

our

proprietary

attribution

technology

and

exclusive

use

of

licensed

training

data,

we

continue

to

demonstrate

that

responsible

AI

development

is

not

only

possible

but

commercially

viable.

We  invite  you  to  explore  our  compliance  documentation  and  discover  how  Bria  is
setting

new

standards

for

trustworthy

AI

development

in

the

European

market

and

beyond.

For  questions  about  our  AI  Act  compliance  or  to  access  our  documentation,
please

get

in

touch

with

us

at

legal@bria.ai
.

Effective  Date:  September  1st,  2025

Summary  of  Training  General-Purpose  AI  Models
Required  by  Article  53  (1)(d)  of  Regulation  (EU)  2024/1689  (AI  Act)
Provider  Information
Field  Information
Provider  name  and  contact  details  Bria  Artificial  Intelligence  Ltd.
Authorised  representative  name  and  contact  details
Vered  Horesh  at  legal@bria.ai
Model  Information
Field  Information
Versioned  model  name(s)  Bria  3.2
Model  dependencies  N/A
Date  of  placement  of  the  model  on  the  Union  market
June  10,  2025
Training  Data  Overview
Modality  Training  Data  Size  Types  of  Content
Text  Up  to  19.2  billion  tokens  Image  data  enrichment
Image  479  million  images  Fully  licensed  images  provided  by  Bria  data  partners
Data  Characteristics
Field  Description
Latest  date  of  data  acquisition/collection  for  model  training
June  2025
Description  of  linguistic  characteristics
N/A

Other  relevant  characteristics
Bria's  training  data  is  sourced  exclusively  through  commercial  licensing  agreements  with  data  partners  globally,  ensuring  diverse  representation  across  cultures,  ethnicities,  ages,  genders,  and  geographical  locations.  The  dataset  maintains  balanced  coverage  across  domain  categories  while  incorporating  content  from  multiple  international  markets.  All  training  data  consists  of  human-created  content  with  explicit  commercial  use  releases,  deliberately  excluding  public  figures,  harmful  materials,  or  copyrighted  fictional  characters.
2.  List  of  Data  Sources
2.1  Publicly  Available  Datasets
Q:  Have  you  used  publicly  available  datasets  to  train  the  model?
A:  No
Fully  licensed  images  provided  by  Bria  data  partners  through  commercial
licensing

agreements

with

rightsholders

globally.

All

training

data

is

sourced

exclusively

through

transactional

commercial

licensing

agreements

that

explicitly

authorize

the

use

of

licensed

content

for

generative

AI

model

training

purposes.

Each

licensing

agreement

includes

comprehensive

warranties

and

representations

from

data

licensors

confirming

their

full

legal

right,

title,

and

authority

to

license

the

data

objects

and

grant

the

rights

necessary

for

AI

training

applications.

2.2  Private  Non-Publicly  Available  Datasets  Obtained  from  Third  Parties
2.2.1  Datasets  Commercially  Licensed  by  Rightsholders  or  Their  Representatives
Question
 Answer
Have  you  concluded  transactional  commercial  licensing  agreement(s)  with  rightsholder(s)  or  with  their  representatives?
Yes
If  yes,  specify  the  modality(ies)  of  the  content  covered  by  the  datasets  concerned
Image
2.2.2  Private  Datasets  Obtained  from  Other  Third  Parties
Question
 Answer

Have  you  obtained  private  datasets  from  third  parties  that  are  not  licensed  as  described  in  Section  2.2.1?
No
General  description  of  non-publicly  known  private  datasets  obtained  from  third  parties
All  content  is  sourced  from  its  rightsholders  or  their  authorized  representatives  who  have  obtained  all  necessary  model  releases,  property  releases,  and  intellectual  property  clearances.
2.3  Data  Crawled  and  Scraped  from  Online  Sources
Q:  Were  crawlers  used  by  the  provider  or  on  behalf  of?
A:  No

2.4  User  Data
Question  Answer
Was  data  from  user  interactions  with  the  AI  model  (e.g.  user  input  and  prompts)  used  to  train  the  model?
No
Was  data  collected  from  user  interactions  with  the  provider's  other  services  or  products  used  to  train  the  model?
No
2.5  Synthetic  Data
Note:  According  to  the  AI  Office's  instructions,  this  Section  does  not  refer  to  the
use

of

AI

models

to

clean

or

enrich

data

(e.g.,

AI-generated

metadata

to

enrich

or

modify

a

dataset,

such

as

creating

text

descriptions

of

images).

Bria

does

use

captions

generated

with

third-party

AI

models

for

enrichment

of

its

data.

Q:  Was  synthetic  AI-generated  data  created  by  the  provider  or  on  their  behalf  to
train

the

model?

A:  No
2.6  Other  Sources  of  Data
Q:  Have  data  sources  other  than  those  described  in  Sections  2.1  to  2.5  been
used

to

train

the

model?

A:  No

3.  Processing  Aspects
3.1  Respect  for  the  Reservation  of  Rights  from  the  Text  and  Data  Mining
Exception

or

Limitation

Question  Answer
Are  you  a  Signatory  to  the  Code  of  Practice  for  general-purpose  AI  models  that  includes  commitments  to  respect  reservations  of  rights  from  the  TDM  exception  or  limitation?
Yes
Describe  the  measures  implemented  before  model  training  to  respect  reservations  of  rights  from  the  text  and  data  mining  (TDM)  exception  or  limitation
No  data  scraping  is  performed
3.2  Removal  of  Illegal  Content
General  Description  of  Measures  Taken:
Bria's  training  data  sourcing  methodology  inherently  prevents  illegal  content
inclusion

through

exclusive

use

of

commercially

licensed

datasets

obtained

from

verified

professional

data

partners

and

established

image

bank

provi

4.  Bria  Copyright  Policy
Updated  September  2025
4.1.  Copyright  Compliance  Framework  at  Bria
Our  commitment  to  copyright  compliance  is  fundamental  to  our  responsible  AI
development.

We

recognize

that

true

accountability

in

AI

requires

rigorous

adherence

to

intellectual

property

rights

and

legal

standards.

Our  copyright  policy  reflects  our  core  principles:
●  Respecting  rightsholders  ●  Ensuring  full  legal  compliance  ●  Maintaining  the  highest  standards  of  ethical  AI  development  ●  Providing  equitable  compensation  to  all  data  licensors  through  our
proprietary

and

patented

algorithmic

attribution

technology

that

measures

and

rewards

each

contributor's

impact

on

generated

content

This  document  outlines  our  comprehensive  approach  to  copyright  compliance
for

our

general-purpose

AI

models

placed

on

the

market.

We  have  developed  this  policy  to  demonstrate  our  commitment  to:
●  Fully  complying  with  laws  and  regulations  on  copyright  and  related  rights,
specifically

Article

53(1)(c)

of

the

EU

AI

Act,

and

Article

4(3)

of

Directive

(EU)

2019/790

on

copyright

and

related

rights

in

the

Digital

Single

Market
 ●  Identifying  and  respecting  the  rightsholder's  reservations  of  rights  ●  Utilizing  state-of-the-art  technologies  for  copyright  protection  -  ensuring
all

of

our

models

are

trained

only

on

fully

licensed

training

data
 ●  Being  committed  to  advancing  AI  technology  while  adhering  to  principles
that

prioritize

societal

benefit

and

accountable

development

Our  approach  goes  beyond  mere  legal  compliance.  It  represents  an  intrinsic
commitment

to

integrity,

transparency,

and

responsible

innovation

in

our

AI

models

development

and

deployment

processes.

By  successfully  building  high-quality  models  through  sustainable  data
partnerships,

Bria

demonstrates

that

responsible

innovation

and

respect

for

intellectual

property

are

not

only

possible

but

also

commercially

viable.

This

evidence

is

crucial

for

policymakers,

regulators,

and

courts,

showing

there

is

no

need

to

choose

between

fostering

AI

progress

and

protecting

creators.

4.2  Training  Data  Compliance  and  Verification
Licensed  Data  Use  Policy
Bria  exclusively  utilizes  commercially  licensed  training  data  explicitly  authorized
for

generative

AI

model

training.

We

maintain

comprehensive

documentation

and

records

of

all

of

our

licensing

agreements

and

authorizations

provided

to

us

by

our

data

partners.

Data  Source  Verification
Our  data  licensing  process  includes:
●  Legal  verification  of  all  licensing  agreements  confirming  that:  ○  Bria  has  entered  into  valid  and  enforceable  agreements  with  all  data
licensors

that

expressly

authorize

the

use

of

licensed

data

for

generative

AI

model

training

purposes
 ○  Each  licensing  agreement  includes  comprehensive  warranties  and
representations

from

data

licensors

confirming

their

full

legal

right,

title,  and  authority  to  license  the  data  objects  and  grant  the  rights
necessary

for

AI

training

applications
 ●  Maintenance  of  detailed  data  cataloging  systems  ●  Regular  audits  of  data  source  compliance
No  Web-Crawling  Policy
Bria  does  not  and  will  not  engage  in  web-crawling  activities  or  utilize  publicly
accessible

online

content

for

model

training.

This

approach

ensures

complete

compliance

with

copyright

obligations

and

eliminates

risks

associated

with

unlicensed

content.

Rights  Reservation  Compliance
While  our  business  model  does  not  involve  web-crawling,  we  acknowledge  and
respect

rightsholder

reservations

expressed

pursuant

to

Article

4(3)

of

Directive

(EU)

2019/790

and

maintain

systems

to

identify

and

comply

with

such

reservations,

if

applicable.

4.3  Data  Partner  Compensation  and  Attribution  Framework
Fair  Compensation
We  compensate  partners  based  on  their  measured  contribution  to  generated
content,

providing

a

recurring

revenue

stream

to

data

partners.

Bria

rejects

one-time

license

deals

for

AI

training

data,

instead

implementing

a

fair

and

transparent

system

of

ongoing

compensation

that

ensures

creators

receive

a

share

of

the

long-term

value

their

work

generates

in

existing

and

future

AI

applications.

Attribution  Technology
Our  patented  attribution  technology  enables  Bria  to  bridge  the  gap  between
demand

for

synthetic

content

and

supply

of

authentic

training

data.

Each

synthetic

output

generated

by

our

models

is

attributed

to

the

original

content

creators

that

impacted

the

most

on

its

generation.

Transparency
Bria's  attribution  technology  offers  transparency  to  both  data  contributors  and
customers.

4.4  Content  Due  Diligence  for  Third-Party  Sources

Bria  maintains  comprehensive  due  diligence  procedures  for  any  content
obtained

through

third-party

providers.

We

require

all

third-party

data

providers

to:

●  Warrant  their  full  legal  right  and  authority  to  license  content  for  AI  training
purposes
 ●  Provide  comprehensive  warranties  that  all  data  licensed  is  original  and
human-created

content
 ●  Ensure  all  data  is  subject  to  legal  releases  covering  commercial  use  and  AI
training

applications

where

identifiable

persons

or

property

are

depicted
 ●  Provide  representations  confirming  non-infringement  of  third-party
copyrights,

trademarks,

or

other

intellectual

property

rights
 ●  Provide  warranties  that  content  does  not  feature  public  figures,  harmful
materials,

or

copyrighted

fictional

characters
 ●  Present  all  applicable  compliance  certifications  regarding  adherence  to  all
applicable

copyright

laws

and

regulations
 ●  Maintain  detailed  records  and  chain-of-title  documentation  ●  Be  subject  to  periodic  compliance  audits  and  remediation  procedures
Data  Procurement  and  Usage
In  addition,  Bria  maintains  the  following  processes  to  ensure  all  data  licensed  and
used

by

it

will

not

subsequently

create

any

other

harmful

implications

on

rightsholders

or

users:

Data  Quality  and  Diversity:  No  synthetic  data  is  used  for  training  our  models.  Bria
does

not

acquire

data

that

will

not

lead

to

model

quality

improvement

and

will

only

dilute

the

attribution

to

existing

partners.

Dedicated  Storage  and  Access:  Training  data  for  generally  available  models  is
stored

in

dedicated

training

accounts.

Proprietary

data

provided

by

customers

for

training

private

models

is

segregated

from

general

models'

training

data

accounts.

Access

to

proprietary

data

provided

by

customers

for

training

private

models

and

models

informed

by

customers'

proprietary

data

is

restricted

to

such

customers

and

authorized

Bria

support

for

maintenance

functions

only

with

rigorous

permissions

system.

Access

to

models

is

subject

to

periodical

penetration

tests.

Asset  Cataloging:  An  automated  pipeline  records  each  asset  in  a  dedicated
catalog,

maintaining

a

clear

link

to

its

origin.

4.5  Output  Protection  and  Copyright  Compliance

Bria  implements  robust  technical  and  policy  measures  to  prevent
copyright-infringing

outputs

from

our

general-purpose

AI

models:

Technical  Safeguards
We  employ  state-of-the-art  technical  measures  to  avoid  our  models  from
reproducing

training

content

in

an

infringing

manner,

including:

●  Advanced  content  filtering  systems  ●  Real-time  output  monitoring  ●  Regular  testing  protocols  to  verify  safeguard  effectiveness  ●  Detection  of  potential  copyright  violations  post-generation
Acceptable  Use  Requirements
Our  terms  and  conditions  explicitly  prohibit:
●  Using  models  to  generate  copyright-infringing  content  ●  Circumventing  technical  safeguards  ●  Using  our  models  to  create  any  unlawful  content
Documentation  Requirements
For  all  model  deployments,  we  provide:
●  Clear  copyright  and  acceptable-use  compliance  guidelines  ●  Explicit  prohibition  of  infringing  uses  ●  Technical  documentation  of  protective  measures
Cross-Platform  Application
These  protective  measures  apply  consistently  across:
●  Direct  model  implementations  ●  On-prem  model  integrations  ●  API  access  ●  All  other  deployment  scenarios
Monitoring  and  Enforcement
We  maintain  ongoing  oversight  through:
●  Regular  audits  of  model  outputs  ●  Compliance  verification  procedures  ●  Incident  response  protocols  ●  Continuous  improvement  of  safeguards

4.6  Rightsholder  Contact  and  Complaint  System
We  maintain  accessible  communication  channels  and  procedures  for
rightsholders

through

an

email

message

to

legal@bria.ai
,

to

submit

precise

and

substantiated

complaints

regarding:

●  Non-compliance  with  copyright  commitments  ●  Potential  infringement  concerns  ●  Rights  reservation  violations  ●  Any  other  copyright-related  matters
This  reporting  mechanism  complements  but  does  not  replace  or  limit  any  legal
remedies

available

under

Union

and

national

copyright

law.

4.7  Other  Protective  Measures
Beyond  our  comprehensive  copyright  compliance  framework,  Bria  maintains
additional

protective

measures

to

ensure

full

regulatory

adherence

and

responsible

deployment

practices

for

the

benefit

of

both

our

data

licensors

and

end

users.

These

supplementary

safeguards

reflect

our

commitment

to

establishing

industry-leading

standards

that

transcend

basic

legal

requirements

and

encompass

the

full

spectrum

of

ethical

AI

development

considerations.

Privacy  and  Data  Protection
●  We  place  strong  emphasis  on  privacy  protection  for  individuals.  We  use
human

likenesses

only

with

explicit

releases

for

commercial

use.

We

strictly

prohibit

the

use

of

public

figures'

data

in

our

models.
 ●  We  implement  robust  data  protection  measures  to  safeguard  personal
information

and

comply

with

relevant

privacy

and

data

protection

regulations.

Identity  Protection  and  Training  Architecture
No

Identity

Mapping:
 Bria's  training  datasets  are  fully  anonymized  through  the
removal

of

all

naming

and

identifying

metadata.

Our

models

are

designed

to

prevent

any

mechanism

for

linking

visual

likenesses

to

real

person

identities.

Balanced,  Multi-Source  Training  Catalog:  We  maintain  a  wide-ranging,  globally
sourced

dataset

that

deliberately

balances

input

across

creators,

contexts,

content

types,

and

personalities.

This

diversity

reduces

prominence

of

any

single

source

and

minimizes

potential

for

overrepresentation

or

unintended

memorization.

Architecture  Design:  Bria's  models  are  specifically  architected  to  learn  general
visual

patterns

rather

than

memorize

or

reproduce

specific

individuals.

Our

technical

architecture

and

sampling

methodology

inherently

discourage

identity

persistence

or

overfitting

to

any

single

visual

subject,

making

it

highly

improbable

for

even

specific

prompts

to

generate

recognizable

individuals.

Commitment  to  Diversity,  Inclusion,  and  Bias  Mitigation
●  We  actively  seek  and  incorporate  diverse  datasets  that  represent  a  wide
range

of

cultures,

ethnicities,

ages,

genders,

and

geographical

locations.

This

approach

ensures

our

AI

models

are

trained

on

a

comprehensive

representation

of

global

diversity.
 ●  Our  development  process  includes  rigorous  testing  and  refinement  to
identify

and

mitigate

potential

biases

in

our

AI

models.

We

employ

diverse

teams

of

experts

to

continuously

evaluate

and

improve

our

models'

fairness

and

inclusiveness.
 ●  We  implement  content  moderation  filters  to  prevent  the  generation  of
harmful

or

biased

content.
 ●  We  regularly  consult  with  diverse  stakeholder  groups,  including
underrepresented

communities,

to

understand

their

perspectives

and

incorporate

their

feedback

into

our

AI

development

and

deployment

processes.
 ●  Our  AI  models  are  designed  with  cultural  sensitivity  in  mind,  respecting
and

accurately

representing

various

cultural

nuances

and

contexts

in

their

outputs.
 ●  We  regularly  publish  reports  on  our  diversity  and  inclusion  initiatives,
including

the

composition

of

our

datasets

and

the

results

of

our

bias

mitigation

efforts,

to

maintain

accountability

and

encourage

industry-wide

progress.

Safety,  Mitigation  of  Misinformation  and  Harmful  Content
●  All  AI-generated  content  is  distinctly  marked  using  cutting-edge
technologies.
 ●  We  enforce  strict  guidelines  against  generating  harmful  or  offensive
content.
 ●  We  implement  measures  to  prevent  the  misuse  of  our  platform.  We  do  not
accept

any

data

that

features

public

figures

or

harmful

content,

making

it

impractical

to

use

our

models

to

generate

these

concepts.

Conclusion

This  Copyright  Policy  establishes  Bria's  comprehensive  framework  for
responsible

AI

development

through

five

core

pillars:

1.  Exclusive  use  of  commercially  licensed  training  data  with  verified  legal
authorization
 2.  Proprietary  attribution  technology  that  provides  ongoing  compensation
to

data

licensors

based

on

measured

contribution

impact
 3.  Robust  technical  safeguards  preventing  copyright-infringing  outputs  4.  Rigorous  due  diligence  procedures  for  third-party  data  sources  5.  Accessible  rightsholder  communication  channels  for  compliance
concerns

Our  approach  encompasses  additional  protective  measures  including  privacy
protection,

diversity

and

inclusion

initiatives,

bias

mitigation

protocols,

and

safety

measures

against

harmful

content

generation.

Through  our  data  partner  empowerment  and  collaboration  framework,  we
maintain

long-term

partnerships

that

create

mutual

value

while

advancing

responsible

AI

innovation.

Many  of  our  data  licensors  leverage  our  models  to  offer  their  creator
communities

and

customers

advanced

generative

AI

capabilities

under

preferred

commercial

arrangements.

This

symbiotic

relationship

strengthens

our

collaborative

ecosystem

and

delivers

mutual

value

creation

across

the

AI

development

lifecycle.

We  view  our  data  licensors  as  integral  to  our  sustainable  AI  development
approach

and

remain

committed

to

nurturing

long-term,

mutually

beneficial

relationships

that

evolve

with

the

advancing

AI

landscape

and

regulatory

environment.

Together,  we  can  create  an  AI  landscape  that  is  not  just  innovative  but  also
trustworthy,

inclusive,

and

truly

beneficial

for

all.

Contact  Information
For  questions  or  concerns  regarding  this  policy,  please  contact:
Bria  Artificial  Intelligence  Ltd.

Email:

legal@bria.ai

Website:

https://bria.ai/eu-policy

Document  last  updated:  January  6,  2026