An introduction to the platform — what it is, how it is built, and what you decide.
Before we start
What we will cover.
One
What Cygnus is — and what it is not
Two
The five layers underneath the chat window
Three
The product, working
Four
The decisions that stay with your institution
Most of the platform is invisible from the outside. That invisible part is what this session is about.
In one sentence
Cygnus is a private, sovereign AI environment for an institution.
Your people use AI the way they already know how. The institution keeps control of the data, the permissions, the rules, the models and the cost.
Your people
Accessible only through corporate mailboxes.
Your knowledge
Connected to the systems you already use.
Your rules
Permissions, limits, and a full record.
Your infrastructure
Your own servers, or a private space built for you.
To avoid confusion
What Cygnus is not.
Not a chatbot
Chat is one application sitting on top. The platform is everything underneath it.
Not a search engine
It does not build an index of documents. It builds a map of the things your institution works with.
Not an AI model
Models plug into it and can be exchanged. Cygnus is what surrounds them.
Not a system you move to
Nothing is migrated. It sits underneath what you already run.
The visible part
What your people see.
chatapplication
.
cbainstitution
.
amdomain
Deployed on a subdomain of your own domain — your name, your address, your certificate. A familiar chat window and user experience. Sign-in through corporate mailboxes. A choice of model and how deeply to search. Nothing to learn.
This is the whole of what an employee experiences. It is a small part of what Cygnus is.
The rest of it
Five layers. Your people see one.
Layer 2 · Agents
Seven decisions, made by you.
Agent
A governed reader of your knowledge
Seven things you set, explicitly
Knowledge it may read
one or more knowledge bases — and nothing else
The topics it will answer on
the frame — anything outside it is declined
The model it runs on
cloud, or private and inside your building
Instructions
how it should behave, in your words
Tools it may call
quick lookup, or a deep search
Grounding mode
strict — answer only from knowledge, or say so
Usage cap
how much it is allowed to spend
Everything an agent may do is set in advance — including the topics it will answer on, and whether it may answer from anything other than your own knowledge.
The same answers you can trust. Only the capability and the cost change.
Take one model out, put another in. Nothing else about the agent changes.
Layer 3 · Security
The same question, two answers.
One identical question, asked by two employees
“What did the last supervisory decision on this institution require?”
Head of Supervision
Supervision division
All staffSupervisionLegal
Supervisory decisions
Legal & regulation
Statistics
Board papers
A complete answer, citing the decision, the legal act it rests on, and the board paper behind it.
Analyst
Statistics division
All staffStatistics
Supervisory decisions
LOCKED
Legal & regulation
Statistics
Board papers
LOCKED
“I don't have access to that.” The supervisory record is never retrieved, so it can never leak into the wording.
The AI is only given what the person may see. It cannot mention what it never received.
Two people ask the same thing. The AI reads only what each of them is allowed to read, so the answers differ.
Layer 4 · Knowledge
Connect almost anything.
Where knowledge comes from
Public websites
read and re-read on a schedule
Any system, through its API
a REST connection
Files uploaded directly
a document at a time
Whole folders and shares
a directory at a time
Databases and registries
structured records
Mail, intranet and wikis
everyday working material
If it can be read, it can be connected. Nothing is migrated.
Your ontology
one per knowledge base — the map of the things and relationships your institution actually works with
Governed knowledge
Regulationentity
Decisionentity
Institutionentity
Personentity
Indicatorentity
Publicationentity
… and every relationship between them.
Websites, APIs, uploaded files, whole folders, databases, mail. If it can be read, it can be connected — and it stays where it is.
Layer 4 · Knowledge
It keeps itself up to date.
01
Read
parse and normalise the source document
02
Identify
find the things your ontology defines
03
Extract
resolve attributes and relationships
04
Commit
write the facts and links into the graph
It never stops
Sources are re-read on the schedule you set. New documents enter the graph on their own. Nobody maintains the knowledge base.
Why this matters for privacy
Every stage is built to run on open-weight models. The entire pipeline — the part that reads every document you own — can run inside your own building.
In one live deployment
14,113
documents
0
people maintaining it
Nobody is given the job of keeping it current. And the part that reads all your documents can run inside your own building.
Layer 4 · Knowledge
A map of what the institution knows.
Entity types
EconomicIndicator
Publication
BoardDecision
Organization
FinancialInstitution
StatisticalSeries
+ 14 more
26,000
entities
47,000
relationships
And it does not only find
Analyse
summarise a body of decisions, compare documents, show what changed
Reason
connect facts across sources to answer what nobody wrote down
Act
hand routine work to an agent that follows the same rules
Not a search box — a map of what your institution works with. And agents do not only search it.
Where it runs
Public cloud, private cloud, or your own infrastructure.
Public cloud
Azure, AWS and others
Managed for you
The fastest way to start. No equipment, and nothing to prepare.
Private cloud
Focused on Firebird
An isolated environment
A separate network of your own, joined to yours. Not shared with anyone.
Your own infrastructure
Your servers, your data centre
Inside your building
Everything, including the models, on machines you own and control.
Private AI infrastructure is not a condition of starting. It is a decision you make later.
Who does what
Three companies, three roles.
Cygnus
The platform
The product, its engineering and its direction.
VOLO
Integration partner
Connects it to your systems, configures it, and supports it.
Firebird
The infrastructure
Computing power, hosting, and private environments.
The software, the people who fit it to your institution, and the place it runs.
The decisions that stay with you
Five things only your institution can decide.
Which knowledge each group of people may reach — and which stays closed, file by file.
Which models you allow, and whether they run in the cloud or inside your own building.
How much may be spent — weekly and yearly, per team and per person.
Which rules the application enforces, and what it tells someone when it stops them.
Where the whole thing runs.
Everything else is engineering. These five are governance, and they remain yours.
Cygnus
The chat window is the part everyone sees.
What makes it safe to use is the four layers underneath it — and the decisions that stay with you.