What is Canton Network, and what problem does it actually solve?
Canton is a network of interoperable ledgers rather than a single shared chain. Its architecture has three roles: parties, participant nodes, and synchronizers. Daml code executes on participant nodes, which host parties and synchronize state by exchanging messages through a synchronizer. Because the protocol assumes participant nodes do not trust one another, each organization normally runs its own participant node.
The property that makes it interesting to regulated institutions is sub-transaction privacy. Only eligible participants receive the data relevant to them, and within a single atomic transaction not all participants are necessarily even aware of one another. The data nodes exchange is encrypted, and the synchronizer cannot read it — it orders and routes encrypted envelopes and never decrypts payloads or validates transaction contents. Validation is done by the stakeholder participant nodes themselves.
That is a materially different privacy model from a public chain, where confidentiality depends on address obscurity and every validator sees the full transaction. It is also different from a private chain where everyone on the network sees everything. On Canton, a bank and its counterparty settle atomically without a third participant on the same network learning that the trade occurred.
The synchronizer handles two jobs: sequencing, which gives ordered and confidential communication between participants, and mediating, which coordinates transactions through a two-phase commit so a multi-party transaction either commits everywhere or nowhere. Participants can connect to multiple synchronizers, which is what makes composition across applications possible without merging them into one ledger.
How does the Daml authorization and privacy model change how you design?
In Daml, a contract is an instance of a template with signatories, observers, and choices. Signatories must authorize creation and archival. Observers are informed about creation and archival. Choice controllers — the actors — are informed about the exercise of a choice, and choice observers are informed as well. A party is a stakeholder when it is a signatory or a contract observer.
This is the design work, and it is not incidental. On an EVM chain, who can see what is a question you answer off-chain, because everything on the ledger is public. In Daml, disclosure is a property of the contract you write: putting a party in an observer clause to make a workflow convenient can hand that party visibility into a position you intended to keep private, and the mistake is silent — the code works, it just tells someone something.
So the sequence we follow is deliberate. Map the parties and what each is entitled to know. Model the workflow as contracts and choices. Set signatories, observers, and controllers against that disclosure map. Then write Daml Script tests that assert the privacy properties directly, so a later refactor that quietly widens disclosure fails a test instead of reaching production.
Divergence between the disclosure model and the intended business confidentiality is the defect class we would expect to find in an audit of an institutional Daml application, and it is the one worth engineering against from the first sprint.
What is Aegas's actual Canton track record?
We would rather answer this plainly than let you discover it on a reference call.
Our published portfolio is EVM and Solidity work: DeFi protocols, perpetuals exchanges, lending markets, tokenization platforms, and a regulated exchange with MPC custody and full KYC/KYT. We do not have a production Canton deployment in that portfolio, and we are not going to describe one that does not exist.
What we do bring is the two things a Canton build actually consumes. First, multi-party financial workflow modelling — lending, collateral management, settlement, and instrument lifecycle — which we have built and operated at real volume. Second, the off-ledger engineering that is the majority of the hours on any institutional deployment: ledger API integration, event streaming, reconciliation against core systems, admin and investor product surfaces, and reporting. That work is largely the same regardless of which ledger sits underneath, and it is where our senior .NET and TypeScript engineers spend most of their time.
The honest way to start with us is a paid, time-boxed proof of concept: we model your workflow in Daml, prove the privacy and atomicity properties you need, and hand back an architecture and integration plan that is yours whether or not you continue with us. If the PoC shows we are not the right team for your production build, you have lost weeks rather than quarters — and you still have the artifact.
When is Canton the right choice over an EVM chain?
Canton earns its complexity when three conditions hold together: the participants are known and permissioned, confidentiality between them is a hard requirement rather than a preference, and transactions have to settle atomically across more than one organization.
Interbank settlement, repo and collateral movement, fund subscription and redemption between an administrator and a distributor, and tokenized instruments where holdings must not be visible to other holders all fit that shape. In each case a public chain forces an uncomfortable choice between disclosing positions and moving the interesting logic off-chain, which defeats the point.
An EVM chain remains the better answer when you want permissionless access, deep existing liquidity, retail distribution, or an ecosystem of composable protocols to plug into. Most tokenized instruments aimed at accredited-but-broad investor bases are better served on Ethereum or an L2, where custody support is far more mature.
The failure mode we would push back on is choosing Canton for a project whose counterparties are not on Canton. The privacy and atomicity guarantees are between participants on the network. If the parties you need to settle with are not running participant nodes, you are carrying the operational cost of a permissioned network for benefits you cannot yet collect.
What does a Canton application need beyond the Daml code?
The Daml model is the smallest part of the delivery, in the same proportion we see on tokenization projects generally — usually 15–25% of the engineering effort. The rest is the system around it.
That means ledger API integration and event streaming so your existing systems learn about ledger state; reconciliation against the core ledger or register that remains your legal record; identity, KYC, and accreditation flows for the parties involved; admin consoles for approvals and exception handling; product surfaces for whoever is on the other side, whether that is an investor, a distributor, or a counterparty desk; and reporting an auditor will accept.
Node operations also have to have an owner. Each organization typically runs its own participant node, and someone has to run, monitor, upgrade, and back up that infrastructure. Whether that is your platform team, a managed provider, or us as part of a support arrangement is a decision worth making during scoping rather than the week before go-live.
How long does a Canton project take, and what does it cost?
A proof of concept — one workflow modelled in Daml, privacy and atomicity properties demonstrated, a working demo against a test topology, plus an architecture and integration plan — is typically 4–6 weeks with a small team, quoted fixed-price.
A first production application with real integration, identity flows, an admin console, a counterparty-facing surface, and reporting generally runs 5–8 months. The variance is driven almost entirely by how many external systems must be integrated and how many organizations have to agree on the workflow, not by the Daml itself.
On multi-organization projects, the schedule risk that dominates everything else is agreement between the parties. Every participant has its own security review, its own infrastructure standards, and its own approval calendar. We have seen more institutional blockchain timelines slip on counterparty coordination than on any technical dependency, and we plan for it explicitly rather than discovering it in month four.
