Praecise Cloud: where agents run
Agents are moving from demos into production, and the question is no longer which model to call but where the agent lives. Praecise Cloud builds, places and supervises agents, MCP servers and their backends from source, on hardware Praecise owns.
The next decade of software will be written less as applications and more as agents: programs that read, decide, call tools and keep working after the person who started them has gone home. The hard part is no longer the model. Models are a call away. The hard part is everything around the model that has to stay up, stay current and stay accountable for months at a time. An agent needs somewhere to live.
That is the gap Praecise Cloud is built for. It is compute, MCP servers and backends for agents, on hardware Praecise owns. You bring the source. Praecise builds it, places it behind the edge, supervises it and keeps it reversible.
The agent is not the hard part
Building an agent that works on a laptop takes an afternoon. Running one in production is a different job. It needs a process that restarts when it falls over, a certificate, a URL other systems can reach, a database, object storage, a way to change models without rewriting code, and a record of what was deployed and when. Each of those is a small project. Together they are the reason so many agent pilots never become services.
Analysts have started to say so plainly. Gartner predicts that over 40% of agentic AI projects will be cancelled by the end of 2027, citing escalating costs, unclear business value and inadequate risk controls. Two of those three are infrastructure problems wearing a different name. Cost runs away when every team assembles its own hosting. Risk controls are inadequate when nobody can say which release is live or roll it back in one step.
Bring the source; Praecise operates it
Praecise Cloud starts from the tree you already have. There is no Dockerfile to write. The platform reads the source, recognises Node, Python and static sites, builds a release on Praecise machines, gives it a port and a unit, and places it behind the edge with a certificate. The previous release stays in place until the new one responds. Rollback is a pointer back to the earlier release.
Once it is running, the process is supervised and health-checked by name, and served bytes can be checked against the ones that were approved. Every placement and every provision is recorded. For a CTO, that record is the point: it is the difference between believing an agent is running the approved code and being able to show it.
Agents deploy the same way as everything else. A folder that runs locally with praecise dev is placed by the same process. An agent written with Praecise Harness, the open-source framework, is served as a chat UI, a REST endpoint, an MCP server and an A2A agent card from the same deploy.
MCP servers as first-class services
The Model Context Protocol has become the common way agents reach tools. When it moved to the Linux Foundation's Agentic AI Foundation, Anthropic reported more than 10,000 active public MCP servers. Most of them are small services someone has to host, secure and keep alive.
On Praecise Cloud an MCP server is deployed like an app. On the first deploy it gets a URL, a certificate and a token, and agents elsewhere can call it over the internet. That turns an internal capability, such as a pricing lookup, a stock check or a ledger query, into a tool any authorised agent can use, without a separate hosting project for each one.
A model ladder, not a model id
Hard-coding a model identifier ties an agent to a moment in time. Praecise Cloud offers a ladder instead, with fast, balanced and best tiers. Praecise keeps the models behind the ladder current and accelerates them with Praecise Engine, its open-source inference layer, which speculates only where speculation pays and checks drafter licences before use.
Nothing about this is a lock-in. The framework is open source and works on its own. You can declare your own model endpoints in praecise.config.ts; the first endpoint whose credential is present runs, and a declared endpoint takes precedence over the Cloud. Or you set one key, PRAECISE_API_KEY, and models, database and object storage are provisioned and reachable through the same code. The Cloud shortens the configuration. It never changes the code.
Data, machines and automations
Agents are only as useful as what they can remember and what they can run on. Praecise Cloud provides Postgres, vectors, time series, key-value and object storage, with one command to provision a tenant and hand the app its credentials. It offers virtual machines in fixed shapes and whole GPU nodes for training, batch jobs and models that do not fit the ladder. The GPU class is NVIDIA Grace Blackwell, where Praecise Engine is verified, with one CUDA build spanning Turing through Blackwell.
Automations sit alongside: scheduled or event-driven durable workflows that keep a journal and can pause for a person. An agent that needs a human to approve a step does not lose its place while it waits.
Who it is for
Praecise Cloud is for teams building agents who do not want to run infrastructure. It suits a CTO who has a working agent and a list of reasons it is not yet a service: hosting, certificates, rollback, model churn, storage, audit. It suits platform teams that want MCP servers reachable by agents across the business without standing up a new service for each. It suits organisations that need to point at a record and say what is deployed, on which machines, and since when.
Early workloads are placed by conversation. You describe what you run and where it runs today, and Praecise replies with what is needed to place it.
How it connects
Praecise Cloud is the layer where an agent runs. The rest of the suite gives it what it needs to do real work.
Underneath, Praecise Metal is the owned machines, placed, powered and cooled to measured targets, and Praecise Furcate is the operating system and edge hardware on them. That is what "on hardware Praecise owns" means in practice.
Above, each agent gets an address and a searchable record in Praecise Inbox, so what it says and receives is attributable to it. Businesses hand payments, books, orders and mail to agents with Ipnops. Agents that need to move money call Skerry with their own keys, where Bridge and Stripe perform the regulated acts under their own licences. One Praecise account opens all of it.
The place agents live
The organisations that get value from agents will be the ones that treat them as services: built from source, placed deliberately, supervised, reversible and recorded. Praecise Cloud is that place, on machines Praecise owns and operates. Read more about it, and how to place a first workload, on the Praecise Cloud page.
