VPS Paperclip: controlled deployment
Deploy Paperclip on a controlled VPS
To proceed with confidence, rely on the guides available on the official Paperclip website. You retain control of CPU, memory and storage resources, as well as your data, audit logs and AI models. This approach promotes a clear, reproducible deployment adapted to your usage.
VPS-1
From
A$6.29
ex. GST/month
A$6.92 incl. GST/month
Specifications:
2 vCores
4 GB RAM
40 GB SSD NVMe
Daily backup of the previous 24 hours
VPS-2
From
A$11.90
ex. GST/month
A$13.09 incl. GST/month
Specifications:
4 vCores
8 GB RAM
75 GB SSD NVMe
Daily backup of the previous 24 hours
VPS-3
From
A$17.08
ex. GST/month
A$18.79 incl. GST/month
Specifications:
6 vCores
12 GB RAM
100 GB SSD NVMe
Daily backup of the previous 24 hours
VPS-4
From
A$32.81
ex. GST/month
A$36.09 incl. GST/month
Specifications:
8 vCores
24 GB RAM
200 GB SSD NVMe
Daily backup of the previous 24 hours
Orchestrating your AI agents with Paperclip
In an autonomous AI agent project, the difficulty is not limited to the choice of model: you must define the objectives, accessible tools, exchanges between agents and executed decisions. Paperclip provides this orchestration layer by structuring the roles of each agent, their responsibilities, their operational memory and the rules that determine when they can act, delegate or query an external service. This organisation facilitates operational governance. Agents can be separated according to their functions — planning, execution, validation, supervision — in order to prevent a single component from concentrating too many privileges. Access to APIs, AI models, business data or third-party systems can thus be controlled in a more granular way, with a least-privilege logic and better traceability of the actions performed. Deploying Paperclip on an OVHcloud VPS allows this orchestration to be centralised in a self-hosted, controlled and isolated environment. You retain control over the configuration, access keys, logs and flows between agents, whilst having a flexible base to connect your AI services. This approach offers a clearer framework for industrialising your use of autonomous agents, strengthening their security and evolving your architecture without depending entirely on an external platform.
Organise your AI agents with control, traceability and controlled costs
Structuring autonomous AI agents in production
Paperclip allows you to structure a multi-agent system as a controllable software architecture, and not as a succession of isolated calls to a model. Each agent can be defined with a functional scope, permissions, expected inputs, standardised outputs and escalation rules. This organisation facilitates operation by DevOps teams and AI startups: responsibilities are identifiable, dependencies are explicit, and decision flows can be tracked, tested and then adjusted over the course of iterations.
Decomposing objectives into controlled workflows
Cascading objectives transform a business intention into tasks executable by several specialised agents. A main objective can be broken down into sub-objectives, enriched with technical constraints, then distributed to the relevant agents with an adapted context. This approach limits execution drift: autonomy remains framed by success criteria, validation points and priority rules. Teams thus retain control of the expected result, whilst automating part of the analysis, generation or verification.
Assigning precise and auditable roles
Fine-grained role management allows functions to be distributed between coordinating agents, analysis agents, execution agents, quality control agents or validation agents. Each role can be associated with a level of authority, accessible tools and operational limits. One agent can propose an action, another evaluate it, whilst a coordinator arbitrates or triggers a human validation. This separation improves traceability, reduces unpredictable behaviour and makes orchestration more readable for product, security and platform teams.
Choose AI models and control API costs
Paperclip lets you choose the most suitable AI models for each stage of the workflow: high-performance model for complex reasoning, more economical model for classification, specialised model for technical generation or document analysis. This flexibility helps to optimise the quality, latency and cost ratio. By controlling API calls by role, by scenario or by volume, teams can limit unnecessary requests, compare several providers, adjust usage policies and anticipate expenditure before scaling up.
The concrete benefits of a self-hosted Paperclip VPS
Install Paperclip manually on an OVHcloud VPS
Prepare a VPS sized for Paperclip
Before installation, size the VPS according to the document volume, the number of users and the expected AI processing. Provide a maintained Linux distribution, secure SSH access, a non-privileged user with sudo, NTP synchronisation, an active firewall and a domain name pointing to the public IP address. For a test environment, 2 vCPUs, 4 GB of RAM and 40 GB of SSD storage constitute a reasonable base; in production, increase the RAM, vCPUs and disk space according to indexing, attachments, logs and backup retention.
Install Paperclip with Docker and Compose
Manual installation relies on Docker Engine and Docker Compose in order to isolate services and make deployment reproducible. After updating the system, install Docker from the official repositories, add the operating user to the docker group, then describe the services in a compose file: Paperclip application, database, potential reverse proxy and persistent volumes. Environment variables must cover secrets, public URLs, database settings, AI API keys and execution options specific to your environment.
Secure the network and preserve data
Persistence must be treated as a central element of the architecture. Mount dedicated volumes for the database, generated files, imported documents, indexes and application logs, with permissions strictly limited to the relevant container. Expose only the necessary ports, ideally via a TLS reverse proxy, and limit administration to SSH with keys, fail2ban and restrictive firewall rules. Schedule regular off-VPS backups, test restoration and enable OVHcloud infrastructure DDoS protection to strengthen network availability.
Monitor and connect the AI workflow
In operation, track CPU, RAM, disk, I/O usage, container availability, application errors and processing queue saturation. Docker commands, journald, Prometheus, Grafana or a monitoring agent can be integrated into your existing practices. Paperclip can then join your AI workflow: connection to models such as Gemini, triggering of automations, development assistants, internal pipelines or ticketing tools. The objective is to maintain an observable, backed-up and controlled platform, whilst giving AI agents a stable environment to produce, classify and trace their actions.