
Build agents on Prajvis or bring your own. Every agent gets identity, storage, tools, sandbox, and observability.
You can spin up an agent in minutes. But making it production-ready? That's where months of work begins.
Your agent acts on behalf of users, but you can't track which user triggered which action.
Knowledge bases in one place, files in another, chat history somewhere else. Your agent has no unified memory.
Every new capability means building another integration. MCP tools scattered across services with no central management.
No visibility into what your agents are doing. No data to fine-tune. No insights to improve.
Build agents directly on Prajvis or bring your own. Every agent gets identity, storage, tools, an on-demand sandbox with terminal and browser, and complete observability. All agents become first-class citizens.
Identity, storage, tools, sandbox, and observability. Build agents here or bring your own, all become production-ready.
Every agent has its own identity with permissions and tool access. Every user gets social login built-in. Now you can track exactly what each agent did, for which user, at what time.
Upload documents for your agent to reference. Add notes and instructions. Store files that agents can work with. Everything your agent needs to be effective, centralized and always available.
Connect OpenAI, Anthropic, or any provider. Switch models per agent. Host your MCP tools directly on Prajvis or connect remote servers. Mix and match for each task.
Every agent gets access to its own hosted sandbox on demand. Execute code in a terminal, browse the web, interact with systems, all in an isolated, secure environment that spins up when needed.
Every conversation logged. Every tool call recorded. Every user interaction captured. Use this data to understand behavior patterns, identify issues, and fine-tune your models.
Your agents, your MCP servers, your integrations - all running on Prajvis with access to shared context, storage, and providers.
External A2A agents? Custom-built agents? They all become first-class citizens on Prajvis with full data capture and observability.
Build MCP servers and host them directly on Prajvis. Attach them to any agent. Use remote MCP servers alongside built-in tools.
Plugins can request object storage, files and Postgres with vector DB. Use existing Prajvis data in your integrations and agents.
Full visibility into agent behavior. Complete data capture for insights and improvement. Enterprise-ready security and compliance.
Every agent gets its own identity with permissions. Every user gets authentication. Track exactly who did what and on whose behalf.
Every conversation, every tool call, every user interaction is captured and stored. Use this data for insights, debugging, and model fine-tuning.
Understand how users interact with your agents. Identify patterns, track engagement, and continuously improve based on real usage data.
Complete separation between workspaces. Each tenant's agents, users, and data are isolated. No cross-contamination possible.
Define who can access which agents and tools. Set permissions at workspace, agent, or tool level. Full control over your deployment.
Complete audit trails for compliance. Every action logged with timestamps, user context, and outcomes. Export for regulatory review.
With auth, storage, tools, and observability handled,you can focus entirely on what your agents actually do.
Works With Any Stack
Whether you're building your first agent or orchestrating dozens, Prajvis provides the runtime you need.
Ship real AI products, not demos. Get auth, storage, and tools out of the box. Focus on your agent's unique capabilities.
Share tools and context across agents. Unified observability for your whole fleet. Data capture for continuous improvement.
Complete audit trails, multi-tenant isolation, and governance controls. Connect your own infrastructure. Know exactly what every agent does, for every user.
Stop duct-taping infrastructure. Give your agents identity, storage, tools, a sandbox, and observability in minutes, not months.