Build the intelligence layer for your business.
Clouisle combines AI agents, workflow orchestration, and enterprise-grade knowledge retrieval into one production platform.
Designed for platform teams shipping secure AI at scale
Why Clouisle
Clouisle turns static enterprise knowledge into agent-driven execution. Teams can retrieve context, reason across systems, and trigger workflows without losing security or governance.
Capabilities
Each capability is designed to shorten delivery cycles, improve response quality, and reduce operational risk in enterprise AI deployments.
Build multi-model agents with knowledge binding, tool orchestration, visibility control, and conversation lifecycle management.
Design production workflows with 15+ node types, multi-trigger execution, real-time monitoring, and debugging mode.
Ingest PDFs, DOCX, XLSX and more, then run chunking, vector indexing, and async processing on enterprise scale.
Operate with multi-tenancy, RBAC, SSO, audit logging, and compliance-ready controls built into every workflow.
Extend the platform with built-in tools, custom HTTP tools, MCP integrations, and sandboxed code execution.
Track execution states, token usage, API activity, and audit trails to keep teams aligned and production safe.
Memory Layer
Clouisle maintains a persistent, permission-aware memory profile for each user. This memory is only used inside agents, helping them inherit context, preferences, and prior actions across sessions without repeated setup.
Agents can reuse one durable memory record that carries role, preferences, recent objectives, and accepted outputs across sessions.
Memory is only available to agents, and every read or write stays scoped by tenant, team, and role policies.
RAG Strategy
Use the right retrieval strategy for each business scenario. Clouisle supports both deterministic retrieval and agent-driven reasoning workflows.
Best for policy Q&A, documentation lookup, and scenarios where stable grounding and low latency are critical.
Best for complex tasks requiring decomposition, iterative lookup, tool invocation, and cross-source synthesis.
Advantages
Beyond features, Clouisle delivers the operational model required for enterprise AI: governed, measurable, and production-ready.
Launch pilot agents and workflows in weeks, not quarters, with reusable templates and unified orchestration.
Business-ready pilot window: under 2 weeks
Apply RBAC, SSO, audit trails, and scoped API controls across every critical workflow from day one.
Compliance-friendly by default
Switch between 15+ providers and models while keeping consistent execution, observability, and policy controls.
Avoid provider lock-in
Track quality, latency, cost, and usage in one control plane to make AI operations visible and accountable.
Runtime + governance telemetry unified
Enterprise rollout path
A practical delivery sequence that aligns platform teams, business owners, and compliance stakeholders.
Identify 2-3 business-critical scenarios where response quality and execution speed directly impact outcomes.
Configure knowledge access, tool permissions, and execution policies, then validate with staged rollout gates.
Use unified monitoring to optimize model routing, cost, and reliability while meeting audit and security requirements.
Architecture
A clean separation between UI, API, and infrastructure gives engineering teams predictable performance and operational control.
Scene 01
User traffic enters through a thin web gateway, then hands execution to a centralized orchestration layer.
Scene 02
Knowledge retrieval and durable state stay separated, so recall remains fast without losing auditability.
Scene 03
Async workers and schedulers turn agent decisions into background execution, follow-up, and timed automation.
Scene 04
Vector and worker clusters expand horizontally when throughput grows, while the control plane keeps policies stable.
Frontend Service
Next.js Web Gateway
Backend Service
FastAPI Control Plane
Vector DB Cluster
Distributed Qdrant
PostgreSQL
Transactional Metadata Store
Async Worker Cluster
Distributed Task Runtime
Scheduler Service
Cron & Time-based Triggers
Qdrant Node A
Primary shard reads/writes
Qdrant Node B
Replica + failover
+ Add Node
Auto-join distributed cluster
Worker Node A
Document processing queue
Worker Node B
Workflow execution queue
+ Add Node
Elastic worker expansion
Security & Deployment
Private deployment: run the full stack in your own VPC or on-premises infrastructure
Data isolation: all business data, vectors, and model interactions stay within your network boundary
Multi-tenancy with team-level resource isolation
SSO with OIDC, OAuth2, SAML 2.0, and CAS
Granular RBAC and scoped API keys
Audit logs with before/after snapshots
No external data transfer: LLM calls can be routed through private endpoints or local models
Encryption at rest and in transit for all stored data and API communications
Use Cases
Deliver trustworthy answers grounded in internal documents, policies, and systems.
Automate business workflows that mix LLM reasoning, APIs, approval gates, and notifications.
Standardize contract, policy, and regulatory analysis with auditable AI execution.
Empower support teams with agent-driven triage, retrieval, and guided resolutions.
Now: AI agents, workflows, RAG, SSO, notifications, audit logging · Next: industry templates, analytics workspace, plugin marketplace, mobile apps
The platform is currently in closed beta. Try it out or get in touch with us.
