# How It Works

> Source: https://ibl.ai/how-it-works

From first conversation to production agents — our partnership process

## Step 1 — Deployment: Platform Delivery

Choose the deployment model that fits your organization

### ibl.ai-Hosted

We manage the infrastructure

- Fastest time to launch
- No infrastructure overhead for your IT team
- Fully managed updates and maintenance
- Ideal for organizations that want speed

### Customer-Hosted

Deployed in your environment

- Full GitHub repository — the complete platform code
- Pre-built Docker images — ready to deploy
- Your security perimeter, your control
- Ideal for regulated industries and data sovereignty

Both options deliver the same platform — a runtime for creating, managing, deploying, and using AI agents across web, mobile, API, and MCP

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Platform is live — agents are accessible from day one

## Step 2 — Delivery: How Delivery Works

A three-phase process from code handoff to production

### 1. We deliver the platform

- Full GitHub repository — the complete multitenant platform code
- Pre-built Docker images — ready to deploy, tested, and versioned

### 2. Joint development environment

- We work alongside your team in a dev/staging environment
- Agent configuration, system integration, testing, and training happen here together

### 3. Production — your way

- Your team can promote to production independently, on your schedule and through your processes
- Or we manage production for you — we run production environments for many leading organizations
- Access to your production data is never a prerequisite — the choice is yours
- ibl.ai-hosted deployments include full production management by our team

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Platform deployed — begin building and connecting agents

## Step 3 — Development: Agent Development

Self-serve, collaborative, or both — your team and ours build together

### Self-Serve

Your teams build independently

- Create agents through the platform UI or API
- Connect to your data sources directly
- Leverage institutional knowledge your team already has
- Full API coverage — programmatic agent management

### Collaborative

We work with you to build agents

- Build agents connected to specific data sources
- Develop MCP servers and custom data integrations
- Configure SSO and enterprise deployment standards
- Build software that makes agents more capable

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Agents live and working — visible results from day one

## Step 4 — Integration: Enterprise Integration

Connect to the tools and systems your organization already uses

- **Single Sign-On** — SAML / OIDC
- **Data Sources** — Your existing databases and APIs
- **MCP Servers** — Custom data integrations
- **Existing Tools** — LMS, CRM, SIS, and more

The platform adapts to your stack — your workflows don't need to change to support agents

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Integrated and operational — continuous improvement begins

## Step 5 — Partnership: Ongoing Collaboration

A continuous partnership — not a one-time deployment

- **Building specific agents** — We develop purpose-built agents for your use cases, connected to your data and tuned for your workflows.
- **Extending platform capabilities** — We build new features and integrations that make your agents more powerful — additional data sources, richer tooling, new interfaces.
- **Ongoing communication** — Dedicated channels for collaboration, support, and strategic alignment as your needs evolve.

## Best Practices: What Makes This Successful

1. **Lead with tangible results** — Start with concrete agents that can be demonstrated from day one. Stakeholders see working agents immediately — not a black box for months.
2. **Start with specific use cases** — Define concrete agents early. If the project definition is too broad without specific agents to show, stakeholder buy-in stalls while time goes into invisible infrastructure work.
3. **Adapt to the existing stack** — The platform integrates with your current tools and data sources. Your teams don't need to change their workflows to accommodate agents.
4. **Empower your engineers** — Your team has the institutional knowledge. When your engineers can build agents programmatically and connect them to internal data sources, the value compounds.

## Getting Started: Proposed Next Steps

- **Pilot program** — Deploy the platform on your infrastructure with a focused use case
- **Architectural deep-dive** — Walk through the platform architecture with your technical teams
- **Integration mapping** — Assess your existing systems and architect the agent layer
- **Hands-on workshop** — Your teams learn to build and deploy agents on the platform

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*[View on ibl.ai](https://ibl.ai/how-it-works)*