AI Agent Builder
A low-code environment for composing new agents from governed Foundation-layer building blocks.
What breaks without this
- Teams build one-off AI scripts outside any governance framework because there is no supported way to compose an agent quickly.
- Every new use case re-implements authentication, logging and error handling from scratch.
- IT and security lose visibility into AI use cases built outside a central platform.
Provides a low-code environment for internal teams to compose new agents from existing Foundation layer building blocks — gateway access, retrieval, orchestration primitives — so new use cases inherit governance and security controls by default instead of being built as one-off, unmonitored scripts.
What it does
Visual and low-code composition of agents from pre-built tool, retrieval and reasoning components.
Automatic inheritance of gateway authentication, logging and policy enforcement for every agent built on the platform.
A component library covering common patterns — document lookup, form filling, approval routing, notification.
Built-in testing and evaluation harness before an agent is promoted to production.
Publishing controls so new agents require a defined review before going live.
From request to result
Compose
A builder assembles an agent from existing components — retrieval, tools, decision logic — in a visual or low-code interface.
Test
The agent runs against a test harness and evaluation suite before promotion.
Review
A defined reviewer approves the agent for production, inheriting governance and observability by default.
Operate
The published agent runs under the same monitoring, logging and policy enforcement as every other agent on the platform.
Built to be audited, not just used
- Every agent built on the platform inherits Enterprise AI Gateway and Governance & Observability controls automatically — it cannot opt out.
- Production publishing requires an explicit review step, preventing unreviewed agents from reaching live systems.
Fits existing infrastructure
Outcomes to expect
Qualitative, directional outcomes. We do not publish unverified performance figures — see the case studies section for engagement-specific, authorized results.
- New AI use cases are built inside a governed platform rather than as unsupported shadow scripts.
- Time to stand up a new internal agent decreases because common components already exist.
- IT and security retain full visibility into every agent running in production.
Works alongside
AI Workflow Automation
Automates multi-step business processes end to end, with human checkpoints where judgment is required.
Developer & EngineeringAI Code Review Copilot
Reviews pull requests for defects, security issues and standards compliance before a human reviewer does.
Developer & EngineeringAI QA / Test Automation
Generates, maintains and prioritizes test coverage as the application changes.
Evaluate AI Agent Builder for your environment
Talk to an architect about integration into your existing stack, or request a scoped demo against a representative use case.