Andi API Overview
AI-native platform for human and agent collaboration to automate manual processes
Andi API is the AI-native platform for human and agent collaboration.
It gives teams and agents a shared execution layer to automate manual processes at scale by combining data, tools, and apps in one platform.
Why Andi API
- AI-native by design: built for agentic execution and human collaboration from day one.
- Code-first and API-first: define logic in code, integrate with your stack, and automate through APIs.
- Composable architecture: reuse data models, tools, and app surfaces across workflows.
- Operational reliability: add guardrails, approvals, and visibility where automation touches critical processes.
Core Building Blocks
- Data: Model your business context once and reuse it everywhere so agents can reason with complete, current state.
- Tools: Expose business actions as safe, composable tools with typed interfaces instead of brittle prompt-only behavior.
- Apps: Ship operator-facing workflows where teams can review outputs, approve actions, and intervene when needed.
How It Works
- Define your models: capture domain definitions, state transitions, hooks, and business logic in code.
- Integrate your use cases: wire models into tools and apps so agents can execute real workflows end to end.
- Operate with control: enforce permissions, monitoring, approvals, and auditability so automation stays safe and reliable.
- Deploy and run: move workflows to production, operate them continuously, and iterate with real-world feedback.
Use Cases
Create AI-native workflows for high-volume, decision-heavy operations:
- Automate pipeline generation: Generate and maintain operational pipelines from business rules, data dependencies, and delivery requirements.
- Track purchase orders: Monitor PO lifecycle in real time, surface exceptions early, and coordinate follow-ups across teams.
- Manage support tickets: Automatically triage, classify, and route tickets while keeping humans in the loop for escalations.
- Create data-driven recommendations: Turn live operational data into actionable recommendations for pricing, prioritization, and resource allocation.