Interactive CLI & SDK
Operate the entire platform. As code.
The iai CLI and the Python SDK, designed to build and run Interactive Agents.
kyc-verifier · iai
Created from your codebase.
Control the entire platform.
From your terminal, or your coding agent.
The iai CLI and the Python SDK give you programmatic control of the entire platform: your agents, their context, and the infrastructure they run on. Drive them yourself, or point your favourite coding agent at them.
Control
Control the whole platform.
As code.
The iai CLI and the Python SDK are one programmatic interface to the entire platform and every agent, built for human developers and AI agents alike. Point your favourite coding agent at it, like Claude Code, or build with Co-Pilot.
One interface
The CLI and SDK control the entire platform and your agents.
Humans and agents
The same surface for developers and for AI coding agents.
Coding-agent native
Point Claude Code or any MCP agent at the platform.
Or use Co-Pilot
Drive the same objects in conversation.
Agents
Build any agent.
As a declarative manifest.
Declare the agent's behavioural logic, routines, policies, prompts, glossaries, macros, in one agent config manifest. No per-agent code. Create and manage agents with a single iai command.
iai agents
Create, update, and manage agents from the CLI.
Declarative manifest
Create the agent from one declarative YAML manifest.
Routines & policies
Multi-step processes and single-step rules, declared inline.
Prompt repository
Version-controlled prompts with prod, staging, and dev labels.
Context
Manage context.
As versioned components.
Policies, routines, glossaries, prompts, every context component managed as a versioned, schema-enforced object. The schema is checkable by developers and interpretable by AI agents, so generated context can never be malformed.
Versioned components
Every edit is a new version, reversible at any point.
Schema-enforced
Validated on create, so context can't be malformed.
Agent-readable
The same schema AI agents author against.
Policies & routines
iai policies, routines, prompts, glossaries, macros.
Observe
Inspect any run.
Human or agent.
iai traces returns the full hierarchical trace: every observation, model route, score, and cost on one record. Let other AI agents inspect running agents, and create autonomous evals that score them continuously.
Traces
Hierarchical traces with full attribution per turn.
Human or agent
Developers and other AI agents read the same record.
Autonomous evals
Score running agents continuously against your bar.
Scores & metrics
Read and write scores; trace-derived metrics.
Infra
Deploy the infrastructure.
Without managing it.
Define services and databases in a stack config, then deploy them with one command, or manually from the terminal. The power of Kubernetes under the hood, behind a CLI, so you focus on building agents that deliver value, not on infrastructure.
Services & databases
Deploy and manage both from one place.
Kubernetes, hidden
Autoscaling and replicas, without the operational overhead.
Stack config or terminal
Sync from a stack config, or deploy by hand.
Managed Postgres
Postgres with pgvector for retrieval.
Most platforms force a choice: the chat for your operators, or the SDK for your engineers. Here they're the same primitives, composed two ways. Co-Pilot drafts in conversation; your engineers compose in code. Same audit trail. Same approval pipeline. Same shipped artefact.
Pedro Mota Carmo
Enterprise Implementation Lead, InteractiveAI
Three surfaces · One platform
Operated by the engineers who own the runtime.
No new mental model. The iai CLI and your CI compose the same objects Co-Pilot composes in chat; the Python SDK traces and integrates the running agent. One versioned catalog, one trace.
Python SDK
Instrument and integrate in Python.
- pip install interactiveai
- Trace your own code on OpenTelemetry, with full spans and attributes.
- Integrate channels with a running agent: open sessions, stream events, set customer variables.
- Native LangChain & LangGraph, plus LlamaIndex, CrewAI, AutoGen, OpenAI Agents, Pydantic AI, and the Claude Agent SDK.
iai CLI
Build and operate from your terminal.
- iai agents create: the agent from a versioned manifest.
- iai routines · policies · prompts · macros · glossaries: behavioural config as code.
- iai stacks sync: services and databases, from a stack config or the terminal.
- iai datasets · dataset-runs · scores · traces: evaluate and audit every run.
Coding agents
Point your coding agent at the platform.
- Expose the platform to Claude Code, or any MCP-capable agent.
- Have it create, deploy, and monitor your Interactive Agents.
- Every component is schema-enforced, so generated context can't be malformed.
- Same CLI, same SDK, same governance as a human developer.
One versioned catalog · One trace · Composable in chat or in code
CLI & SDK, answered.
The questions engineering leads and platform teams bring before building on a new AI runtime.
Start Building
Build your first agent from the command line.
Author policies, ship through iai stacks sync, and stream traces to your stack, all from your dev loop. Read the docs or start building now.