Interplay
Low-code platform for building, running, and scaling agentic AI workflows across enterprise systems.
- Tool type
- Enterprise agentic AI workflow platform
- Made for
- Enterprise teams
- Runs on
- Customer-managed environments
- Container, desktop application, or self-extracting Linux server package; supports on-premises, private cloud, edge, and air-gapped deployments.
What it does
Interplay is Iterate.ai’s enterprise platform for creating AI-powered applications and agentic workflows. Teams can assemble AI agents, LLM calls, business logic, and system connections on a visual canvas, use code, or combine both. The platform includes a visual builder and SDK, multi-provider LLM orchestration, MCP support, vector search and RAG pipelines, custom nodes, and document automation. It can produce deployed workflows and applications that connect AI with enterprise systems.
It is aimed at enterprise platform and integration engineers, data and AI teams, product teams, and IT or security teams building and operating AI applications. Interplay runs in an organization’s environment: as a container, a desktop application for Windows, macOS, and Linux, or a self-extracting Linux server package. Supported deployment settings include on-premises, private cloud, edge, and air-gapped environments. The official pages describe both a visual workflow and a code-first SDK; they do not establish a hosted public web app or self-service signup.
To begin, contact Iterate.ai to schedule a demo, then discuss deployment and access with the company. Before adoption, confirm licensing and any compute or model-provider costs: no public price is provided. Deployment requires choosing an environment and providing suitable infrastructure; the product is hardware-agnostic but is not a managed public SaaS offering. Its integration palette is described as 600+ prebuilt nodes, but the sources do not enumerate the full list.
What it can do
- Visual low-code workflow builder and code-first SDK
- Orchestration of multi-provider LLM calls and AI agents with tools
- MCP support, vector search, and RAG pipelines
- Custom nodes generated from plain-language descriptions or installed from a registry and npm
- Document classification, OCR, extraction, and robotic process automation
- SSO, role-based access, secrets wallet, and workflow version control
Before you choose
- Interplay is deployed in the organization’s environment; it is not documented as a hosted public web runtime.
- Pricing and any licensing or infrastructure charges are not published in the official pages; confirm them with Iterate.ai.
- The platform offers both visual development and a code-first SDK; the latter may require engineering skills.
Listed under
Get started
Interplay product page directs prospective users to schedule a demo.
- Contact Iterate.ai to schedule a demo and discuss access.
- Select a deployment format and target environment with the vendor.
- Configure the environment, required integrations, and model access with the implementation team.
Plans and prices
Contact Iterate.ai for pricing. Compute, infrastructure, and model-provider charges are not specified in the pricing page.
We couldn’t find published prices for Interplay.
Sources for this overview
Product pages, documentation, and pricing checked 2 Nov 2026. Each source supports part of the overview; availability and prices can change.
- Interplay Documentation | Iterate.ai Docs ↗docs.iterate.ai
- Interplay: Build, Run, and Scale Agentic AI—Securely, at Enterprise Speed ↗iterate.ai
- Iterate.ai - Enterprise AI Application Platform ↗iterate.ai
- About Us ↗iterate.ai
- Generate Documentation | Iterate.ai Docs ↗docs.iterate.ai
- AgentOne ↗iterate.ai
- Iterate.ai Documentation ↗docs.iterate.ai
- Generate Enterprise ↗iterate.ai
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How we research- Company website
- iterate.ai: product, pricing and policy pages
- YC directory mirror
- Batch and company name
- Social accounts
- Accounts the company links, and its posts on X
- Human review
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- knowledge_base
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Last checked 2 Nov 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.