How does Tulip AI close the gap between documentation and deployment?
Operational knowledge shouldn't live in a document. Tulip AI reads what already exists — SOPs, work instructions, checklists — and brings it to the floor. Connected to live production data. Governed from day one. No middleware, no months of setup.
From existing process to deployed app
AI Composer transforms the documents you already have — SOPs, work instructions, checklists — into working Tulip apps.
Pick a use case
Start with a specific process pain point: an inspection, changeover, or escalation flow.
Build with AI Composer
Upload your SOP, work instruction, or checklist as a PDF — AI Composer extracts the content, proposes an app structure, and generates a working Tulip app in minutes. Use an existing app as a template to enforce your organization's standards across every generated app.
Test and validate
Review the generated app, test with real data, and configure human-in-the-loop approval gates before any AI action reaches the floor.
Deploy and govern
Deploy with full version control and audit logging. Publish to the Library, track adoption, and roll back any version instantly.
Connect Tulip to your AI and data stack
Connect Tulip to Snowflake, Cognite, and your full AI stack via the open Connector framework — MCP, REST APIs, MQTT, OPC-UA. Load AI Skills that make any LLM Tulip-aware.
How does Tulip AI reduce defects and eliminate manual data entry on the floor?
A measurement drifts. Before the operator reaches for a clipboard, the agent has already flagged it, logged it, and routed it to the right person. The operator gets a nudge — in their language — and keeps working. No escalation meeting, no paperwork, no missed deviation.
AI agents that act inside Tulip
Deploy fully configurable AI Agents that gather information, make decisions, and optimize performance across operations — from predicting maintenance needs to flagging defects and balancing resources, keeping production running smoothly without manual input.
- Monitor triggers across apps, tables, and APIs
- Assign tasks, escalate issues, update records automatically
- Pre-built roster: Quality, Changeover, SOP, Multilingual
- Build custom agents — no code required
Every agent runs within Tulip's governance layer — with configurable human approval steps, full audit trails, and override controls at every decision point. Operators stay in control; AI handles the routine.
Mastering agentic AI with Tulip
Step-by-step university course walking through agent architecture, triggers, and deployment in Tulip — from your first agent to production rollout.
Take the course →Tulip Connectors
HTTP connector, webhooks, and REST API — bring any external system, data source, or AI model directly into your Tulip workflows.
Explore Connectors →How does Tulip AI surface production intelligence without manual reporting?
The shift ends. Before the outgoing team walks out, the summary is already written — what ran, what drifted, what the next shift needs to know. The incoming leader reads it on the way in. No analyst, no delay, no "we'll circle back tomorrow."
Replay what happened on the floor
Factory Playback connects your existing IP camera infrastructure to large visual AI models — detecting quality issues, operator presence, waste, and process deviations directly from floor video. No new hardware required. Currently in active customer pilots.
- Quality issue and defect detection from live video feeds
- Process adherence and operator presence monitoring
- PPE compliance detection
- Waste identification for lean improvement initiatives
- Video observations correlated with Tulip production data
