LLM as a Service + Human in the Loop Integrations, Built by an AI Agent
Put LLM as a Service + Human in the Loop to work with AI and enterprise-grade automation
Learn more about LLM as a Service integrations or talk to a human
4.9/5 on G2·
Google for Startups Accelerator
Workflows you can build between LLM as a Service and Human in the Loop
See the kind of workflows teams build with LLM as a Service and Human in the Loop below — describe the exact one you want above and the Agent builds it on demand.
LLM as a Service + Human in the Loop
When a low token customer trigger fires in LLM as a Service, send a review request to Human in the Loop.
See details
Browse the full workflow library →
Looking to achieve something else with LLM as a Service and Human in the Loop?
Just describe what you need — the Agent researches both APIs and builds the real automation on demand.
Try Knit FreeTriggers & actions for LLM as a Service and Human in the Loop
Everything LLM as a Service and Human in the Loop can do inside a workflow — the triggers that start one and the actions that run when it fires.
LLM as a Service Explore LLM as a Service →
LLM as a Service provides cloud access to large language models for building custom artificial intelligence text generation applications.
TriggersTriggers when a customer falls below the token limit you specify.
Triggers when a new customer makes their first call in your application, or a new customer is manually created in your control panel.
Updates the context data in an Agent
Updates the status of a customer.
Updates the number of tokens a customer has in the system
Creates or updates a customer in the system.
Human in the Loop Explore Human in the Loop →
An AI workflow platform that incorporates human oversight and verification into automated data processing tasks.
TriggersTriggers when a specific Human in the Loop step runs in another Zap.
Ask for additional information during the Zap run.
Ask someone to approve or change data before continuing the Zap.
Other AI Models apps on Knit
Explore more AI Models integrations you can automate with Knit — or describe a custom workflow and the Agent builds it.
Anthropic (Claude)
Anthropic (Claude) is an artificial intelligence platform and AI assistant designed to process text, analyze information, and assist with complex tasks.
AssemblyAI
AssemblyAI is an artificial intelligence speech recognition platform offering transcription, audio intelligence, and speech-to-text API models.
Azure OpenAI
A cloud service providing enterprise access to OpenAI's advanced language models with built-in security and compliance controls.
Claude
Anthropic Claude is an artificial intelligence language model designed to perform conversational reasoning, text generation, and complex data analysis tasks.
Cohere AI
Cohere AI provides large language models and natural language processing tools for building custom artificial intelligence applications.
Deepgram
An AI speech recognition and transcription API platform that converts spoken audio into structured text in real time.
DeepSeek
DeepSeek is an artificial intelligence platform that provides advanced open-source language models for reasoning, coding, and text generation.
Eden AI
An API aggregator platform that connects multiple artificial intelligence engines for speech, vision, and natural language processing.
Other AI Agents apps on Knit
Explore more AI Agents integrations you can automate with Knit — or describe a custom workflow and the Agent builds it.
Agenthost.ai
A cloud platform designed to host, deploy, and monitor autonomous artificial intelligence agents for business automation.
AgentHub
AgentHub is an automation platform that enables users to build, link, and deploy automated AI workflows for business operations.
Agents
Agents is an AI development platform that allows users to build, configure, and deploy autonomous AI agents for automated tasks.
AirAgent
AirAgent is an AI-powered automated agent platform designed to automate customer interactions, answer incoming inquiries, and manage phone calling tasks.
Airtop
An artificial intelligence platform that enables autonomous AI agents to interact with websites and perform browser-based workflows.
Appointwise
Appointwise is an AI-powered conversational agent that automates customer appointment scheduling, rescheduling, and calendar management.
Bland AI
An AI platform that enables businesses to build and deploy conversational phone agents for automated voice calling.
CrewAI
CrewAI is an open-source framework for orchestrating autonomous AI agents to collaborate and execute complex multi-step workflows.
Customer Stories
See how leading technology firms are scaling their operations
Amazing Product With Exceptional Support from the team. By using Knit we managed to speed up our development by orders of magnitude.
A brilliant tool to let you seamlessly integrate with many different systems. It is very easy to integrate with and customer support is next level.
Seamless integration experience. Well-documented, self-explanatory APIs, and excellent service and support.
Easy to integrate. Knit's dashboard is intuitive for setting up and testing integrations, and the sandbox is extremely useful during development.
Knit shipped a brand-new Timesheet API in a week and handed us a ready-to-use NetSuite sandbox. That velocity is priceless when you're running payroll in 40+ countries.
#1 in Ease of Integrations
4.9 out of 5 stars on G2
Common questions about LLM as a Service + Human in the Loop
Is there a pre-built LLM as a Service + Human in the Loop automation?
Not yet, but Knit's Integrations Agent can build one — describe what you want and it researches LLM as a Service and Human in the Loop's public API docs (or your own uploaded docs) and builds a working automation.
Does this require a pre-built LLM as a Service or Human in the Loop connector?
No. The Agent works whether or not LLM as a Service or Human in the Loop already has a pre-built connector in Knit's catalog — it researches the real API surface either way.
How long does it take to build?
Minutes to build a first working version, not weeks — you test it against real data before it goes anywhere near production.