Introducing Lamatic 3.0

Turn Domain Expertise into Reliable Agentic Apps

Lamatic is the AI middleware to build Agents visually, Deploy on Serverless, and let your team Optimze continously while we handle the rest.

Make me an AI chatbot by Scrap|
Automation
Assistant
Embed
Agentic
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AI Chatbot
Bot for Slack
Recruiting Bot
No credit card required

RAG (Retrieval-Augmented Generation)

Generate accurate responses using large volumes of structured and unstructured data

Internal Assistant

Build an internal chatbot that finds precise answers within your company’s knowledge base.

Semantic Search

Perform natural language search ( aka vector search ) across structured and unstructured data effortlessly.

Document Processing

Extract valuable insights from documents and unstructured information at scale.

Deep Research

Customized agentic deep research across both internal and external data sources.

Generative AI

Generate text, JSON, or images intelligently based on the given context.

Build fast

Cut time to market 10x, invest 3x less money by choosing a pre-built workflow or creating a new workflow with a visual flow builder

Integrate in a click

Plug seamlessly into the tools and data you already use, making integration a one-click step instead of a month-long project.

Enhance with AI

Generate instant answers from your data, personalize user journeys, automate repetitive tasks, making your product smarter while your team focuses on growth.

Scale instantly

Deploy and scale without limits with Lamatic’s serverless infrastructure; you cut latency in half and handle millions of users automatically.

Stay reliable, even at scale.

Get full visibility with real-time tracing,insights, and performance dashboards. Spot issues before customers do, and ensure every agent delivers results.

Iterate without friction.

Find out what works sooner; Save engineering time, cut unnecessary spending, and deliver more value to customers with every release.

Developer SDK

Designed for engineers, used by non-dev's

JavaScript
Next.js
Python
Curl
//npm i lamatic

import { Lamatic } from "lamatic";
 
const lamatic = new Lamatic({
  apiKey: "your-api-key",
  projectId: "your-project-id",
  endpoint: "your-endpoint",
});

## one line execution
const response = await lamatic.executeFlow(flowId, payload);
#npm i lamatic

import { Lamatic } from 'lamatic'

const client = new Lamatic({
  projectId: process.env.LAMATIC_PROJECT_ID,
  apiKey: process.env.LAMATIC_API_KEY,
})

export default function Page() {
  const handleClick = async () => {
    const response = await client.executeFlow(process.env.LAMATIC_FLOW_ID, {
      prompt: 'hello',
    })
    console.log(response)
  }

  return (
    <button onClick={handleClick}>Execute Flow</button>
  )
}
import os
import requests

response = requests.post(
  os.getenv('LAMATIC_ENDPOINT'),
  headers={
    "Authorization": f"Bearer {os.getenv('LAMATIC_API_KEY')}",
    "Content-Type": "application/json",
    "x-project-id": os.getenv('LAMATIC_PROJECT_ID')
  },
  json={
    "query": """query ExecuteWorkflow($workflowId: String!, $topic: String) {
      executeWorkflow(workflowId: $workflowId, payload: {topic: $topic}) {
        status
        result
      }
    }""",
    "variables": {
      "workflowId": os.getenv('LAMATIC_WORKFLOW_ID'),
      "topic": "topic"
    }
  }
)

print(response.json() if response.status_code == 200 else f"Error: {response.status_code} - {response.text}")
curl -X POST https://<project>.lamatic.dev \
  -H "Authorization: Bearer ${LAMATIC_API_KEY}" \
  -H "Content-Type: application/json" \
  -H "x-project-id: YOUR_PROJECT_ID" \
  -d '{
    "query": "query ExecuteWorkflow($workflowId: String!, $prompt: String) { executeWorkflow(workflowId: $workflowId, payload: { prompt: $prompt }) { status result } }",
    "variables": {
      "workflowId": "YOUR_WORKFLOW_ID",
      "prompt": "The excited car draws."
    }
  }'
Success metrics

Measurable Impact

Teams launch faster, more efficiently, and with significant cost savings using Lamatic

Start risk free
Up to
10x
Faster to Launch & Iterate
Up to
$30,000/yr
Estimated Savings (per project)
Up to
3x
Faster Performance

Integrate with 100+ models, data sources, and apps.

Case Studies

What Lamatic made happen:

Nemo’s MVP launched just over 3 months from project start to public beta.

ā€œWe have full control over the product experience, and Lamatic gives us the tools to move like a startup while building like an enterprise.ā€

Johan Hoernell
CEO, Co-Founder
Read full case study →

How Beehive Climate Does The Right Thing

"With Lamatic, we suddenly had infrastructure that just worked. Instead of building a data extraction engine from scratch, we could focus on delivering the insights and recommendations our customers needed so they could take action."

Andrew Phavichitr
CTO & Cofounder at Beehive
Read full case study →

Reveal Upgrades More Than Software Training

"Lamatic has supercharged our AI development and allowed us to deploy complex AI workflows faster than ever."

Johan Hoernell
CEO, Co-Founder
Read full case study →

Traq.ai Accelerates Roadmap

Smart, user-friendly, and incredibly valuable – Lamatic is the perfect solution.

Adam Rubenstein
CEO
Read full case study →

Select a template and be live by Ā 13:55

Designed for fast-moving teams that count their time in minutes, not hours.

Google indexation

Vectorizes Google Drive data and loads it into a vector database. Enables fast, accurate search and RAG Flows grounded in the context of your data.

Rag chatbot

This flow builds a chatbot that answers questions based on a context database containing all relevant information. User queries are answered using the existing documentation.

Semantic Search

This flow builds a search widget that retrieves data from a vector database and a RAG Node, presenting the information in the ideal widget format.

Website Indexation

This automation allows you to scrape webpage content, vectorize it, and store it in a context store. The vectorized content can then be used to chat with and answer questions about the webpage.

Slack Bot

Delivers instant answers through Slack using the /Ask command by running a RAG retrieval on vectorized data. Provides quick answers to audiences already using Slack.

S3 Indexation

This flow vectorizes S3 data and loads it into a vector database, enabling fast, accurate search and RAG flows grounded in the context of your data.

Let's turn your expertise into AI Agents together

Book a demo to see how Lamatic can help your turn your pain point or disruptive idea into a Reliable Agentic Application.

Get a Demo

Frequently Asked Questions

Can I use Lamatic today?

Yes. Lamatic is available to all. Just click Sign Up and start building.

What does Lamatic's monthly subscription include?

Lamatic's monthly subscription includes all available managed integrations, a vector database, managed hosting, edge deployment, and an SDK which includes pre-built, customizable components, a GraphQL API and chat support. Professional services are offered on an hourly basis on request.

What is your cancellation policy?

You may cancel your subscription at any time and your subscription will terminate at the end of your current subscription term (either monthly or annually).

Do you offer services in addition to your platform?

Yes. We offer consulting, project management and development services to help you achieve your GenAI objectives. While our work doesn't include Full Stack or non-AI application development, we are happy to work with you to ensure great user experience and help you realize your vision.

What about data and ownership?

Your data is encrypted and stored in the cloud. You can export or delete your data at any time. We don't have access to this information unless you explicitly grant permission for development or troubleshooting purposes. You own the models trained with your data and the related IP.