Maitai

About Maitai

Maitai provides a managed AI model stack that detects and autocorrects faults in real-time, ensuring reliable and high-performance output tailored to specific applications. By preemptively switching to secondary models during performance issues, Maitai eliminates unexpected AI results and reduces operational risks for businesses.

```xml <problem> AI models can produce unreliable or faulty outputs, leading to unexpected results and increased operational risks for businesses. Detecting and correcting these faults in real-time is challenging, and relying on general-purpose models can be inefficient and costly. </problem> <solution> Maitai offers a managed AI model stack that detects and autocorrects faults in real-time, ensuring reliable and high-performance output tailored to specific applications. The platform preemptively switches to secondary models during performance issues, eliminating unexpected AI results. Maitai builds and manages custom AI model stacks, providing reliable, fast, and cost-effective inference. The system monitors AI health in real-time and provides actionable alerts through integrations with tools like Slack and PagerDuty. </solution> <features> - Real-time fault detection and autocorrections in AI output - Preemptive fallback to secondary models during outages or degraded performance - Custom AI model stacks tailored to specific applications - Simple integration with existing systems using a Python package - Real-time monitoring and observability of AI application health - Actionable alerts via Slack or PagerDuty integrations - Managed governance to ensure deterministic AI-enabled features </features> <target_audience> Maitai targets engineers and operations teams seeking to build reliable AI applications and simplify AI operations, as well as individuals and startups looking for managed AI solutions. </target_audience> <revenue_model> Maitai uses a tiered subscription model, with options for individuals ($50/month/app + $0.02/request after 5k), startups ($250/month/app + $0.02/request after 50k), and larger teams (custom pricing). </revenue_model> ```

What does Maitai do?

Maitai provides a managed AI model stack that detects and autocorrects faults in real-time, ensuring reliable and high-performance output tailored to specific applications. By preemptively switching to secondary models during performance issues, Maitai eliminates unexpected AI results and reduces operational risks for businesses.

Where is Maitai located?

Maitai is based in Bend, United States.

When was Maitai founded?

Maitai was founded in 2024.

How much funding has Maitai raised?

Maitai has raised 500000.

Who founded Maitai?

Maitai was founded by Christian DalSanto and Ian Hoegen.

  • Christian DalSanto - Founder/CEO
  • Ian Hoegen - Co-Founder/CTO
Location
Bend, United States
Founded
2024
Funding
500000
Employees
4 employees
Major Investors
Y Combinator, Pioneer Fund
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Maitai

Score: 100/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

Maitai provides a managed AI model stack that detects and autocorrects faults in real-time, ensuring reliable and high-performance output tailored to specific applications. By preemptively switching to secondary models during performance issues, Maitai eliminates unexpected AI results and reduces operational risks for businesses.

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Crunchbase
Founded 2024Bend, United States

Funding

$

Estimated Funding

$500K+

Major Investors

Y Combinator, Pioneer Fund

Team (<5)

Christian DalSanto

Founder/CEO

Ian Hoegen

Co-Founder/CTO

Company Description

Problem

AI models can produce unreliable or faulty outputs, leading to unexpected results and increased operational risks for businesses. Detecting and correcting these faults in real-time is challenging, and relying on general-purpose models can be inefficient and costly.

Solution

Maitai offers a managed AI model stack that detects and autocorrects faults in real-time, ensuring reliable and high-performance output tailored to specific applications. The platform preemptively switches to secondary models during performance issues, eliminating unexpected AI results. Maitai builds and manages custom AI model stacks, providing reliable, fast, and cost-effective inference. The system monitors AI health in real-time and provides actionable alerts through integrations with tools like Slack and PagerDuty.

Features

Real-time fault detection and autocorrections in AI output

Preemptive fallback to secondary models during outages or degraded performance

Custom AI model stacks tailored to specific applications

Simple integration with existing systems using a Python package

Real-time monitoring and observability of AI application health

Actionable alerts via Slack or PagerDuty integrations

Managed governance to ensure deterministic AI-enabled features

Target Audience

Maitai targets engineers and operations teams seeking to build reliable AI applications and simplify AI operations, as well as individuals and startups looking for managed AI solutions.

Revenue Model

Maitai uses a tiered subscription model, with options for individuals ($50/month/app + $0.02/request after 5k), startups ($250/month/app + $0.02/request after 50k), and larger teams (custom pricing).