Aito
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About
Aito is a predictive database designed to bridge the gap between traditional data storage and machine learning. Unlike conventional machine learning platforms that require extensive model training, deployment cycles, and complex MLOps pipelines, Aito allows developers to query predictions, recommendations, and insights directly from their data using a familiar SQL-like syntax. It serves as a hosted instance where data is uploaded and immediately becomes queryable for predictive tasks. This unique approach simplifies the integration of artificial intelligence into applications by treating machine learning as a database operation rather than a separate, complex engineering silo. The platform operates with impressive speed, boasting query latencies consistently under 200ms. Its core architecture supports multiple prediction targets from a single dataset, meaning users do not need to build separate models for different fields or outcomes. Aito also features continuous learning; as new data is uploaded, the system adapts in real-time without requiring manual retraining sessions. This effectively solves the problem of concept drift and model maintenance. Integration is further streamlined through a REST API and pre-built connectors, including an Airtable Marketplace app, making it accessible for both high-code and low-code environments. Aito is particularly well-suited for software engineers, SaaS product teams, and Robotic Process Automation (RPA) developers who need to add intelligence to their workflows without hiring a full team of data scientists. It is heavily utilized in industries like accounting and finance for invoice processing, e-commerce for personalized product recommendations, and customer support for automated ticket routing. Because it is GDPR-ready and EU-hosted in Ireland, it is a strong candidate for European enterprises requiring strict data residency and security standards. What sets Aito apart is the near-total elimination of the "model training" phase. Traditional machine learning typically requires a 3-12 month implementation cycle, whereas Aito allows for deployment in hours to days. It provides a unified language for analysis, assistance, and automation. By providing confidence thresholds and evaluation workflows, it offers the transparency needed for human-in-the-loop systems. Additionally, the company claims a 90% cost reduction compared to traditional infrastructure by removing the need for dedicated GPU clusters and specialized MLOps personnel.
Pros & Cons
Eliminates the need for manual model training and deployment cycles.
Supports multiple prediction targets using a single uploaded dataset.
Delivers high accuracy rates typically ranging between 90% and 98%.
Scales to handle over 10 million predictions per day with 99.9% uptime.
Reduces machine learning infrastructure costs by up to 90%.
Sandbox instances are automatically deleted after 7 days of inactivity.
Free tier is restricted to only 3 hours of active server time per day.
Base paid plan storage is limited to 500MB without upgrades.
Automatic backups are only available starting at the Production tier.
Use Cases
Accounting teams can automate invoice data extraction and GL code prediction to reduce manual entry time.
E-commerce developers can implement personalized product recommendations and smart search to improve site conversions.
RPA developers can add intelligent decision-making and exception handling to automation bots without ML infrastructure.
Customer support managers can automate ticket routing and categorize incoming requests in tools like Freshdesk.
SaaS product teams can build 'next best action' suggestions and autofill features directly into their user interface.
Platform
Task
Features
• rest api integration
• airtable marketplace integration
• confidence threshold scoring
• gdpr-ready eu hosting
• multi-tenant hosted infrastructure
• sub-200ms query latency
• real-time continuous learning
• sql-like predictive syntax
FAQs
How does Aito differ from traditional machine learning platforms?
Aito acts as a predictive database, allowing you to query predictions using SQL-like syntax instead of building and training separate models. This approach reduces implementation time from several months to just a few days.
Does Aito require manual retraining when new data is added?
No, the platform features continuous learning and real-time adaptation. It automatically updates its logic as new data is uploaded, eliminating the need for manual retraining cycles and traditional MLOps maintenance.
What kind of query latency can I expect for production apps?
Aito is designed for real-time performance with a P95 latency of less than 200ms. Typical response times for standard queries range between 20ms and 168ms.
Is Aito compliant with GDPR and other security standards?
Yes, Aito is GDPR-ready and hosted within the EU in Ireland. It uses AES-256 and TLS 1.3 encryption, provides tenant isolation, and includes audit trails for enterprise security.
Can I integrate Aito with Robotic Process Automation (RPA) tools?
Aito integrates directly with major RPA platforms like UiPath and Automation Anywhere. It enables bots to handle complex tasks such as document classification and intelligent exception handling.
Pricing Plans
Dev
EUR75.00 / per month• 500,000 API calls per month
• 500MB storage
• 12h active server per day
• Access to all API endpoints
• Slack support
• Multiple team members
Prod
EUR350.00 / per month• Unlimited API calls per month
• 1GB storage (extendable)
• Unlimited active server per day
• Access to all API endpoints
• Slack support
• Multiple team members
• Automatic backups
Enterprise
Unknown Price• Tailored package
• On-premise deployment available
• Custom storage limits
• Dedicated infrastructure
Sandbox
Free Plan• 5000 API calls per month
• 100MB storage
• 3h active server per day
• Access to all API endpoints
• Slack support
• Shared multi-tenant infrastructure
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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