MyMagic AI

What is MyMagic AI?

MyMagic AI is a batch inference service and orchestration platform for running large language models over big sets of files. You place files in your own AWS S3 or Google Cloud Storage bucket, call the completions API with a model, question and optional JSON schema for structured output, and receive a job ID. You then poll a job status endpoint until the job is queued, processed and complete, and results are written back to the same bucket folder. The supported models include Mistral-7b, Mixtral-8x7, CodeLlama-70b, Llama2-7b, Llama2-70b and Llama3-70b. Its documentation also describes a workflow layer where YAML flows chain tasks, run on schedules or file events, and support plugins in languages such as Python, R, Julia, Ruby, Shell and Node.js. Typical uses are extraction, summarization and sentiment classification for research, media monitoring, social listening and lead generation. The pricing details are not confirmed in the documentation, so check the pricing page on the vendor's site.

Use cases

• Extract fields from large document sets
• Summarize large bodies of text
• Classify text and run sentiment analysis
• Monitor media and social listening data
• Schedule recurring LLM batch jobs
• Generate structured JSON from unstructured files

Who it's for

• Data engineers
• AI developers
• Research and analytics teams
• Lead generation teams

Why use MyMagic AI

• Keeps your data in your own bucket, with access limited to an IAM role you control.
• Handles large file sets as one batch job instead of many individual calls.
• Workflows can run on a schedule or when new files arrive.
• The vendor says open-source models for batch jobs can lower costs.
• Structured output makes results easier to feed into other systems.

MyMagic AI features

• Batch completions API with job IDs and status checks
• Structured output through a JSON schema
• Open-source models including Mistral, Mixtral, CodeLlama and Llama
• Reads from and writes to AWS S3 or GCS buckets
• YAML workflows with scheduling and file-event triggers
• Plugins and scripts can be written in Node.js, Shell, PowerShell, Ruby, Julia, R or Python
• Live monitoring of workflows and full-text search of execution logs
• Deployment on serverless, hybrid cloud, on-premise VMs or Kubernetes

MyMagic AI integrations

• AWS S3

How to get started with MyMagic AI

1. Sign up to get a personal access token and set up read and write access to your S3 or GCS bucket.
2. Put your files in a folder named after your token and session, then call the completions API with a model and question.
3. Poll the job status endpoint until the status shows Completed.
4. Collect the output file from your bucket, or chain steps with a YAML workflow.

MyMagic AI limitations

• You must create an IAM role so the service can read and write your S3 bucket
• Documented models are open-source LLMs listed in the API reference
• Job results are returned after asynchronous processing rather than instantly

MyMagic AI pricing

We couldn't confirm pricing on the official site. Check mymagic.ai for current prices.

Prices can change and may vary by country or exclude tax. Check the official pricing page.

MyMagic AI alternatives

The main MyMagic AI alternatives listed on Debuly are Together AI, Fireworks AI, Anyscale, Modal, LlamaIndex and Extend. The table compares pricing and platforms; order is A–Z.

1. 

   Anyscale

   Managed platform for running Ray workloads, with pay-as-you-go compute and options to deploy in your own cloud.

   Developer platformsAutomation and agents
   PaidVisit Anyscale (official site)
2. 

   Extend

   Document processing APIs for parsing, extracting, splitting, classifying and verifying documents for AI agents and pipelines

   Developer platformsAutomation and agents
   FreemiumVisit Extend (official site)
3. 

   Fireworks AI

   Inference and training platform for open models: pay-per-token serverless APIs, GPU deployments, fine-tuning and reserved capacity.

   Developer platformsCodingAutomation and agents
   PaidVisit Fireworks AI (official site)
4. 

   LlamaIndex

   Open-source framework plus the LlamaParse platform for parsing, extracting and indexing documents so LLM apps can use them.

   Developer platformsResearch and searchAutomation and agents
   FreemiumVisit LlamaIndex (official site)
5. 

   Modal

   Serverless cloud platform for running AI inference, training, batch jobs and agent sandboxes, billed per second of compute.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Modal (official site)
6. 

   Together AI

   AI cloud for running open-source models through serverless and batch inference, dedicated endpoints, GPU clusters and fine-tuning.

   Developer platformsCoding
   PaidVisit Together AI (official site)

MyMagic AI FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

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