For Teams & Employees
Stop Juggling Models.
Start Finishing Tasks.
Many tool providers focus on offering a large suite of models. We focus on workflows for specific real-world tasks. Leave the model optimization to us.
The Problem: Your Team Shouldn't Be Prompt Engineers
Each AI workflow benefits from specific models. Benchmarking, evaluating, and prompt engineering for these models is hard and time-consuming. That expertise is what we bring to the table.
Each model requires a specific style of prompt. When you start chaining models of different forms and types — an LLM into a diffusion model into an upscaler — the complexity multiplies.
Instead of handing your workers raw model endpoints and expecting them to figure out the best way to use them, leave that to us. Let your employees focus on choosing the right workflow to match the job. They focus on execution and quickly delivering results — not testing, benchmarking, and tuning.
Pick a Workflow, Get Results
Your team doesn't need to know which model is best. They browse workflows by job title, pick the one that matches, upload their file, and get a production-grade result in seconds.
We Do the Science
Our team benchmarks every new model release against every workflow. When a new model improves results, we swap it in. When it doesn't, we don't. You never have to think about it.
Execution Over Experimentation
Your brand photographer shouldn't spend 3 hours testing prompts. They should spend 3 minutes running a workflow and move on to the next client.
Constantly Get the Best Models
WITH NO WORK ON YOUR END
We are constantly deploying new models and integrating them into workflows when it makes sense. You don't have to follow what new models are released, when they're released, or benchmark them compared to old models.
Just keep using the latest version of the workflow, and we keep you on the cutting edge. Every time you run a spell, you're automatically using the best model available for that specific task — no research, no switching, no downtime.
Automatic Workflow Versioning
When we release a new workflow version, we test it to work for the maximum number of users. There is a small chance (~1%) that the old version was better for your specific use case. If you detect that, we let you pin to the previous version with a single parameter.
// Pin to a previous version if needed
version: "2025-03-01"
Enjoy all the upsides of constantly improving workflows with no work on your end — and a graceful fallback to escape the small chance of a downside.
✕ Without Magic Genie
- •New model drops every week — who evaluates it?
- •Each team member writes different prompts for the same task
- •Hours lost testing, tweaking, and debugging model chains
- •Inconsistent quality across your team's output
- •Your brand photographer becomes a part-time ML engineer
✓ With Magic Genie
- •We evaluate every new model for you, automatically
- •One workflow = one consistent, optimized result every time
- •Pick a workflow, upload your file, done in seconds
- •Production-grade quality, every team member, every time
- •Your brand photographer stays a brand photographer
YOU deploy a brand photographer.
WE do the engineering.
Let your employees focus on the task at hand — running AI workflows to better suit your customer's needs. NOT forcing your team to become machine learning engineers just to benchmark and evaluate their toolset every few days as new models are released.