The research copilot for computer vision

Turn your vision dataset into a research-ready project

Prism.ai analyzes your data, connects it to the literature, and builds a clear path from first hypothesis to reproducible results.

See how it works

Built for researchers, ML engineers, and ambitious vision teams.

See it in action

From dataset to defensible research decisions

Upload a dataset once. Prism.ai measures it, finds grounded research, and turns both into an experiment you can explain.

RESEARCH RUN #24

Brain Tumor MRI Classification

Analysis complete
Dataset Analysis
Literature
Experiment Plan
Code Gen
Report

Images

5,632

Classes

4

Imbalance ratio

1.02×

Class distribution

Measured from upload
Glioma
1426
Meningioma
1408
Pituitary
1402
No tumor
1396

Grounded literature

Deep convolutional networks for brain tumor classification using MRI images

Relevant to the same four-class diagnostic setting and supports transfer-learned DenseNet evaluation.

View OpenAlex source

Recommended architecture

DenseNet-121 + SE

Primary

Strong feature reuse for a balanced, moderate-size MRI dataset, grounded in the selected literature.

5

Connected pipeline stages

OpenAlex

Real literature citations

Plan-aligned

Configurable PyTorch code

Minutes

Dataset to research plan

One connected workspace

Less tool-switching. More defensible research.

Without Prism.ai

  • Search and screen papers across disconnected tools
  • Guess which architecture fits the dataset
  • Rewrite training boilerplate for every project
  • Manually assemble decisions into a report

With Prism.ai

  • Measure dataset quality and class balance first
  • Connect recommendations to real OpenAlex papers
  • Generate plan-aligned, configurable training code
  • Carry evidence through to a research-ready report

One connected workflow

From raw data to research direction

Prism.ai connects every stage of computer vision research, so each decision is grounded in your dataset and the literature.

01
Dataset analysis

Profile structure, quality, balance, and visual patterns in minutes.

02
Literature intelligence

Surface relevant methods, benchmarks, and open research questions.

03
Experiment planner

Turn promising directions into a rigorous, testable experiment plan.

04
Code generation

Generate reproducible training and evaluation code for your stack.

05
Research report

Bring findings, evidence, and next steps into one clear narrative.

Start with your dataset

Ready to accelerate your research?

Turn measured dataset evidence into literature, experiments, code, and a report in one traceable workflow.