Ideas without a clear test
A new method needs a precise question, a testable hypothesis, and a definition of what would count as progress.
EARLY STAGE. RESEARCH FIRST.
From research idea
to experiment plan.
ResearchFlow helps machine learning researchers structure ideas, papers, baselines, experiments, ablations, and evaluation plans with AI.
No sign-up required / Bootstrapped & in development
RESEARCH, WITH A CLEAR NEXT STEPFIG. 01
THE STARTING POINT
Can retrieval improve factual accuracy in a small language model?
EXPERIMENT PLAN
Illustrative draftRetrieval-augmented QA
01
Research question
Does retrieved context improve answer correctness?
02
Baselines & evaluation
Closed-book vs. retrieval · exact match & token F1
03
Ablation studies
Context length · retrieval depth · reranking
IDEA → QUESTION → PROTOCOL
BUILT AROUND THE RESEARCH PROCESS
Clear questions+Thoughtful comparisons+Reproducible plans
01 / THE PROBLEM
A promising idea is only
the beginning.
Between reading a paper and running an experiment, there’s a lot to work out. ResearchFlow is being built to make that thinking more structured.
Too many moving parts
Datasets, baselines, metrics, and compute constraints need to fit together before implementation begins.
Details lost between tools
Paper notes, experiment decisions, and implementation tasks often live in different places. The context gets scattered.
02 / THE WORKFLOW
Give your next idea a plan.
The workflow we’re building keeps the researcher in control,
from the first question to the first implementation.
01
Start with the idea
Bring a research question, paper notes, or an abstract. Add your task, data, and practical constraints.
INPUT / IDEA + CONTEXT02
Structure the experiment
Work toward a coherent draft: hypotheses, meaningful baselines, evaluation criteria, and ablation studies.
PROCESS / RESEARCH PLANNING03
Review, refine, implement
Check the assumptions, adapt the plan to your resources, and turn the next steps into an implementation checklist.
OUTPUT / AN ACTIONABLE PLANThe demo below previews this structure using browser-local templates. AI assistance is in development.
03 / CORE FEATURES
The essentials of
a well-designed experiment.
PRODUCT DIRECTION
Six connected parts of the ResearchFlow workflow. Explore their structure in the planning demo.
01
Research questions
Translate an open-ended idea into a focused question and a hypothesis you can test.
02
Baseline planning
Define fair comparisons, reference methods, and the conditions that should stay constant.
03
Dataset decisions
Document data requirements, splits, access considerations, and possible sources of leakage.
04
Evaluation plans
Choose task-appropriate metrics and specify how results and uncertainty will be reported.
05
Ablation studies
Isolate which components matter with controlled, one-variable-at-a-time comparisons.
06
Implementation checklists
Carry research decisions into concrete tasks, from environment setup to result analysis.
04 / TRY RESEARCHFLOW
Less blank page.
More next steps.
INTERACTIVE WORKFLOW PREVIEW
Try an idea. Get a structured draft you can review and export. No account needed.
EXAMPLE PLAN
Draft for reviewRetrieval-augmented QA
A starting example. Change the idea and create your own draft.
IDEAS IN. STRUCTURE OUT.
Drafts are planning suggestions, not verified literature reviews or experimental results.
05 / ABOUT RESEARCHFLOW
Early stage.
Long-term curiosity.
ResearchFlow is a bootstrapped, early-stage AI product currently being developed for machine learning researchers.
The goal is straightforward: help researchers move from a paper or promising idea to a clearer, more reproducible experiment plan. AI can help organize the work. The scientific judgment stays with you.
Independently bootstrapped Currently in development
06 / CONTACT
Help shape what comes next.
Questions, research workflows, or feedback on the demo?
We’d like to hear what would make ResearchFlow useful to you.
LET’S TALK RESEARCH
Our contact channel is being set up.
Please check back for direct contact details.07 / YOUR PRIVACYPrivacy PolicyUpdated October 7, 2026 +
This policy describes the ResearchFlow website and its current interactive demo. It will be updated when the product’s data handling changes.
Demo inputs and drafts
The demo processes text entirely in your browser. It does not send your research idea or dataset name to ResearchFlow or to an AI provider. Inputs and generated plans are held in the current tab’s memory; this website does not store them in cookies or local storage. Reloading or closing the tab clears the demo state. If you copy or export a plan, that copy is under your control.
Website hosting
Your browser sends ordinary request information, such as an IP address, browser information, and requested page, to the hosting infrastructure to load the site. Hosting providers may process technical logs to deliver and secure the website. ResearchFlow has not added analytics, advertising trackers, or tracking cookies to this page.
Contact information
If you contact ResearchFlow by email once a contact address is available, the information you choose to send may be used to respond to your inquiry. Email is handled by the relevant email providers. Avoid sending confidential research, credentials, or sensitive personal information.
External services and future features
The current demo has no accounts, paper uploads, payments, or live AI service. Any future feature that changes what data is collected or shared will need updated privacy information before use.
Questions
Privacy questions can be directed to the contact channel above once available.