The research scientist
that never sleeps.
Hand Mindify a question. It plans the study, reads the literature, runs experiments on real hardware, versions every result, and writes the paper — while you watch each step live.
› /goal characterise scaling laws for sparse attention on long-context retrieval
◷ planning · 6 steps
✓ searched arXiv — 14 papers · ✓ inspect_gpu — RTX 3080 Ti, 16 GB
⟳ run_python — sweeping seq_len ∈ {2k…64k} · record_experiment sparse-attn/sweep-v3
✓ compile_latex — report.pdf ready
summary written to report.md
A full research stack, autonomous.
Every capability a graduate researcher needs — wired into one agent that uses them on its own.
Plans like a scientist
Decomposes a question into a research plan, then keeps a living to-do list you can watch update as evidence comes in.
Reads the literature
Searches arXiv and the live web, reads primary sources, and cites everything inline. No invented references.
Runs experiments
Writes and executes Python, discovers and uses your local GPU, and verifies quantitative claims instead of guessing.
Tracks every result
Records each experiment with automatic naming and versioning into a database you can query with plain SQL.
Writes the paper
Drafts a structured report and typesets publication-quality PDFs with LaTeX — compiled, not hallucinated.
Works while you sleep
Launch a long-running goal with /goal and reconnect anytime. The run survives your browser closing.
How a study runs.
Pose the question
Type a research question or drop a /goal for a long-running investigation. Pick Anthropic, OpenAI, or a local Ollama model.
Watch it work
The plan, every literature search, code run, and GPU probe streams into the Lab live. Nothing is hidden behind a spinner.
Keep the record
Experiments are versioned into a queryable database. The final report and compiled PDF land in your workspace.
Put a scientist to work tonight.
Start free with your own model keys, or let Mindify run on managed compute.