Now in early access — 2,400+ researchers already inside

Research. Write. Train.
All in one workspace.

Five AI modes that adapt to your work — from literature synthesis and protein analysis to model training, LaTeX papers, and research-level math.

Synthesize 50 papers on transformer architecture and identify open research gaps

Try it now
Five modes, one workspace

Switch instantly. Keep everything.

Research

Full-cycle research automation: from framing hypotheses and synthesizing literature to planning experiments, GPU training, running evaluations, and drafting manuscripts.

Literature SynthesisHypothesis FramingManuscript Drafting
✓ Context preserved (29k tokens)

Biology

Your specialist for both wet-lab and computational biology — covering protein design, genomics, pathway analysis, and biomedical reasoning workflows.

Protein DesignGenomicsPathway Analysis
✓ Context preserved (47k tokens)

Flywheel

Turn production usage into compounding model gains — automatically design fine-tunes, run evaluations, and continuously ship better versions.

Auto Fine-tuningEvaluationsModel Shipping
✓ Context preserved (18k tokens)

Write

Transform rough notes into publication-ready papers with structured arguments, fact-checked citations, clean LaTeX, and camera-ready layouts.

LaTeX OutputCitation VerificationCamera-Ready
✓ Context preserved (25k tokens)

Mathematics

Solve anything from arithmetic to research-level mathematics — step-by-step working, KaTeX-rendered proofs, formal theorem proving, function graphs, and web-grounded solutions from MathOverflow and arXiv.

Step-by-Step ProofsKaTeX RenderingFunction Plots
✓ Context preserved (26k tokens)
1000s of pipelines

A workflow for almost everything.

Research

Literature Synthesis Pipeline

Condense 100+ papers into one organized survey

Biology

Protein Structure Analysis

Execute AlphaFold variants on your own sequences

Flywheel

Custom Data SFT Fine-Tuning

Supervised fine-tune DeepSeek on specialized datasets

Write

Paper Drafting

Go from outline to a LaTeX-ready first draft

Research

Research Hypothesis Builder

AI-guided formulation of research questions

Biology

Genomics Analysis Pipeline

Perform variant calling, annotation, and pathway mapping

Flywheel

Benchmark Harness Configuration

Automated benchmarks across model checkpoints

Write

Paper Structure Builder

Convert notes into a well-organized paper structure

Research

Experiment Design Tool

Plan ablations and statistical testing strategies

Biology

Compound-Target Screening

Screen compound libraries against specific protein targets

Flywheel

Preference Data Generator

Automatically generate preference pairs from production logs

Write

Citation Fact-Checker

Live fact-checking against OpenAlex and PubMed

Math

Step-by-Step Solver

Full working for any integral, ODE, or algebra problem

Math

Proof Assistant

Formal proofs by induction, contradiction, and direct methods

Math

Practice Generator

Unlimited problems across 33 math topics with graded solutions

Math

Linear Algebra Suite

Eigenvalues, SVD, matrix transformations with visualizations

View all workflows →
Your keys. Your compute.

Bring the tools you already trust.

GitHub
Repositories and version control
Hugging Face
Models, datasets, and Spaces
Weights & Biases
Track experiments
Modal
On-demand GPU compute
Prime Intellect
Distributed model training
Pinecone
Vector search database
OpenAlex
Open academic knowledge graph
PubMed
Biomedical research database
Agents that keep going

Built to run while you're away.

Stateful Sandboxes

Every agent runs inside an isolated, stateful environment with full checkpointing and reliable resume.

Resume from any state without manual intervention
Runs stay fully reproducible
Context is preserved through disconnections

Flexible Compute Scaling

Go from a single analysis node to a full GPU cluster — no need to change prompts, workflows, or context.

Covers single-CPU sessions all the way to multi-GPU clusters
Training, evaluations, and writing in one unified flow
Resources allocated dynamically by task demand

Background Job Orchestration

Send long evaluations, training runs, and literature pipelines to a background queue while you're away.

Jobs keep running even when you close the browser
Artifacts are collected and organized automatically
Results delivered to your dashboard, ready when you return
Research-grade infrastructure

Long-horizon RL environments, built for scientific work.

Build RL environments and process-based training data for LLMs — beginning with agentic coding environments designed for ML research workflows.

Begin building
AI-driven coding environments
Process-level reward signals
End-to-end evaluation pipelines
Coordinated multi-agent systems
A note from the founder

I created Veil because I kept jumping between five separate tools just to complete a single research task — reading papers in one tab, running models in another, writing in a third. Every switch shattered my flow and wiped my context.

Researchers and ML engineers deserve a workspace where the AI holds the full context of their work — not just the last message. That's what Veil is. One unified workspace, five specialized modes, thousands of workflows, your own compute — all together, always in sync.

Veil
Vibhor Pandey
Founder, Veil Research — UPES University, Dehradun
vibhorpandey09@gmail.com

Research smarter.
Build stronger models.

Join researchers who are running experiments, reviewing literature, and training models — all inside one seamless workspace.