Yila AI
AI research agent for academic work
About Yila AI
Yila AI is an AI research agent built for academic work, covering the full arc of a research project from the first literature search to the final figures and slides. Rather than a single chat assistant, it is organized as a set of task-specific agents (playbooks) for literature, writing, data analysis, and presentation, each handling a concrete step a researcher actually performs. The problem it solves is the sheer volume of busywork in research: searching every database, screening dozens of papers to find the few worth reading, formatting citations, running statistics, and typesetting to a journal template all consume time that could go to the actual thinking. Yila automates those steps so researchers spend more time on discovery and less on mechanics.
The platform spans the literature workflow (research-gap validation, cross-database literature search, paper triage, full literature review that reads 50-plus papers and drafts with citations, bilingual side-by-side reading, structured evidence cards, and multi-paper evidence matrices), the writing workflow (turning results and notes into manuscript sections, polishing prose for a target journal, and auto-formatting to journal templates), the data workflow (turning a question into an executable analysis plan, auto-checking and analyzing uploaded data, exploratory data analysis, and statistical tests with written results), and the presentation workflow (publication-quality scientific figures from a sentence, academic posters from a paper, and editable PPTX slides for talks or a defense). Payments are processed by Stripe, with card and WeChat Pay options.
A researcher picks the agent that matches the task at hand. To scope a project, the research-gap agent tests whether a topic is open and feasible, and the literature-search agent queries major academic databases at once. To process the reading list, paper triage screens which papers are worth the time, the literature-review agent reads 50-plus papers and drafts a review with citations, and evidence cards and matrices structure what each paper contributes. For analysis, you turn a question into an executable plan, upload a dataset for automatic checks and analysis, and get statistical tests written up as results. For output, the writing agents turn notes and results into manuscript sections and polish them for a target journal, while the presentation agents generate publication figures, posters, and editable slides. Each task runs as a multi-step agent, and work is metered in credits that refresh with each billing period.
- •Literature Search and Review - Searches all major academic databases at once, triages which papers are worth reading, and runs a literature-review agent that reads 50-plus papers and drafts with citations.
- •Structured Evidence Tools - Produces evidence cards from a single deep read and evidence matrices that compare findings across papers, plus bilingual side-by-side reading of a paper line by line.
- •Data Analysis Agents - Turns a research question into an executable analysis plan, auto-checks and analyzes uploaded data, surfaces distributions and quality at a glance, and runs statistical tests with written-up results.
- •Manuscript Writing - Converts results and notes into manuscript sections, polishes prose for a target journal, and auto-formats to journal templates.
- •Publication Figures and Posters - Generates professional scientific figures from a single sentence, builds an academic poster from an uploaded paper, and exports editable PPTX slides for a talk, lecture, or defense.
- •Credit-Based Plans - Each tier grants a monthly credit allowance that refreshes on renewal, scaling from individual everyday use to sustained, high-output research programs.
Yila AI is built for academic researchers, PhD students, and postdocs who need to move faster through literature reviews, data analysis, and manuscript preparation. Individual researchers on the Starter plan use it for steady everyday work, while labs and frequent authors on the Pro and Flagship tiers run parallel topics and batch delivery. Students preparing a thesis or defense use the slide and poster agents to turn a paper into presentation material, and anyone writing for a specific journal uses the polish and typesetting agents to meet formatting requirements. Researchers working across languages benefit from the bilingual reading agent, and data-heavy fields use the analysis and statistics playbooks to go from raw data to written results without separate statistical software.
