Agentic Research Pipeline
An autonomous agent loop that decomposes natural-language research prompts into executable plans — from exploratory data analysis through model training to publication-ready reports.
On-Premise Deployment
Ships as a containerized stack onto your DGX or GPU cluster. Data never leaves the building. Air-gapped, HIPAA-aligned, designed for organizations that cannot move their data to the cloud.
Planner
Receives natural-language research objectives. Decomposes into a multi-step plan with checkpoints and human-review gates.
EDA Agent
Profiles distributions, missingness, target leakage, class imbalance. Generates visualizations and a data quality report before any modeling begins.
Feature Engineering
Domain-aware feature creation. Understands clinical hierarchies, spectral transforms, ICD codes, OMOP CDM, genomic variant encoding, and time-to-event structures.
Modeling Agent
Writes and executes real code — XGBoost, LightGBM, PyTorch, TensorFlow. Iterates on hyperparameters, compares architectures, and explains why one approach outperformed another.
Evaluation
Beyond accuracy. Calibration curves, fairness metrics, subgroup analysis, clinical utility, decision curves, and FDA-ready model cards and validation documentation.
Report Agent
Produces publication-quality outputs — LaTeX manuscripts, executive summaries, interactive dashboards — with proper citations and full reproducibility artifacts.
Not AutoML. A Research Teammate.
Existing platforms optimize for speed-to-deployment. We optimize for research depth. AID3D doesn't drag-and-drop a model — it reasons about your data, proposes hypotheses you haven't considered, runs overnight experiments, and presents findings in the morning. It maintains a research backlog your team can prioritize. It's the scaling function for organizations sitting on massive data lakes with more questions than data scientists.
Healthcare & Clinical
EHR data, clinical signals, imaging features, and patient outcomes — research pipelines that run inside hospital data silos.
Pharma & Biotech
Genomics, proteomics, drug response data, and clinical trial analytics on proprietary compound libraries.
Life Sciences Research
Multi-omics integration, signals processing, and large-scale observational study analysis with regulatory-grade documentation.